proceedings of the icvl 2009

The 4th International Conference on Virtual Learning VIRTUAL LEARNING – VIRTUAL REALITY

www.icvl.eu/2009 www.cniv.ro/2009

ICVL 2009 Awards – Sponsored by Intel Corporation

Excellence Award "Intel®Education" – USD 1000

Special Award "Intel®Education" – USD 500

The ICVL Award is offered in recognition of ICVL papers published within in "Proceedings of the International Conference on Virtual Learning"

ICVL and CNIV Coordinator: Dr. MARIN VLADA

The printing of Proceedings was sponsored by the Ministry of Education, Research and Innovation, National Authority for Scientific Research, ROMANIA

Proceedings of the 4th

International Conference

On Virtual Learning

October 30 - November 1, 2009

MODELS & METHODOLOGIES, TECHNOLOGIES, SOFTWARE SOLUTIONS

, 2009

ICVL and CNIV Partners: Grigore Albeanu, Mircea Popovici, Radu Jugureanu, Olimpius Istrate

www.icvl.eu www.cniv.ro

© Bucharest University Press Şos. Panduri, nr. 90-92, BUCUREŞTI – 050663; Tel.Fax: 021 410.23.84

E-mail: [email protected] Web: www.editura.unibuc.ro

Tehnoredactare computerizată: Meri Pogonariu

ISSN: 1844-8933

MMOOTTTTOOSS

„„The informatics/computer science re-establishes not only the unity between the pure and the applied mathematical sciences, the concrete technique and the concrete mathematics, but also that between the natural sciences, the human being and the society. It restores the concepts of the abstract and the formal and makes peace between arts and science not only in the scientist' conscience, but in their philosophy as well..””

GGrr.. CC.. MMooiissiill ((11990066--11997733)) Professor at the Faculty of Mathematics, University of Bucharest,

Member of the Romanian Academy, Computer Pioneer Award of IEEE, 1996

http://www.icvl.eu/2006/grcmoisil

”Learning is evolution of knowledge over time”

Roger E. Bohn Professor of Management and expert on technology management,

University of California, San Diego, USA, Graduate School of International Relations and Pacific Studies http://irps.ucsd.edu/faculty/faculty-directory/roger-e-bohn.htm

GENERAL CONTENTS

About ICVL 2009 ................................................... 13

Section M&M MODELS & METHODOLOGIES .................................................... 23

Sections TECH TECHNOLOGIES ........................................................................ 179

Sections SOFT SOFTWARE SOLUTIONS ............................................................. 255

Section Intel® Education INNOVATION IN EDUCATION AND RESEARCH ............................ 329

News and Events ICVL 2009 Web site .................................................................... 437

Authors Index ..................................................................... 443

C O N T E N T S

Paper

No. PAPER TITLE AND AUTHOR(S)

Page No.

Section Models & Methodologies

1

E-Learning and Educational Software. Educational Projects and Experience of Implementation in Romania

Marin Vlada, Radu Jugureanu, Olimpius Istrate

25

2

Scientific Knowledge and Solving Problems Modelling. Representation and Processing

Marin Vlada

40

3 Towards virtual learning grid developments

Grigore Albeanu 52

4 How to Model the Design Efficiency of the VLE?

Patrick Wessa 60

5 A model for the evaluation of learning styles design effectiveness

G. Bruno Ronsivalle, Massimo Conte 70

6 Metrics and requierements in Learning Management System

Ion Roceanu, Virgil Popescu 78

7 Mapping the Spaces of Virtual Learning Environments

Ioannis Paliokas 83

8

On line environments to enhance entrepreneurial mindsets in young students

Allegra Mario, Fulantelli Giovanni, Gentile Manuel,

La Guardia Dario, Taibi Davide

91

9

Future of Virtual Learning Methods and User Expectations –

Can Present Methods Flourish Without Change?

Indika Perera

98

10 Learn of the Network Concepts Using Project Based Learning

Costel Aldea, Ion Florea 106

11 Computational Physics with Python

Rubin H. Landau, Cristian C. Bordeianu , Manuel J. Paez 112

The 4th International Conference on Virtual Learning ICVL 2009

9

12

SRoL - Web-based Resources and Tools used for e-Learning of Languages and Language Technology

Silvia Monica Feraru, Horia-Nicolai Teodorescu

119

13

Virtual Learning, Blended Learning and Modern Foreign Languages: Let’s listen to the students!

Nathalie Ticheler

127

14 The eLiTA (e-Learning in Textiles & Apparel) Project

Mirela Blaga, Simon Harlock 134

15 Recommender Systems for Smart Lifelong Learning

Ahmad A. Kardan, Omid R. B. Speily, Somayyeh Modaberi 142

16

A Proposed Structure for Learning Objects Using Ontology

for Effective Content Discovery

Ahmad A. Kardan, Shima Zahmatkesh

151

17

Interdisciplinary and Specialized

Programmers Used in the Practical Part of Teaching a Technical Course

Irina-Isabella Savin, Ioana Pristavu

158

18

Research Project on Implementation of Open Distance Learning Method in University Education

Tudor Bragaru, Ion Craciun

164

19 Knowledge Communication Programs Design

Ioan Maxim, Tiberiu Socaciu-Lendvai 172

Section Technologies

20

Java in Scientific Computation An educational approach

Ernest Scheiber

181

21 New ways of transforming Drupal from CMS to LCMS

Liviu Beldiman, Dorin Canepa 189

22

Management of Knowledge –Base Systems in

Desktop and Mobile Learning Environments

Veronica Ştefan, Ion Roceanu, Cătălin Radu, Ioana Stănescu, Antoniu Ştefan

195

23 e-Tutor - An Approach for Integrated e-Learning Solution

Pradipta Biswas and S. K. Ghosh 203

University of Bucharest and “Gh. Asachi” Tehnical University of Iasi 10

24 A Multilingual Virtual Environment for Shoe Design Training

M. Sahin, A. Mihai, S. Yaldiz, M. Pastina 214

25

Educational software for the simulation of virtual dynamical systems

Puşcaşu Gheorghe, Codreş Alexandru, Codreş Bogdan Stancu Alexandru

223

26

Development Interactive Courses of Education in Microbiology

Based on E-Learning System Applying in Technical College of Yambol

Dineva S., Nedeva V.

231

27

Advantages of the Web-Based Training for the Increasing Quality of Preparation and Self-Preparation of Students from the Specialty

“Food Technology”

Margarita Pehlivanova, Zlatoeli Ducheva, Snejana Dineva

239

28

Dynamics in the meaning negotiation: can online participation and reification be correlated in informal settings?

Nicolò Antonio Piave

247

Section Software Solutions

29

Open learning resources as an opportunity for

the teachers of the Net Generation

Fulantelli Giovanni, Gentile Manuel, Taibi Davide, Allegra Mario

257

30

Applying Agent-Based Technology to University Knowledge Management

Mihaela Oprea, Elia Petre

265

31

Differential Geometry of Surfaces with Mathcad: A Virtual Learning Approach

Nicolae DăneŃ

276

32 Restructuring the Easy Learning On-line Platform

Radu Rădescu, Radu VelŃan, Raul Tudor 284

33 New Operating Tools in the Easy Learning On-line Platform

Radu Rădescu, Adrian Şişu, Raul Tudor 292

34

A Hybrid Recommender System for E-learning Environments Based on Concept Maps and Collaborative Tagging

Ahmad A. Kardan, Solmaz Abbaspour, Fatemeh Hendijanifard

300


11

35

Ranking Concept Maps and Tags to Differentiate the Subject Experts in a Collaborative E-Learning Environment

Ahmad A. Kardan, Fatemeh Hendijanifard, Solmaz Abbaspour

308

36

Validation of Messages in Discussion Groups Using the Learner Model: An Approach to Enhance Trustworthiness

Ahmad A.Kardan, Mehdi Garakani, Somayeh Modaberi

316

37

Using Genetic Algorithms to Increase the Quality of University

Research Management

Florentina Alina Chircu

322

Section Intel® Education

38 Digital education usage models for the classroom of the future

Peter Hamilton, Eileen O’Duffy

331

39 Effective eLearning

Olimpius Istrate

341

40

The evolution of Learning Object repository: Towards the Learning Object Management System

and dynamic use of metadata

Gentile Manuel, Fulantelli Giovanni,

Taibi Davide, Allegra Mario

349

41

E-portfolio and semantic web to support informal learning

in social network environment

Taibi Davide, Gentile Manuel, Fulantelli Giovanni, Allegra Mario

357

42 Integration of Multimedia in class work and lab activities

Carmen – Gabriela Bostan, Ştefan Antohe 364

43 Using data mining techniques in higher education

Elena Şuşnea 371

44 Classification techniques used in Educational System

Elena Şuşnea 376

45

Intelligent Agents as Data Mining Techniques Used in Academic Environment

Irina Tudor, Liviu Ionita

380

46 Knowledge Exchange in an Experimental E-learning System

Iuliana Dobre 385


47 E-literature in E-learning

Zlatko Nedelko, Carmen Elena Cirnu 393

48 Discovering green energy @ portal.moisil.ro

Mihaela Garabet, Ion Neacşu 401

49 Toward A Comprehensive E-Learning Style (CELS)

Ahmad A. Kardan, Seyedeh Fatemeh Noorani 408

50

Social Network Analysis for e-assessment: reliability of formal and informal social reticles


416

51

Using of Suitable Software for Students Education in Clothing Technology

Magdalena Pavlova

424

52 An Approach to the Study of Science for Young Learners

Daniela Popescu, Flavius Popescu 430

About ICVL 2009

ICVL Project – www.icvl.eu

2010 – TOWARDS A LEARNING AND KNOWLEDGE SOCIETY – 2030

VIRTUAL ENVIRONMENTS FOR EDUCATION AND RESEARCH C3VIP: "Consistency-Competence-Clarity-Vision-Innovation-Performance"

© Project Coordinator: Ph.D. Marin Vlada, University of Bucharest, Romania Partners: Ph.D. Prof. Grigore Albeanu, Ph.D. Mircea Dorin Popovici,

Prof. Radu Jugureanu, Prof. Olimpius Istrate Institutions: The Romanian Ministry of Education Research and Innovation,

SIVECO Romania, Intel Corporation

ICVL 2009 is held under the auspices of: – EYCI - the European Year of Creativity and Innovation 2009 – The European INTUITION Consortium – The Romanian Ministry of Education and Research – The National Authority for Scientific Research


Conference Organisation

• General Chair Dr. Marin Vlada, Professor of Computer Science, University of Bucharest, Research Center for Computer Science (Romania), European INTUITION Consortium member

• Technical Programme Chair Dr. Grigore Albeanu, Professor of Computer Science, Spiru Haret University, Research Center for Mathematics and Informatics (Romania)

• Associate General Chair Dr. Dorin Mircea Popovici, Professor of Computer Science, Ovidius University of Constanta (Romania), CERV- European Center for Virtual Reality (France)

• Associate General Chair Prof. Radu Jugureanu, AeL eContent Department Manager, SIVECO Romania SA, Bucharest, Romania

• Associate General Chair Prof. Olimpius Istrate, University of Bucharest, Romania, Education Manager, Intel Romania Bucharest, Romania

October 30-November 1, 2009 – JASSY, ROMANIA

Location: "Gh. Asachi" Technical University of Iasi, Faculty of Electrical Engineering, ROMANIA


15

Organizers: University of Bucharest, "Gh. Asachi" Technical University of Iasi, Siveco Romania, Intel Company

Scientific Committee/Technical Programme Committee / Executive reviewers

Dr. Grigore

Albeanu Professor of Computer Science, Spiru Haret University, Research Center for Mathematics and Informatics, Romania

Dr. Adrian

Adascalitei

Professor of Electrical Engineering Fundamentals, Technical University "Gh. Asachi", Faculty of Electrical Engineering, Iasi, Romania

Dr. Michael E. Auer

Professor of Electrical Engineering, Carinthia University of Applied Sciences, School of Systems Engineering, Villach, Austria General Chair, ICL - Interactive Computer aided Learning, http://www.icl-conference.org/

Dr. Angelos Amditis

Research Associate Professor (INTUITION Coordinator, http://www.intuition-eunetwork.net/), Institute of Communication and Computer Systems, ICCS- NTUA Microwaves and Optics Lab, ATHENS, GREECE

Dr. Grigore

Burdea

Professor of Applied Science (Robotics), Rutgers – The State University of New Jersey, Director, Human-Machine Interface Laboratory, CAIP Center, USA

Dr. Pierre Chevaillier

LISYC – Laboratoire d'Informatique des Systèmes Complexes, CERV – Centre Européen de Réalité Virtuelle (European Center for Virtual Reality), France, European INTUITION Consortium member

Dr. Mirabelle D' Cruz

Virtual Reality Applications Research Team (VIRART), School of Mechanical, Materials and Manufacturing Engineering (M3),University of Nottingham University, U.K., European INTUITION Consortium member

Dr. Steve

Cunningham

Noyce Visiting Professor of Computer Science, Grinnell College, Grinnell, Iowa 50112, USA Department of Computer Science

Dr. Ioan Dzitac Professor of Computer Science, Executive Editor of IJCCC, Agora University,Oradea, Romania

Dr. Victor

Felea Professor of Computer Science, “Al.I. Cuza” University of Iasi, Faculty of Computer Science, Romania


Dr. Horia Georgescu

Professor of Computer Science University of Bucharest, Faculty of Mathematics and Computer Science, Romania

Dr. Radu

Gramatovici

Professor of Computer Science University of Bucharest, Faculty of Mathematics and Computer Science, Romania

Dr. Felix Hamza-Lup

Professor of Computer Science at Armstrong Atlantic State University, USA

Dr. Angela Ionita

Romanian Academy, Institute for Artificial Intelligence (RACAI), Deputy Director, Romania

Olimpius Istrate Intel Education Manager, Bucharest, Romania www.intel.com/education

Prof. Radu Jugureanu

AeL eContent Department Manager, SIVECO Romania SA, Bucharest, Romania www.siveco.ro

Dr. Bogdan

Logofatu

Professor at University of Buchares, CREDIS Department Manager, Bucharest, Romania www.unibuc.ro

Dr. Jean-Pierre Gerval

ISEN Brest (école d'ingénieurs généralistes des hautes technologies), France, European INTUITION Consortium member

Dr. Daniel Mellet-d'Huart

AFPA Direction de l'Ingénierie Unité Veille sur la Réalité Virtuelle MONTREUIL, European INTUITION Consortium member

Dr. Mihaela Oprea

Professor in the Department of Informatics, University of Ploiesti, Romania

Thomas Osburg Intel Education Manager, Europe www.intel.com/education

Dr.

Harshada(Ash) Patel

Virtual Reality Applications Research Team (VIRART)/Human Factors Group Innovative Technology Research Centre, School of Mechanical, Materials and Manufacturing Engineering, University of Nottingham, University Park, Nottingham, U.K., European INTUITION Consortium member

Dr. Dana Petcu Professor at Computer Science Department of Western University of Timisoara, Director at Institute e-Austria Timisoara, Romania

Dr. Dorin Mircea Popovici

Professor of Computer Science, Ovidius University of Constanta, Romania / CERV– European Center for Virtual Reality (France, European INTUITION Consortium member)

Dr. Ion Roceanu

Professor of Computer Science, Director of the Advanced Distributed Learning Department, "Carol I" National Defence University, Bucharest, Romania


17

Dr. Maria Roussou

Virtual Environments and Computer Graphics Lab., Department of Computer Science, University College London, U.K., European INTUITION Consortium member

Dr. Ronan Querrec

CERV – Centre Européen de Réalité Virtuelle (European Center for Virtual Reality), Laboratoire d'Informatique des Systèmes Complexes, France

Dr. Luca-Dan Serbanati

Professor of Computer Science, University "Politehnica" of Bucharest, Romania and Professor at the "La Sapienza" University, Italy, European INTUITION Consortium member

Dr. Doru Talaba

Professor, “Transilvania” University of Brasov, Product Design and Robotics Department, Romania, European INTUITION Consortium member

Dr. Leon

Tambulea Professor of Computer Science, "Babes-Bolyai" University, Cluj-Napoca, Romania

Dr. Jacques Tisseau

CERV – Centre Européen de Réalité Virtuelle (European Center for Virtual Reality), LISYC – Laboratoire d'Informatique des Systèmes Complexes, France, European INTUITION Consortium member

Dr. Alexandru Tugui

Professor at “Al. I. Cuza” University of Iasi, FEAA, “Al. I. Cuza” University Iasi, Romania

Dr. Marin

Vlada

Professor of Computer Science, University of Bucharest, Faculty of Mathematics and Computer Science, Romania, European INTUITION Consortium member

Participate

The Conference is structured such that it will:

• provide a vision of European e-Learning and e-Training policies; • take stock of the situation existing today; • work towards developing a forward looking approach.

The Conference will consider the perspectives and vision of the i-2010 programme and how this will stimulate the promotion, and development of e-Learning content, products and services and the contribution of these to lifelong learning.

Participation is invited from researches, teachers, trainers, educational authorities, learners, practitioners, employers, trade unions, and private sector actors and IT industry.


Research papers – Major Topics The papers describing advances in the theory and practice of Virtual Environments for

Education and Training (VEL&T), Virtual Reality (VR), Information and Knowledge Processing (I&KP), as well as practical results and original applications. The education category includes both the use of Web Technologies, Computer Graphics and Virtual Reality Applications, New tools, methods, pedagogy and psychology, Case studies of Web Technologies and Streaming Multimedia Applications in Education, experience in preparation of courseware.

Thematic Areas / Sections

• MODELS & METHODOLOGIES (M&M) • TECHNOLOGIES (TECH) • SOFTWARE SOLUTIONS (SOFT) • "Intel® Education" – Innovation in Education and Research (IntelEdu)

Objectives

2010 – Towards a Learning and Knowledge Society – 2030

At the Lisbon European Council in March 2000, Heads of State and Government set an ambitious target for Europe to become "the most competitive and dynamic knowledge-based economy in the world" by 2010. They also placed education firmly at the top of the political agenda, calling for education and training systems to be adapted to meet this challenge.

Relevant topics include but are not restricted to:

• National Policies and Strategies on Virtual Learning • National Projects on Virtual Universities • International Projects and International Collaboration on Web-based Education • Dot-com Educational Institutions and their Impact on Traditional Universities • Educational Portals for education and training • Reusable Learning Objects for e-Learning and e-Training • Testing and Assessment Issues of Web-based Education • Academia/Industry Collaboration on Web-based Training • Faculty Development on Web-based Education • Funding Opportunities for Projects in Web-based Education

Learning and the use of Information and Communication Technologies (I&CT) will be examined from a number of complementary perspectives:

• Education – supporting the development of key life skills and competences • Research – emerging technologies and new paradigms for learning


19

• Social – improving social inclusion and addressing special learning needs • Enterprise – for growth, employment and meeting the needs of industry • Employment – lifelong learning and improving the quality of jobs • Policy – the link between e-Learning and European / National policy imperatives • Institutional – the reform of Europe’s education and training systems and how

I&CT can act as catalyst for change • Industry – the changing nature of the market for learning services and the new

forms of partnership that are emerging

General Objectives

The implementation of the Information Society Technologies (IST) according to the European Union Framework-Programme (FP6, FP7)

• The implementation of the Bologna Conference (1999) directives for the Romanian educational system.

• The development of a Romanian Framework supporting the professional and management initiatives of the educational community.

• The organization of the activities concerning the cooperation between the educational system and the economical companies to find out an adequate distribution of the human resources over the job market.

• To promote and implement the modern ideas for both the initial and continuing education, to promote the team based working, to attract and integrate the young graduates in the Research and Development projects, to promote and implement IT&C for initial and adult education activities.

Particular objectives

The development of Research, projects, and software for E-Learning, Software and Educational Management fields

• To promote and develop scientific research for e-Learning, Educational Software and Virtual Reality

• To create a framework for a large scale introduction of the e-Learning approaches in teaching activity.

• To assist the teaching staff and IT&C professionals in the usage of the modern technologies for teaching both in the initial and adult education.

• To improve the cooperation among students, teachers, pedagogues, psychologists and IT professionals in specification, design, coding, and testing of the educational software.

• To increase the teachers' role and responsibility to design, develop and use of the traditional technologies and IT&C approaches in a complementary fashion, both for initial and adult education.


• To promote and develop information technologies for the teaching, management and training activities.

• To promote and use Educational Software Packages for the initial and adult education.

Thematic Areas/Sections

Models & Methodologies (M&M):

• Innovative Teaching and Learning Technologies

• Web-based Methods and Tools in Traditional, Online Education and

Training

• Collaborative E-Learning, E-Pedagogy,

• Design and Development of Online Courseware

• Information and Knowledge Processing

• Knowledge Representation and Ontologism

• Cognitive Modelling and Intelligent systems

• Algorithms and Programming for Modelling

Technologies (TECH):

• Innovative Web-based Teaching and Learning Technologies

• Advanced Distributed Learning (ADL) technologies

• Web, Virtual Reality/AR and mixed technologies

• Web-based Education (WBE), Web-based Training (WBT)

• New technologies for e-Learning, e-Training and e-Skills

• Educational Technology, Web-Lecturing Technology

• Mobile E-Learning, Communication Technology Applications

• Computer Graphics and Computational Geometry

• Intelligent Virtual Environment

Software Solutions (SOFT): • New software environments for education & training

• Software and management for education

• Virtual Reality Applications in Web-based Education

• Computer Graphics, Web, VR/AR and mixed-based applications for

education & training, business, medicine, industry and other sciences

• Multi-agent Technology Applications in WBE and WBT

• Streaming Multimedia Applications in Learning

• Scientific Web-based Laboratories and Virtual Labs

• Software Computing in Virtual Reality and Artificial Intelligence

• Avatars and Intelligent Agents

Topics of interest include but are not limited to:

Virtual Environments for Learning (VEL):


• New software environments for education & training


21

• Web & Virtual Reality technologies

• Educational Technology and Web-Lecturing Technology


• Innovative Web-based Teaching and Learning Technologies

• Software and Management for Education


Virtual Reality (VR):


• Algorithms and Programming for Modeling

• Web & Virtual Reality-based applications

• Graphics applications for education & training, business, medicine,

industry and other sciences


• Software Computing in Virtual Reality

Knowledge Processing (KP):

• Information and Knowledge Processing

• Knowledge Representation and Ontologism




• Cognitive Modelling, Intelligent systems

• New Software Technologies, Avatars and Intelligent Agents

• Software Computing in Artificial Intelligence

Education solution towards 21st Century challenges (IntelEDU):

• Digital Curriculum, collaborative rich-media applications, student

software, teacher software

• Improved Learning Methods, interactive and collaborative methods to

help teachers incorporate technology into their lesson plans and enable

students to learn anytime, anywhere

• Professional Development, readily available training to help teachers

acquire the necessary ICT skills

• Connectivity and Technology, group projects and improve communication among teachers, students, parents and administrators

Section

MODELS & METHODOLOGIES Models and Methodologies (M&M):

• Innovative Teaching and Learning Technologies • Web-based Methods and Tools in Traditional, Online Education and Training

• Collaborative E-Learning, E-Pedagogy, • Design and Development of Online Courseware • Information and Knowledge Processing • Knowledge Representation and Ontologism • Cognitive Modelling and Intelligent systems • Algorithms and Programming for Modelling

E-Learning and Educational Software. Educational Projects and Experience of Implementation in Romania

Marin Vlada1, Radu Jugureanu2, Olimpius Istrate3

(1)University of Bucharest, Research Center for Computer Science, Romania

(2) Siveco Romania, AeL eContent Department, Romania (3) University of Bucharest, Faculty of Psychology and Education Sciences and Intel

Corporation [email protected], [email protected], [email protected]

Abstract The responsibility for education is nowadays shared: collaborative demarches and adequate commitment from all stakeholders is very much increasing the effects of education as a whole, oriented towards preparing competitive human resources equipped with competences for the 21st Century: cooperation, communication, critical thinking, creativity, innovation. In Romania, the emergence of a knowledge-based economy and the need to assure conditions of social inclusion to all for the 21st Century have brought into light the necessity to enhance the continuous development of the human capital according to a lifelong learning perspective. In these regards, innovative education strategies aiming to integrate ICT are effective and viable when supported by several stakeholders: companies, European institutions, NGOs, schools, teachers, education managers, parents and students themselves. The present paper focuses on the use of ICT in Romanian education system, using research data from several reports released in the last year. Throughout the article, we will be paying consideration to two assumptions: firstly, introduction of ICT helps students to have access to knowledge and to develop competencies for the XXI Century: critical thinking, problem solving, creativity, use of ICT; secondly, the introduction of ICT helps teachers improve the way they educate, by employing various updated resources, by improving their methods, by exchanging resources and ideas within larger online communities of professionals. Keyword: E-Leanrning, educational software, knowledge society, develop competencies.

1 Introduction and Motivation The general trend of Romanian society towards intensive use of new technologies, generated by the need to keep up with the evolving European economy, is encouraged, supported and pushed ahead by governmental programmes and complemented by several European initiatives or by projects developed by private companies. “Today’s pupils took part actively in transforming the IT labs in classrooms, redefining IT as a support for teaching and the computer as a support for training. We are determine to involve the pupils more and more in developing their own knowledge as well as in the process of creating educational resources meant for future generations”, R. Jugureanu, Vision 2020


– How Pupils See the Future of Education [6]. In the United States and also in UNESCO strategies these are referred to as the 21st Century Skills. The European Union in the Lisbon framework outlines eight domains of Key Competences for Lifelong Learning. These 21st Century Skills are critically important to support the challenges of the modern work-place and the dynamic and rapidly changing knowledge society. Highly structured and disciplined schooling systems do not necessarily prepare students well for the dynamics and challenges of the 21st century workplace and society. More self-motivated, individualized, group and collaborative learning processes, supported by ICT will contribute significantly to the preparation of a more agile modern workforce. 2 IT-Based Education System in Romania (SEI Program) One of the most effective governmental action is the SEI Programme (Sistem Educational Informatizat – IT-Based Education System), started in 2001, aiming to equip schools with computer labs, to train teachers in the use of ICT, and to provide educational software to support the teaching and learning. The IT Based Educational System (SEI) is a complex program initiated by the Ministry of Education, Research and Innovation, aiming to offer ICT support for the Romanian education system. The Program is implemented in partnership by the state administration (RMER) and the private sector. The main companies involved in SEI implementation are the Romanian company SIVECO Romania SA, HP and IBM. SEI is aiming to provide all schools in Romania with complete IT solutions for use in the teaching/learning process. Also, the SEI program promotes ICT in education through specific projects designed both for administrative and educational purposes. The SEI Program offers new tools for use in schools, thus increasing the quality of the education process. It offers a substitute for expensive or dangerous instruments and experiments by means of virtual counterparts. Within SEI Program, the local, regional and country administration is provided with managerial and administrative support. The main components of the solution are: Hardware (IT laboratories); Learning, Content Management Solution (the AEL software system); Educational software and electronic educational content; Teacher training; Internet connectivity. AeL is an integrated Learning and Content Management System developed by SIVECO aimed to support professors/tutors, students, content editors, administrative staff and other stakeholders in the learning process. AEL is qualified of management and delivery of various content types such as interactive multimedia, tutorials, exercises, simulations, educational games etc. Its powerful knowledge base, which acts as a content repository and management solution, adaptive, configurable and searchable, allows first-time users to easily:

– create content (built-in HTML editor, mathematical formulae editor, test editors and wizards, glossaries/dictionaries editor);

– import/export content from files, archives/folders of resources, standard packaging formats like SCORM and IMS;

– adapt or modify content; – derive their own courses from common content components. These are the stages in the SEI implementation:


27

– SEI-1 (2001-2002): the pilot period – design and experimental use of the main components, adjustments at different levels based on the data that were obtained;

– SEI-2 and SEI-3 (2003-2004): the transition period – the communication lines and technical support were established, the general methodology for implementation was developed and the favourable area was covered at high-school level; the methodology for construction, approval and distribution of multimedia educational contents;

– SEI-4 (2005-2008): period of the construction and generalisation of ICT in the education system.

2.1 Effects of SEI program in Romania The results of this process are presented in a synthetic form (December, 2006):

• equipment: 76,000 computers and servers; 4,780 laboratories, auxiliary equipment included;

• IT labs at the Ministry of Education and the 42 county school inspectorates and teacher centres;

• computers for administrative use; • educational software in every laboratory for teaching, testing and assessment,

school management, educational content management. The multimedia educational content distributed in each school includes 1650 lessons

for grades 5 – 8 (gimnaziu) and 9 – 12 (high-school), 8500 lesson moments for: biology, mathematics, computer science, languages, history, geography, chemistry, physics, technology etc.; encyclopaedias, dictionaries, glossaries. Some 25,000 high-school teachers and 40,000 gimnaziu teachers have been trained in the use of ICT. The results of the 4th stage speak for themselves: 3270 laboratories in schools; 42 laboratories for the teacher centres; updates for the laboratories established in 2001; 1255 multimedia lessons; multimedia English lessons for grades 1 - 8; 40,000 teachers included in the training programmes.

An in-depth investigation carried out in 2008 by a group of researchers from several institutions reveals the following aspects of the SEI Programme: (a) to what degree different types of schools are provided with computers and other equipment, (b) students’ and teachers’ access to the new technologies, (c) to what degree these technologies are used, (d) the impact the use of the new technologies had in the beneficiaries’ view (managers, teachers, students), including different kinds of problems which require interventions/ solutions, as well as human/technological/ financial resources. Representative samples in each category of beneficiaries were returning their opinions relevant for the entire Romanian education system: 195 school managers, 1588 teachers and 3953 students. We can already say that the SEI Programme establishes in the Romanian schools working practices based on 1:1 student-computer interaction model. In time, “lessons in the SEI laboratory” will become regular lessons – as frequent as the other lessons – where each student has access to an individual computer (Fig. 1).

With regard to the type of learning activities carried out with students, it’s relevant to mention the average scores [Based on the average which resulting from the transformation into a 0-1-2 scale of the ranking of activities based on their frequency


(never-rarely-often)] which are higher for diversified activities in urban schools, especially with regard to those activities that encourage creativity and for activities which use the Internet (Table 1).

0%

10%

20%

30%

40%

50%

60%

70%

Series2 58,70% 4,00% 12,30% 3,70%

In the SEI lab, using

AeL

In a computer lab,

without AeL

In a regular class,

with computer and

videoprojector

Other situation

Figure 1. Situations in which ICT is used for teaching-learning-evaluation Total R U

Sequences when teaching and learning involve the use of electronic lessons (for my subject)

1.036 1.000 1.092

Tasks when the students work individually using ICT 0.965 0.912 1.051 Tasks when the students work in groups using ICT 0.958 0.929 1.003 Sequences when the students learn to use computer programmes (editing, computing, Internet browsing)

0.851 0.875 0.836

Sequences when the students use the Internet look for information

0.848 0.559 1.026

Activities when the students are required to be creative, to explore and to innovate, using especially ICT resources and/or the Internet

0.816 0.682 1.028

Activities having as a result a multimedia product (a film, a web page, a presentation)

0.655 0.539 0.833

Table 1. Types of teaching&learning activities involving the use of ICT; rural-urban

differentiation

On average, a little past half (53.1%) of the students who participate in lessons taking place in the computer laboratory have access to an individual computer, 34.9% share a computer with a classmate at the same time, 7.1% share a computer with other two classmates and 1.3% work together with other three colleagues on the same computer, and 1.7% of the students work in groups even larger on the same computer.


29

Differences between educational levels are considerable in point of the number of students using a computer at the same time during classes in the computer laboratory as follows: most of the students who work alone on a computer are high-school (HSC) students (67.8%), and only 25% are gymnazium students (Table 2).

In this situation, it is obvious that the most significant inconveniences encountered by students during classes in the SEI laboratory are the limited time for computer use during classes, indicated by 35% of the students, and the number of students per computer, mentioned by 21% of the students.

Total GIM HSC

1. One student 53.1% 25.5% 67.8% 2. Two students 34.9% 54.5% 24.7% 3. Three students 7.1% 12.9% 3.8% 4. Four students 1.3% 2.0% 0.9% 5. Other: 1.7% 3.2% 1.1% No answer 2.0% 1.9% 1.8% Total 100.0% 100.0% 100.0%

Table 2. Number of students per computer

Extending the range of possibilities for using the computers available in the school to a series of current activities carried out by teachers (Table 3), we find out that the equipment and the Internet connection are mainly used by teachers for:

– consulting the school legislation or the news on the Internet: 54.4% – creating worksheets for students, informative materials, sketches, assessments:

50.1% – searching information to help them prepare the lessons – 46.4%. At the opposite end, teachers use the new technologies least for creating educational

soft (56.9% saying they don’t use at all a computer for this activity), for communicating with students after school hours (49.2%) or with their parents (64.7%).

Activities carried out with the use of computers Average

consulting school legislation or news on MoE website, official portals etc. 1.403

creating worksheets for students, informative materials, sketches, assessments etc. 1.384

information to prepare the lesson 1.375

teaching-learning activities in the computer laboratories 1.067

administrative activities: student records, filling-in pedagogical and psychological forms etc.

1.015

use of educational resources (enciclopedias, picture libraries, dictionaries etc.), delivered and installed by MoE/ school inspectorate/ Siveco Company

0.967

communication with teachers from other schools, via email, chat or the Internet 0.920

computer-based assessment tests for students 0.892

designing development projects for my school 0.755

contact with my students, outside school hours 0.549

creating educational soft 0.342

contact with my students’ parents via email or the Internet 0.291

Table 3. Types of teaching-learning activities involving the use of ICT


Regarding the continuous professional development, teachers begin to see the value of the Internet and computers for information and documentation activities, for distance courses, for exchanges of experience, for learning computer programmes, for publication of articles etc. The use of the new technologies for professional development looks pretty much the same in rural and urban areas, teachers being equally aware of the opportunities of the computerisation process.

However, we can see that the use of ICT is still at the beginning and still far away from the quality and competitiveness promoted by the Ministry of Education and the strategy documents and recommendations of the European Commission: in early 2008, one in five Romanian teachers had never used the new technologies for information and documentation purposes, and one in four teachers said they had used only once in a semester a computer or the Internet for such activities.

Use of computers for professional

development in rural schools

22,1%

27,0%

14,0%

9,1%

7,3%

4,7%

11,9%

3,7%

Use of computers for professional

development in urban schools

21,0%

26,2%

17,0%

9,8%

5,3%

3,9%

14,5%

2,3% Never

Once per semester

2 times per semester




More than 6 times

NA

Figure 2. Use of computers for teachers’ professional development; rural-urban differentiation

2.2 Effects of ICT Use in Education

Speaking about the effects of ICT use for learning-teaching-assessment, the teachers ranked some potential benefits, from several points of view (Table 4):

With regard to teachers, ICT contributes first to the facilitation of learning objectives, and then to the facilitation of teacher’s activity; the modernisation of the educational process is not seen by teachers as an important argument for using ICT in designing, teaching and assessment activities;

With regard to students, teachers consider that classes in the computer laboratory are useful first because they facilitate students’ understanding. Then, they mentioned the development of computer use skills, and last they pointed to the role of the new technologies in attracting and motivating students for higher achievement;

With regard to the organisation of the education process, the benefits of ICT are seen by teachers especially in connection with active, participative learning, as well as with cooperative learning; the contribution of ICT to individual or personalised learning is


31

surprisingly ranked last, although the majority of educational applications are more suitable for individual learning.

Segment Poz Estimated effects Average place

1 facilitates the learning objectives 1.856 2 facilitates teacher’s activity (design-teaching-assessment) 1.717

Teacher

3 encourages innovation/ modernisation of the teaching process 1.585

1 facilitates understanding of different phenomena 1.973 2 develops computer use skills 1.593

Student

3 improves the learning outcomes/ attracts students, develops interest in studying

1.534

1 favours active, interactive, participative learning 1.787 2 allows cooperative learning, develops team work abilities 1.785

Didactic activity

3 allows individualised/ personalised learning 1.501

Table 4. Positive effects of using SEI laboratories in teachers’ view 2.3 Impact of ICT Courses on Teaching Practice The attendance of ICT courses by teachers is equitably distributed among areas of residence and education levels. But one third of the Romanian teachers did not attend any course on the new technologies, which is surprising when considering the early initiatives, projects, and programmes for the introduction of ICT in the Romanian education system.

With regard to the usefulness of the existing training programmes (Tabel 5), when compared to the concrete needs for classroom activities, most teachers (58.3%) think they are appropriate for start, but the development of efficient learning activities based on the new technologies requires direct experience and a lot of practice. 7.4% of the teachers consider that the initial and in-service training programmes should be improved. To what extent do you think that the initial and/or in-service training programmes in which you participated are appropriate when considering the practical use of computers for classroom activities?

They are appropriate in a first stage, but I still need more practice 58.3% They are appropriate and meet the requirements of real use; I don’t need more other courses so as I can carry out efficient learning activities with the help of ICT

17.2%

They are inappropriate; the courses I attended are not enough for me to design and carry out learning activities with the help of ICT

7.4%

I don’t know/ I have no opinion. 11.4% No answer 5.7% Total 100.0%

Table 5. Opinions on the usefulness of training programmes for the use of computers in the classroom


The introduction of more simulations and practical exercises is one way in which the teacher training programmes (Table 6) for the use of ICT could be improved (indicated by 10.8% of them). In addition, the organization of cyclic training activities, in phases from simple to complex (16.4%), differentiated based on subjects or level of difficulty (6.5%), supported by adequate teaching materials (7.7%) is considered by teachers an initiative which would support more efficient training, with real benefits for the improvement of pedagogical practices in the use of ICT.

Continuing to analyse the usefulness of training courses, one significant difference can be seen between teachers who attended a specialised training programme and teachers who didn’t attend such a programme, more teachers from the first category saying that their use of new technologies in the classroom had a positive impact on their students – both on highly-achieving students (83.3% compared to 64.5%) and on low achievers (65.3% compared to 48.2%).

Impact:

Target group

Has the teacher attended an ICT

course? positive negative none

Don’t know

No answer

YES 83.3% 0.4% 3.4% 10.2% 2.6% On highly-achieving students NO 64.5% 1.2% 5.3% 21.5% 7.5%

YES 65.3% 3.9% 14.4% 12.8% 3.6% On low-achieving

students NO 48.2% 5.2% 13.7% 23.3% 9.7%

Table 6. Teachers’ opinions on the impact ICT has on school achievement, differentiated across student categories

There is also relevant that the no-answer rate

and the percentage of those who cannot estimate such an impact are lower among teachers who attended ICT courses.

A different study, measuring the impact of a very recently initiated teacher training programme, reveals the extent to which innovation penetrate the education practice. Intel Teach course (Essentials, ver. 10, face-to-face) started to be delivered in early 2008 in Romania and is aiming to train more than 15,000 teachers in a couple of years. More than 3,000 beneficiaries already graduating the programme were asked about the changes in the teaching and learning as a result of the course.

Being asked if they have used technology in new ways with their students (Fig. 3) since they

No

11%

Yes

82%

NA

7%

Figure 3. ICT courses improve the way teachers use technologies in

the classroom


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participated in the Intel Teach training, 82% of the teachers said that they did innovate their didactic activities.

Furthermore, participant teachers (Fig. 4) used the ICT firstly with the goal to allow students create multimedia products (22%), then to encourage cooperative skills and attitudes (13.7%) and to improve students’ computer skills (12.2%).

4,5%

3,4%

22,2%

7,1%

4,7%

3,8%12,2%

13,7%

5,1%

23,3%

4,5% Students learn curriculum content

Students work on basic skills (such as math and reading)

Students express their ideas/opinions by creating multimedia products

Students conduct research

Students gain preparation to succeed in the workforce

Students present information to an audience

Students improve their computer skills

Students learn to work in groups

Students learn to work independently

None of the above

NA

Figure 4. Goal of the computer-assisted lessons held after undertaking ICT course

The roles of the teacher are extending and continuously re-defined, ICT being one of

the influencing factors (Fig. 5): – ICT contributes to teachers’ professional development through the addition of

new competencies, useful for the activity with students. – ICT stimulates the communication and collaborative activities within the

teachers’ community. – ICT helps teachers in accomplishing administrative tasks they have at school.

0%

20%

40%

60%

80%

100%

ICT contibutes to my professional

development through the adition of

new competencies, useful for the

activity with my classes.

ICT stimulates the communication

and collaborative activities within

the teachers’ community.

ICT helps me in accomplishing

administrative tasks I have at school.

It would have been useful to have

such courses within pre-service

teacher training programme.

Strongly Agree Agree No Opinion Disagree Strongly Disagree NA

Figure 5. Teachers’ view upon contribution of ICT to their professional development

More than 2/3 of the teachers agree with these statements. However, it is obvious that technologies is more and more becoming useful and effective instruments for educating


young generations, and it is a gain that most of the teachers are becoming aware of this fact.

2.4 Excellence Awards for SEI project The European IT Excellence 2008 awards promoted by the prestigious publication – IT Europa, rewards annually the most efficient software solutions designed for commercial and governmental organizations. The quality of the implementation as well as the impact of the SEI project (The IT-based Educational System) were the main reasons for which SIVECO Romania managed be successful in the European IT Excellence Awards 2008 Gala, receiving a new and prestigious European recognition. “The eLearning solution provided by SIVECO Romania for the country’s Ministry of Education Research and Youth is an excellent example of how to deploy a multimedia based content management system tailored for a dynamic educational environment” [John Chapman, awards organizer and Editorial Director of IT Europa]. SIVECO Romania and SANAKO launched the Virtual Lab for science experiments. BETT 2009, the largest educational technology exhibition, took place between the 14th and the 17th of January in London. 650 companies presented innovative solutions for the 21st century education, and the organizers estimated that more than 30,000 visitors from all around the world visited Olympia Hall (Fig. 2). As every year, at BETT are hosted revolutionary education products launches. The new products encourage the use of modern technologies for developing the education systems to better face the 21st century challenges (Fig. 6). SIVECO Romania and SANAKO Corporation launched SANAKO Study Science Lab.

Figure 6. The Virtual Lab for science experiments – BETT 2009, London – Olympia Hall 3 Experiences of Universities Regarding the higher education system, the level of implementation of the new learning technologies as well as of up-to-date ICT infrastructure is quite high, mainly due to the involvement of Romanian higher education institutions within European and international projects in the field of technology enhanced learning, institutional development and other related fields. Beside the know-how transfer, the higher education institutions benefit of


35

higher funding resources through these programmes that increased substantially the funds received from the Romanian Government through different national programmes. Consequently, most of the higher education institutions have set-up a Distance Education department and some of them Technology Enhanced Education units that deal with the implementation of the new teaching methodologies within the traditional education activities. CREDIS (Centre for Resources, Documentation, Information and Services for Open Distance Learning)

The Open Distance Learning Department of the University of Bucharest was established in 1994. It offers various distance courses, either initial, continuous or post higher education. By the Governmental Decision 944 /29 Aug. 2002 the University of Bucharest has 15 authorized specializations to function by distance education. The distance education programs have comparing to the regular study program the same curriculum, the same specialization, equivalent diplomas, all the rights of the graduates assured by law. The distance study program offered by CREDIS provides specific resources, individual learning tutoring, bi-directional communication and self-assessment facilities. The new ICT used are: CD-ROM, e-books, audio-video tapes, websites, and virtual laboratory. There is used ongoing evaluation as well as an final examination. The elearning platform used can be found at http://portal.credis.ro SNSPA (National School for Political and Administrative Studies)

As an example the Department of Political Sciences from SNSPA have also on distance education program for post high education level. The admission procedure takes into account the bachelor diploma marks as well as the results of an short interview according to a fix number of places. It also provides tutorial facilities (speciality guiding and coordination of the student), run by university teachers and researchers. The curriculum is the same as for the regular study program and ends with exams accounting a certain number of credits.

The program is flexible with regard to the dates of the exams, recognition of the diplomas and opportunity to enter in the regular study program.

Any student may take the diploma exam provided he accomplished the required credits from the analytical curriculum aside the students from the regular study program. Romanian-European eUniversity Politechnica University of Bucharest has different projects in the field of elearning. One of the biggest impacts is the Socrates /Minerva project “Romanian-European eUniversity” accessible at the www.reu.pub.ro/re2u. Its aim is to become a major provider of services to universities as well as to lifelong learning communities based on the development of state-of-the-art innovative teaching and learning methodologies and emerging ICTs.

The main challenges for the Romanian-European eUniversity in becoming alive are: – to promote a critical and responsible use of ICT aimed at supporting the

innovation processes within the higher education system; – to help the Romanian Higher education system to integrate itself in the European

Higher Education Area;


– opens the universities towards the outside world by promoting the collaboration between the university and other actors in the economy and society;

– addresses the issues of access to higher education and lifelong learning by disadvantaged target groups.

– improved quality; – addresses the issues of organizational and economic sustainability.

ASE - Academy for Economic Studies ASE is one of the first universities from Romania establishing a distance education department. Yet it was mainly about the correspondence education than using modern information and communication technologies. Babes Bolyai University Babes Bolyai University is also offering some academic course for graduates and graduate education online. Academia Online Academia Online is a private initiative in the continuous education area, providing online courses either for free or chargeable. Since 2003, Academia Online stands for the Romanian model of quality elearning services, being the winner of Education Projects section of 2004 IT&C Awards of the Government of Romania. The award, along with the 35.000 students enrolled in online continuous courses, were for several years the Romanian barometer of interest in elearning, in the area of continuous/ adult learning. The success of Academia Online project is considered to be the result of the close co-operation between programmers, designers and researchers in pedagogy, as the public-private partnership (a private company and the Institute for Education Sciences) was exercised since the design stage. 4 Complementing and Supporting National Programs Romania is part of global and European education initiatives which brings closer innovation, creativity, competence and commitment, in an effort to raise the quality and the equity of the education system and to complement the governmental steps towards developing an authentic knowledge society.

In particular, two programs have a visible impact on the education practice, contributing to the improvement of the classroom teaching, learning and assessment on the new co-ordinates set up by the 21st Century: development of new competences for future professionals, introduction of computer-assisted education, and increased importance of non-formal learning [7,8].

One of them is the eTwinning project [1], an European initiative aimed to link schools in order to develop collaborative projects involving students, and the other one is Intel Teach program [2], aiming to prepare teachers to better use pedagogy and ICT to create adequate learning situations. The two demarches complete each-other and overlap to a certain extent, one creating the premises for hands-on activities with pupils using the ICT and especially the Internet for collaborative activities, being based on the project-


37

based learning method, and the other setting-up the theoretical frame and the pedagogical tools needed by teachers to educate in the 21st Century. The first one is a community of schools and teachers, the second one prepare teachers to use new ICT tools to co-operate and to develop collaborative projects with their students. Furthermore, both initiatives are putting stress on the learner-centred approach and on the transversal competences as a result of learning: communication and social skills, using new technologies, critical thinking, collaboration, creativity. eTwinning eTwinning has an innovation and creativity dimension, addressing an area of the formal and non-formal education at the very heart of the on-going reform, allowing experimentation of new ways of teaching and new ways of performing traditional tasks. Being part of Life-long Learning Programme, accompanying Comenius action, the main aim of the eTwinning program is to facilitate communication and cooperation between schools in EU countries, involving students in new learning activities: creation of various colaborative educational projects with the use of ICT. So far, around 4000 Romanian teachers, from both urban and rual areas, initiated and participated in eTwinning projects together with colleagues from around Europe [1].

The eTwinning projects promote the use of ICT for development, allowing schools to incorporate innovative practices with impact at students and teachers levels, but also at institutional level. Participation to eTwinning allows pupils to learn using the new technologies, to communicate with their peers from other countries, to aknowledge other cultures’ elements, and to improve their competences of communication in foreign languages. As indicated by their teachers, the students’ enjoyment and motivation to accomplish learning tasks is significantly improving when they are involved in such collaborative projects. The teaching methods are also diversifying, becoming more efficient and motivating for learners, as a result of experience exchanges between teachers within eTwinning partnerships and professional development activities. Not least, the online twinning of schools allows the transfer of information and good practices at institutional level, having also, in some cases, an impact at community level. As stressed by the Romanian Minister of Education (March 2008), eTwinning initiative is a way to capitalise upon the investment in ICT equipments for schools – the Romanian IT-based Education System program – providing teachers proper pedagogical instruments to develop significant learning situations for their students. Intel Teach The support offered by Intel programs in Romania complements the demarches of implementing ICT in education, creating the premises for adequate education reform. The areas of support shows the concern and the added value provided by Intel to Romanian education system in the last years: development of education policies towards implementing education solutions for XXI century, teacher training programmes, access of teachers and students to reliable IT equipments, access to Internet and knowledge, support for education process through offering pedagogical materials for teachers, supporting Science education through participation to the International Science and Engineering Fair (the world's largest pre-college science competition, with more than 4


million USD in awards), establishing a common arena for eLearning stakeholders: education policy makers, researchers, teachers, education software developers, opinion leaders [2].

Intel Teach programme was accredited by the Ministry of Education, Research and Innovation in 2007. Implemented by SIVECO Romania and with the support of the County Teachers’ Houses, the Teach Essentials course is run all over the country and the Romanian teachers are part of a global initiative which trained over 6 million teachers around the world. This coverage and impact have led Intel Teach to be called the most successful professional development program of its kind [12].

Within this initiative, along with the continuous teacher training activities, Intel was supporting the localisation of two significant packages of support-materials for teachers: Designing Effective Projects and Assessing Projects. Romanian teachers have access to pedagogical instruments, education projects templates and examples, in an extended range of curricular domains and levels. 5 Conclusion In Romania, the emergence of a knowledge-based economy and the need to assure conditions of social inclusion to all for the 21st Century have brought into light the necessity to enhance the continuous development of the human capital according to a lifelong learning perspective. In these regards, innovative education strategies aiming to integrate ICT are effective and viable when supported by several stakeholders: companies, European institutions, NGOs, schools, teachers, education managers, parents and students themselves.

REFERENCES

*** (2007) Reflections on eTwinning: Cultural Understanding and Integration. Brussels: European Schoolnet - eTwinning CSS.

*** Intel Education Knowledge Base – Available Online: www.intel.com/education *** UE European Commission (2004) Implementation of “Education and Training 2010” work programme,

Key Competences for LifelongLearning, European Commission, Available Online: http://ec.europa.eu/education/policies/2010/doc/basicframe.pdf.

*** CNIV and ICVL Projects, www.cniv.ro (romanian project), www.icvl.eu (international project) Făt, Silvia & Adrian Labar (2009) Eficienta utilizarii noilor tehnologii in educatie. EduTIC 2009 (Efficiency

of ICT Use in Education. EduTIC 2009). Bucharest: Centre for Innovation in Education. Hamilton, Peter & Eileen O’Duffy (2009) Digital education usage models for the classroom of the future. In:

Proceedings of the 4th International Conference on Virtual Learning. Iassy, Romania: Bucharest, University of Bucharest Publishing House, Available Online: www.icvl.eu/2009/ .

Jugureanu, Radu (2005) Proiectare pedagogica a soft-ului educational. Taxonomia lui Bloom si Bloom-Anderson (Pedagogical Design of Educational Software. Bloom Taxonomy and Bloom-Anderson). In: e-Learning Technologies and Virtual Reality. Buc.: Bucharest, University of Bucharest Publishing House.

Jugureanu, Radu et alii (2006) Componente didactice (Didactic Components). In: Virtual learning. Virtual Reality, Software & Management educaŃional. Bucharest, University of Bucharest Publishing House, Available Online: www.cniv.ro/2006 .

Jugureanu, Radu (2008) Vision 2020 – How Pupils See the Future of Education. The 6th edition of the National Competition for Educational Software Cupa SIVECO 2008-Vision 2020, Available Online: http://portal.edu.ro


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Noveanu, E. & Potolea, D. (coord.) (2008) IT-Based Education System. SEI Programme in Romania. Bucharest: University of Bucharest.

Noveanu, E. & Potolea, D. (coord.) An evaluation research on the achievements of the Romanian SEI Programme was conducted by Dr. Eugen Noveanu and Dr. Dan Potolea, from the University of Bucharest, Faculty of Psychology and Education Sciences. The report is available online: www.elearning.ro

Osburg, Thomas and Olimpius Istrate (2008) Intel Education initiative. Focus: Roamania. In: Proceedings of the 3rd International Conference on Virtual Learning. Constatza, Romania: Bucharest, University of Bucharest Publishing House, Available Online: www.icvl.eu/2008/.

Toma, Steliana et alii (2009) Teaching in the Knowledge Society: The Impact of the Intel Teach Program in Romania. Bucharest: Agata Publishing House.

UNESCO (2008) ICT Competency Standards for Teachers. Available online: http://cst.unesco-ci.org/sites/projects/cst/

Velea, Luciana-Simona (2009) Proiectul eTwinning în Romania (eTwinning Project in Romania). In: Elearning.Romania. Bucharest: TEHNE- Centre for Innovation in Education. Available online: http://www.elearning.ro.

Vlada, Marin (2009) Utilizarea Tehnologiilor eLearning: cele mai importante 10 initiative si proiecte din Romania (Using eLearning Technologies: the Most Important 10 Initiatives and Projects in Romania). In: Elearning.Romania. Bucharest: TEHNE- Centre for Innovation in Education. Available online: http://www.elearning.ro.

Vlada, Marin, Adascalitei, A. and Jugureanu, R. (2009) Trends of eLearning: Learning - Knowledge - Development. In eLSE 2009 - The 5th International Scientific Conference ”eLearning and Software for Education”, BUCHAREST, April 09-10, 2009, "Carol I" National Defense University, Romania, Available Online: http://adl.unap.ro/else2009/index.php

Scientific Knowledge and Solving Problems Modelling, Representation and Processing

Marin Vlada

University of Bucharest, Department of Mathematics and Computer Science,

14 Academiei Street, RO-010014, Romania E-Mail: [email protected]

Abstract This article presents several important topics that show the importance of knowledge and solving problems in the development of scientific knowledge. At present the scientific and technical development, solving problems in a different field (math, science, physics, chemistry etc.) is a creative activity, by building a reasoning, generation, describing the following activities: demonstration process (deduction and reasoning) to show the existence of a solution or several solutions and / or to determine the exact effective solutions; computational process (algorithm) to codify a demonstration, a method or technique to solve in order to determine (possibly approximate) exact solutions. In the problem-solving processes require demonstrative thinking, a algorithms thinking. From the methodological point of view, we need to recast usual problems explicitly and properly resolve their mathematical. If the computer should use to develop algorithmic methods. In both cases you must know the limits of thinking demonstration. You should also know the limits of performance computing and algorithmic thinking. Every science is based on the theories, theorems (laws) and hypotheses that have been identified, studied and demonstrated by the strengthening, development and evolution in time of sciences. The article presents the problem of Gauss and Green theorem used to calculate the area of any polygon. Finally, we propose the following meta-model: problem solution = modelling + processing; modelling = knowledge + representation; processing = language + interpretation.

Keywords: Mathematical Models, Algorithmically Method, Computer Graphics, Gauss’s Problem, Green's Theorem

1 Introduction and Literature Today, Computer Science (Informatics) is among exact sciences along with mathematics, physics and chemistry. If in 70 years at the university level, there were several disciplines own science, today there are complex areas of computer science: Programming and Software Engineering, Computer Networks and Computing, Databases and information systems, programming and Web development, computer graphics and reality virtual, computational geometry, modelling and simulation, parallel and distributed Computing, artificial intelligence and expert systems, knowledge engineering (Vlada, 2005; Vlada and ługui, 2006). A major requirement of today’s knowledge society makes the educational systems of countries to be in a high dynamic. Change theories, disciplines, specializations, skills, and even in the sciences are constantly changing.


41

Today, one can say with certainty that the Mathematics and Computer Science are scientists who have contributed to a rapidly developing Information and Communication Technologies (ICT), in addition to other sciences and areas: Automation, Electronics, Electrical Engineering, Telecommunications etc. Information technology is the technology required for processing, in particular electronic computers use to convert, process and transmit information. Therefore, the computer is only device that theoretical concepts are implemented. Professor Edsger Dijkstra said: "In Informatics you have to do with the computer, as you with the telescope in astronomy." Informatics expression is a word that comes from the word alignment Information and Mathematics.

Computer Science history proceeding the time of occurrence digital computer. Before 1920, the term "computer" referred to a person who performed calculations (an official). The first researchers in what was to be called Computer Science, such as Kurt Gödel, Alonzo Church and Alan Turing, were interested in the computational problem. Computer Science (Informatics) is characterized by the most spectacular evolutions of the impact on human activity. Computer (Computer System) includes technologies of which man has never dreamt. Although at the beginning the use of computer was regarded with reservation, nowadays most of the people are convinced by the performance and utility of computer in all activities.

At present the scientific and technical development, solving problems in a different field (math, science, physics, chemistry etc.) is a creative activity, by building a reasoning, generation, describing the following activities: demonstration process (deduction and reasoning) and computational process (algorithm). Today, the specialists working in a certain field face different complex problems, many of these requiring the use of computer and software products.

2 Mathematics and Computer Science Mathematics is the oldest of the exact sciences and Informatics has emerged and developed as a science in the second half of the 20th century (after 1960, when already emerged modern computer - designed for Hungarian mathematician John von Neumann (1903-1957) and develop theories, methods and techniques of data processing / information), being the newest. And today's report is recognized on John von Neumann's EDVAC Report 1945 (von Neumann, 1945), EDVAC (Electronic Discrete Variable Automatic Computer) is one of the first electronic computers that utilized the binary system that first began performing basic tasks in 1951 (von Neumann, access 2009).

World in those years for pioneering the field of IT and computer use, and Romania has made an important contribution by the school of logic and data created by Romanian mathematician Grigore C. Moisil (1906-1973). Professor Gr. C. Moisil had outstanding contributions to the development of Informatics in Romania and in the formation of the first generation of informaticians. He had a contribution to the introduction and use of the first electronic computing machine in our country. Particularly valuable are the contributions made by Grigore C. Moisil the algebraic theory of automatic mechanisms. He developed new methods of analysis and synthesis of finite automatic and structural theory of them. He entered algebras called him lukasiewicziene trivalent and polyvalent


(known today-Moisil Lukasiewicz algebras) and it has used in the study of logic and circuit switching (Vlada, 2005; Vlada and ługui, 2006). For these contributions, post-mortem in 1996, Gr C. Moisil (O’Connor and Robertson, 2009) received the Computer Pioneer Award of IEEE (received award for his work "For polyvalent logic switching circuits."). The example provided by Moisil was followed by generations of mathematicians and informaticians contributions that have internationally recognized, both in scientific research and the use of computers for the overall development of the Romanian society and international.

2.1 Mathematics and scientific method The word "mathematics" comes from the Greek µάθηµα (máthema) which means "science, knowledge or learning"; µαθηµατικός (mathematikós) means "one who likes learning”. The terms "model", "hypothesis", "theory" and "theorem" has other meanings in science than in the usual language. Scientists use the term "model" to express the description of something, specifically something that can be used to make predictions that can be tested by experiment or observation. In the modern sense, mathematics is the investigation of structures defined in an abstract axiomatic using formal logic. Investigate the structures of mathematics often have their roots in natural sciences, often in physics. Mathematics and investigates and defines the structure and its own theories, in particular to synthesize and unify multiple fields in mathematical theory, single, a method that facilitates generally generic methods of calculation. Mathematics is generally defined as the science which studies the patterns of structure, operations in time and space.

The most important function of mathematics in science is the role that is the expression of scientific models. Processes of observation and grouping the results of experiments, creating assumptions and predictions often require mathematical models. Branches of mathematics most often used in science include the calculation and statistics, although almost every branch of mathematics has applications, even areas "pure" such as number theory and topology. Mathematical models are based on scientific methods. Mathematical models can take many forms, including but not limited to dynamical systems, statistical models, differential equations, graphs, theoretic models etc.

These and other types of models can overlap, with a given model involving a variety of abstract structures. Mathematical models are used not only in the natural sciences and engineering disciplines (such as physics, chemistry, biology, earth science, meteorology, and engineering) but also in the social sciences (such as economics, psychology, sociology and political science); physicists, engineers, computer scientists, and economists use mathematical models most extensively.

Grigore C. Moisil say "All what is correct thinking is either mathematics or feasible to be transposed in a mathematical model". “Sciences are models and virtual representations of knowledge” (Vlada, 2008a).

2.2 Computer Science and solving problems Competence and experience in solving problems using computer can be permanent only if it is the dependency System Computer-Algorithmic-Programming, and if efforts are undertaken to acquire new knowledge and knowledge of all relevant aspects of the physical and virtual model. The entire research and development of software in the field


43

of Information Technology is determined by the invention, design, development, testing, and implementation of useful algorithms and performance.

Wide variety of algorithms and their great applicability in all fields, makes the subject is always present and in a continuous change and improvement. In essence, solving a problem is expressed by the encoding of universe problem and the reasoning for demonstration (Vlada, 2005; Vlada and ługui, 2006). Stages of solving a problem with the computer: the problem, mathematical model, algorithm, program, computer, results and verification solutions [Fig. 1].

Fig. 1 The evolution modelling in solving problems

The performance of IT developer is determined by experience and expertise gained in conducting the two stages (ANALYSIS, PROGRAMMING):

• object thinking stage (ANALYSIS / Projection) - method of analysis and description of the problem by defining the correct objects, the types of objects, relationships between objects and specific operators (UAP development, stage design and analysis-design);

• algorithmic thinking stage (PROGRAMMING / execution) - the choice and proper application methods of solving the exact specification of the operators of processing objects, the correct representation of algorithmic strategies, codified representation of objects and processing according to a programming language (and algorithm development program; stage programming - coding implementation and enforcement).

„Natural environments are ruled by languages. Computer Science use artificial languages. Languages exist therefore, not for communication purposes alone, but particularly for knowledge.” (Vlada, 2005)

Practice solving problems using computer (programming languages or specialized software) resulted in time, various approaches based PC performance. It also depends on


the methods and techniques on implementing advanced solution. Addressing a theoretical problem solving does not guarantee its practice with the computer, and vice versa. We illustrate this in the next section.

Language of knowledge (Vlada and Sarah Nica, 2009): • Natural languages (the languages of the peoples) - "entity"=word; lexical

constructions describe states, images, actions, etc. • Languages of sciences (used in the fields of science: mathematics, physics,

chemistry, economics, etc.) - "entity"= knowledge/meet; study of objects and relationships between objects in the fields of mathematics, physics, chemistry, computer science, biology, economics, etc.

• Artificial languages (used computer) consisting of Procedural Programming languages - "entity" =memory location Functional Programming Languages - "entity" = item list Logic Programming Languages - "entity "= object, clause Object Oriented Programming - "entity" = object Web Programming Languages - "entity" = web/multimedia elements Languages for Databases - "entity" = registration Languages for Computer graphics - "entity" = graphics object Languages for Modeling-Simulation - "entity "= event Languages for Operating Systems- "entity" = process/ task Languages for Artificial Intelligence - "entity" = object/ knowledge

Definition. A language of knowledge is virtual system/logical L = ( V, Sin, Sem, O, C, T, Tc),

where V = vocabulary / alphabet, Sin = syntax (rules), Sem = semantics (rules), O = objects,

C = concepts / terms, T = theories / methods / techniques to solve, Tc = treasury of knowledge (knowledge base). (Vlada, 2005)

Using computers in language led to the conclusion that they are effectively used for processing, not only for communication. Develop programs to solve problems with a computer led to the development and evolution of all sciences. In most countries, research programs, development and innovation are the number of increasingly large and the results are not expected leave. Meanwhile, continuous improvement, knowledge and use of new knowledge in the field of activity should be the major goal of each specialist. They demonstrate that the necessary knowledge and experience to achieve consistent results on various topics of research and development. Also bring important arguments concerning the modelling, representation and processing, all contributing to the performance of technologies.

3 Gauss’s problem solved by a computer Karl Friedrich GAUSS (177-1855) is world’s most famous mathematicians. The German mathematician Karl Friedrich Gauss made outstanding contributions to both pure (studied for its own sake) and applied (studied in order to solve specific problems) mathematics.


45

Gauss’s Problem. A vessel containing 2000 liters of liquid with a concentration 80% alcohol. Every day removed from 15-liter vessel and replaced with another 12 liters of a liquid whose alcohol concentration is only 40%. After how many days the liquid in the vessel reaches 50% ?

Apparently, as set out is a simple problem. This is interesting in terms of resolving

them, as was mentioned at the time of Gauss. Solving the problem is not obvious, as will be seen in what follows. From mathematical point of view, solving requires notions and concepts of higher mathematics in functional equations (equations with finite differences of order scratchy). The problem was solved by W. LOREY (1935) and A. WALTHER (1936) by two scientific articles. From the numerical problem requires specific knowledge of numerical methods to solving equations with finite differences. W. LOREY used a machine to solve the numerical calculation of the difference equations (the solution is obtained after a considerable number of iterations). To make comparison between algorithmic solutions obtained computer and analytical solution (mathematical method), we present brief time resolve A. Walther.

Solving mathematics (Mathematical method) We will do the following:

a - the quantity of liquid (in liters) contained initially in the vessel; b - the quantity of liquid that is removed daily from the vessel; c - the amount of liquid that is added daily vessel; y0 - the amount of alcohol per liter (the concentration of alcohol) a liquid vessel at

the time of the initially ; yp - the amount of alcohol per liter of liquid that is added; yf - the amount of alcohol per liter of liquid in the vessel, at the end; x - number of days (operations fluid replacement); y (x) - the amount of alcohol per liter of fluid from vessel operations after x

replacement fluid. Obtain the following functional equation:

( a - bx + cx ) y(x) - ( a - bx + c(x-1) ) y(x-1) = c yp General solution is

y(x) = yp + (y0 - yp) ))/()(())/(())/(())/()((

xcbcacbaxcbacbba

−−−Γ−Γ−−Γ−−Γ

,

where Γ(x) is Euler’s function:

∫∞

−−=Γ0

1)( dttex xt .

In the case a = 2000, b = 15, c = 12, y0 = 0.8, yp = 0.4, y (x) is a polynomial of degree IV:

)1997

31)(

1994

31)(

1991

31)(

1988

31(4.04.0)(

xxxxxy −−−−+=


By approximation is concluded that the y (194) = 0.5004515, y (195) = 0.4995996, so after x = 195 days to get to the concentration yf =0.5.

Solving using computer (Algorithmics method ) In addition we use the following variables:

z - the quantity of alcohol in the vessel at a time; t - the quantity of liquid in the vessel at a time; y0 - the concentration of alcohol in the vessel at a time.

algorithm Gauss;

int x;

float a,b,c,y0,yp,yf,z,t;

begin // main

read a,b,c ; //liquid quantities

read y0,yp,yf; //concentrations

// initializations

x←1; z←(a-b)*y0+c*yp; t←a-b+c

while yf < z/t do

begin

x←x+1; y0← z/t; //concentration

z←(t-b)*y0+c*yp; t←t-b+c;

end

write x; // solution

end

Execution by the computer program we tested for the following:

a y0-final x (days)

2000 0.5004515 195 5000 0.5001438 488

10000 0.5000983 976 100000 0.5000064 9763 Table 1. Solutions of program: some cases

4 Computer Science and Computational Geometry

"A picture is worth ten thousand as the words" (Chinese proverb)

“The book of nature is written in the characters of geometry” (Galileo)

The term Computer Graphics has several meanings: • the digital images so produced; • the representation and manipulation of pictorial data by a computer;


47

• the various technologies used to create and manipulate such pictorial data; • the sub-field of computer science, which studies methods for digitally synthesizing

and manipulating visual content. The field of computer graphics developed with the emergence of computer graphics

hardware. In 1953 has invented the graphical display (Graphic Display) and so switched to a new stage in the development and spread of the computer. Possibility of modeling the spatial output (OUTPUT device) could not be achieved by using only bits of memory. Early projects like the Whirlwind (The Whirlwind computer was developed at the Massachusetts Institute of Technology; the project's budget was $1 million a year) introduced the CRT (cathode ray tube) as a viable display and interaction interface and introduced the light pen as an input device. A light pen could be used to draw sketches on the computer using Ivan Sutherland's revolutionary (1963, PhD thesis) Sketchpad software (Sketchpad is considered to be the ancestor of modern Computer-Aided Drafting (CAD) programs).

At first graphical representations made on paper using characters (letters and numbers) for images. A plotter is a vector graphics-printing device to print graphical plots that connects to a computer. Graphical representations using character (numeric or alphanumeric) was not a solution to achieve a faithful representation of real objects. The period 1960-1980 after it was invented hardware support; it took research and experiments, models, algorithms and software to use the lighting of a "pixel" (indivisible unit graphics provide a graphical display). Computer displays are made up from small dots called pixels. The word "pixel" was first published in 1965 by Frederic C. Billingsley. Each pixel intensity and colour offering, and their crowd formed a structure of graphic representation (resolution). The intensity of each pixel is variable. This structure is in computer science, which is the calculation in mathematical analysis (Newton, Riemann, Darboux, Leibniz, etc.). System division (discrete process) from the calculation is entirely analogous to the resolution (pixel matrix) provided a graphic display (Vlada 2008; Vlada, Posea, Nistor, Constantinescu, 1992). From that moment was born on Computer Graphics (2D and 3D): drawing a straight segment (Bresenham algorithm), and drawing the circle ellipse, drawing curves and approximation, algorithms for clipping (algorithm Cohen - Sutherland, Hodgman algorithm-Sutherland, Weiler-Atherton algorithm) techniques for 2D and 3D, models of illumination and reflection, raster graphics, vector graphics, texture techniques. Thus were laid the foundations for integrated software solutions and hardware for design, analysis and computer-aided manufacturing (CAD / CAM / CAE). By involving computer use in solving problems in many areas have been defined and solved various requirements and projects in the past were unthinkable.

Road open Computer Graphics was continued for Computational Geometry: polygonal domains, spatial orientation problems and algorithms, triangulation, covering convex 2D and 3D (Quick Hull algorithm, Graham algorithm, the algorithm Jarfis involution, Chan's algorithm), monotonous polygons, Voronoi Diagrams (Fortune algorithm), Delaunay triangulation algorithm, Graph visibility, Dijkstra's algorithm, problems and intersection algorithms, dynamic movement of objects in space, causing the points belonging to a domain (O'Rourke, 1998; Goodman and O'Rourke, 2004).


NOTE: The Jordan Curve Theorem for Polygons. Any simple closed curve C divides the points of the plane not on C into two distinct domains (with no points in common) of which C is the common boundary. We shall take the case where C is a closed polygon P. The proof given by Camille Jordan (1838 -1922) he was quite complicated and it turned out to be invalid (Hales, 2007). A demonstration of the theorem is given in “Computational Geometry Student Projects - 1997” (Toussaint, 1997; CGAL , 2009; Davis, 2006; Goodman and O'Rourke, 2004).

4.1 Green's Theorem and area of a polygon "Imagination is more important than knowledge" Albert Einstein "The beginning of wisdom is the definition of terms." Socrates

George Green (1793-1841) English mathematician and physicist is known for its

contributions through mathematical analysis with applications in the theory of electricity and magnetism. (“An Essay on the Application of Mathematical Analysis to the Theories of Electricity and Magnetism”, George Green, 1828).

Green's theorem gives the relationship between a line integral around a simple closed

curve C and a double integral over the plane region D ⊆ R2 bounded by C. In a cartesian system of axes XOY is considered domain D ⊆ R2 which has the border curve C (D be the region bounded by C) consists of the meeting closed curves C1, C2, C3, C4 (where C2 and C4 are vertical lines).

The curve C1 is given by parametric equations: x = x, y = g1(x), a ≤ x ≤ b. The curve C3 is given by parametric equations: x = x, y = g2(x), a ≤ x ≤ b. It is considered L and M are functions (class C1) of (x, y) defined on an open region

containing D and have continuous partial derivatives. Define )()(,|),( 21 xgyxgbxayxD ≤≤≤≤= where g1(x) and g2(x) are continuous functions on [a,b].

Green's formula establishes the relationship between curves integral and double integral.

Green's formula is given by

In physics, Green's theorem is mostly used to solve two-dimensional flow integrals,

stating that the sum of fluid outflows at any point inside a volume is equal to the total outflow summed about an enclosing area.

Green's theorem for path of class C1 Let a plane region D⊆ R2 bounded by C, where C = FrD =Imγ , γ is path of class C1,

Rba 2],[: →γ , ))(),(()( tytxt =γ , a ≤ t ≤ b.


49

Theorem 1. If a plane region D ⊆ R2 bounded by γ , where γ is path of class C1 and FrD =

Imγ ,

∫ ∫∫≡−=γ

DdxdyydxxdyDm )(

2

1)( ,

where m(D) is Jordan measure (area of D).

Proof. Because the assumptions are valid Green theorem, mainly considering L(x,y)= - y/2, M(x,y)= x/2 and apply Green’s theorem.

Green's theorem for polygons Theorem 2.

If a plane region D ⊆ R2 bounded by γ , where γ is path of class C1 upon portions and FrD = Imγ , then

⇒∪∪∪= γγγγ n...21

∑∫=

−=n

i

ydxxdyDm1

1

0

)(2

1)( ,

where γ is path of class C1 upon portions, and m(D) is Jordan measure (area of D). Proof. Let R2]1,0[: →γ , 0 ≤ t ≤ 1 and

=

→

))(),(()(

]1,0[: 2

tytxt

R

i

i

γ

γ, 1 ≤ i ≤ n

Using ⇒∪∪∪= γγγγ n...21

∫ ∑∫=

−=−=γ γ

n

ii

ydxxdyydxxdyDm0

)(2

1)(

2

1)( .

Corolary. Let the polygon line P=P1…Pn, Pi(xi, yi), 1 ≤ i ≤ n, then area of polygon P is

∑= ++

=n

i ii

ii

yx

yxS

1 112

1,

where xn+1=x1, yn+1=y1. Proof. To see Theorem 2, consider plane region D ⊆ R2 bounded by P = FrD . Using the bijective application between the real segments [0,1] and [a,b], given by

φ(t) = a + t(b-a). The polygon line is modeled using the reunion of the γi paths parametrically represented as follows:

2]1,0[: Ri →γ , ))(),(()( tytxti =γ , 1 ≤ i ≤ n,


whereas x(t) = xi + t (xi+1 - xi), y(t) = yi + t (yi+1 - yi), 1 ≤ i ≤ n-1

noting that for the last path, γn parametric equations are x(t) = xn + t (x1 – xn), y(t) = yn + t (y1 – yn).

Note. Another formula for the area of any polygon:

)()(2

111

1

yyxxS iii

n

ii −⋅+= ++

=∑ (Davis, 2006; Vlada, 1992)

5 Conclusions Languages exist therefore, not for communication purposes alone, but particularly for knowledge. Develop programs to solve problems with a computer led to the development and evolution of all sciences. Results and performance obtained through the use of computers have boosted the development of all sciences. Today, information and knowledge are represented differently, shaped and processed. Also, troubleshooting took new dimensions through the use of algorithmic methods. Many issues would have remained unsolved if not using the methods and performance offered by computer. The concepts of language and algorithm were reviewed. Were invented artificial languages used by computer. These languages are not only used to communicate information, but also for processing information and knowledge. Today, all benefit from this science invention. Weight consists of representation and interpretation. Therefore, scientists need to think both in natural environments, but also in virtual environments.

According to the above considerations we conclude with the followingremarks: 1) Problem solving is based on models of knowledge representation and processing

paradigms; 2) Processing can be described using some language under a specific interpretation.

Finally, we propose the following meta-model: • PROBLEM SOLUTION = MODELLING + PROCESSING

• MODELLING = KNOWLEDGE + REPRESENTATION

• PROCESSING = LANGUAGE + INTERPRETATION

6 Acknowledgement The author would like to express their gratitude to Prof. Grigore Albeanu for their invaluable input and suggestions in this research.

REFERENCES

CGAL (2009): Computational Geometry Algorithms Library, Open Project, http://www.cgal.org/, access may

2009 Davis, T (2006).: Practical calculation of Polygonal Areas, http://www.geometer.org/ mathcircles/

polyarea.pdf, access 2009.


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Goodman, J.E. and O'Rourke, J. (eds) (2004): Handbook of Discrete and Computational Geometry (2nd Ed.), CRC Press.

Hales, T. C. (2007): Univ. of Pittsburgh, http://mizar.org/trybulec65/4.pdf, access 2009. von Neumann, J. L. (1945): von Neumann Architecture of Computer Systems. John von Neumann's EDVAC

Report 1945, http://www.wps.com/projects/EDVAC/, access 2009. von Neumann, J. L.: Ehistory - John von Neumann, http://ei.cs.vt.edu/%7Ehistory/VonNeumann.html, access

2009. O’Connor, J. and Robertson, E. (2009): The MacTutor History of Mathematics archive, http://www-

history.mcs.st-and.ac.uk/, access 2009. O'Rourke, J. (1998): Computational Geometry in C (2nd Ed.). Cambridge University Press, ISBN 0-521-

64976-5. Toussaint, G. T. (1997): Computational Geometry Student Projects Canada, http://cgm.cs.mcgill.ca/

~godfried/, access 2009. Vlada, M., Posea, A., Nistor, I., Constantinescu, C. (1992): Computer graphics using Pascal and C

languages, vol. I, II, Technical Publishing House, Bucharest Vlada, M. (2005): Role of Language in processing Information and Knowledge. In Proceedings of The

International Scientific Conference – eLearning and Software for Education, eLSE 2005, “Carol I” National Defence University, Bucharest, University Publishing House, pp 165-178.

Vlada, M. and ługui, Al. (2006): Information Society Technologies – The four waves of information technologies. In Proceedings of The 1st International Conference on Virtual Learning, ICVL 2006, Bucharest University Press, pp 69-82.

Vlada, M. (2008): SVG Language (Scalable Vector Graphics) For 2D Graphics in XML and Applications. In Proceedings of The 3rd International Conference on Virtual Learning, ICVL 2008, Bucharest University Press, pp 297-306.

Vlada, M. (2008a): Personal communication, From CNIV 2003 to CNIV 2008: Learning – Knowledge - Development. The 6th National Conference on Virtual Learning, CNIV 2008, “Ovidius” University of Constanta, Romania, http://www.cniv.ro/2008/ , access 2009

Vlada, M. and Sarah Nica, A. (2009): Languages and Knowledge versus Modeling and Processing. ECKM 2009, 3-4 Sept. 2009, University of Padua, Italy, Proceedings of 10th European Conference on Knowledge Management, http://academic-conferences.org/

Towards virtual learning grid developments

Grigore Albeanu

Spiru Haret University 13, Ion Ghica Str., Bucharest, RO-030045, ROMANIA

E-mail: [email protected]

Abstract Virtual learning has opened new vistas in meta-information handling. Large collections of portfolios and e-books, large communities of e-people and processes over widespread virtual campuses impose a new management strategy. The most appropriate solution for a global university is to use a grid architecture based on distributed warehouses in order to use its distributed processing power. This paper describes the state of the art in grid computing methodologies and reviews grid models to support the global university paradigm. Keywords: virtual learning, interoperability, grid computing, global university

1 Introduction Virtual learning becomes an important topic not only for business entities, but also for academic institutions and for researchers. Recently, a great interest in using advanced ICT methodologies like grid computing proved the validity of the globalisation theory related to business, research and education.

According to (Albeanu, 2007), virtual learning “is a subset of technology-based learning using Virtual Reality Technologies or/and Virtual Environments”. Virtual reality applications for education ask for powerful computing resources, mainly for simulation and visualization. A solution for managing costs consists of using the grid paradigm.

Created by UNESCO, the United Nations University, and the Technical University of Catalonia, in 1999, the Global University Network for Innovation - GUNI is composed of the UNESCO Chairs in Higher Education, higher education institutions, research centres and networks related to innovation and the social commitment of higher education”, according to GUNI. This is an idea to think about a global university. Another thought comes from distance learning based on ICT methodologies. Finally, an entrepreneurial characteristic of the global university should be considered due to the current nature of globalisation phenomena in business, research and education.

There are universities which already added the slogan “global university”. Only one search using the global searching machine will identify them. However, in our opinion, a global university represents more when taking into account a global infrastructure, not only based on some internet services offered by one server or a cluster of servers.

The aim of this paper is to describe the state of the art in grid computing methodologies suitable for developing powerful virtual learning applications for global universities.


53

The presentation is organised as follows. The second section is a review on current grid computing methodologies used both for research and e-learning.

A grid computing based model of the infrastructure of the global university is described in the third section. A distributed infrastructure as considered by (Berman et al., 2003) is used to solve the problems of interoperability, scalability, reliability and availability, to mention only some quality attributes of such a solution.

Finally, a set of concluding remarks will be outlined in the fourth section.

2 Grid computing methodologies The grid concept was defined by (Foster & Kesselman, 1998) as the “controlled and coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations”. Considering the references (Ferreira et al, 2003) and (Jacob et al, 2005), “a grid is a collection of machines, sometimes referred to as nodes, resources, members, donors, clients, hosts, engines, and many other such terms”, being seen as a virtual computer, where “individual users (or client applications) gain access to computing resources (processors, storage, data, applications, and so on) as needed with little or no knowledge of where those resources are located or what the underlying technologies, hardware, operating system, and so on are”. Other debates related to definitions, grid architecture requirements, and generations of grid systems can be found in (Berman et al, 2003).

When an organization will develop a large scale application, as virtual learning projects for global universities, the grid characteristics of infrastructure, methodologies and a best understanding of the computing power, type of systems’ coupling and interoperability standards are very important.

According to (Jacob et al, 2005), the benefits of grid computing are: 1) reducing time processing by running the application on an idle machine from the network, or using a set of machines available in the grid for parallel/distributed processing by scalability – a measure of the efficiency of the multiple processors usage on a grid; 2) the unused storage capacity can be aggregated, using the data grid concept (a larger virtual data store), in order to improve the performance of the system; 3) the virtualization of resources (files, specialized devices, software, services, licences, etc.) improves the interoperability among heterogeneous grid users; 4) the virtualization of organizations, the building of virtual communities of users improves the sharing and balancing of resources and asks for special security rules; 5) the automatic computing approach is used by grid systems, that means the “grid management software can automatically resubmit jobs to other machines on the grid when a failure is detected”, in order to increase the service availability, or “multiple copies of important jobs can be run on different machines throughout the grid”, for assuring an increased level of fault tolerance and reliability; 6) the maintenance actions of the machines does not decrease the service availability, and a dynamic resource management of the shared resources will assure the needs of running applications; 7) grid computing makes use of “an evolving set of open standards for Web services and interfaces”.

The data grid capacity is increased dynamically by usage the storage of the multiple machines based on a unified file system like: NFS (Network File System), DFS


(Distributed File System), GPFS (General Parallel File System), AFS (Andrew File System), or the generic GFS (Grid File System) assuring distributed replication, and distributed data request/fulfilment.

Depending on the grid size, the implementation can use the cluster approach (the machines have the same architecture and operating system), the intragrid solution (heterogeneous machines but a networked file system; for single organizations, no partner integration support, a single cluster, with a static set of resources), and the intergrid approach (intragrids are extended with dedicated grid machines and dedicated communications’ connections; providing support for many organizations, multiple partners, and based on many multiple clusters). As already established by scientists, and stated in the IBM Red Book, written by Jacob et al (2005), “the primary characteristics of an intragrid are a single security provider, bandwidth on the private network is high and always available, and there is a single environment within a single network”.

An intermediate grid architecture model is called the extragrid. An extragrid brings together two or more intragrids, and involves more than one security provider. Following (Jacobs et al, 2005), “the primary characteristics of an extragrid are dispersed security, multiple organizations, and remote/Wide Area Network connectivity”.

Any application asking for peer-to-peer computing, serving a collaborative computing community, or based on end-to-end processes will be designed in the framework of an intergrid architecture. This is the case of global universities or networks of universities virtual learning solutions.

A particular machine can be enrolled in the grid by installing the grid software and declaring the machine role (passive or donor). As (Jacob et al, 2005) mentioned, the enrolling requires authentication for user/machine. Logging onto the grid depends on the grid solution adopted (ID, grid login, proxy login); once logged on, the user can sent different queries (grid status, the submitted jobs’ status, etc), and can submit jobs. A possible software solution is GSI-OpenSSH being also used to remotely create a shell on a remote system to run scripts or sent shell commands interactively. The grid application developer will use special functions provided by the grid system software application programming interfaces in order to automate the monitoring and recovery from fail of subjobs (processes, threads).

A special grid user is the administrator with special tasks in managing the grid: grid configuration, software customization, the members’ management, controlling the rights of the users/machines, removing the users/machines, communication with the administrator of the donor machine (about user ID, software, access rights, policy restrictions, etc.), setting permissions for grid users to access resources (usage tracking, billing reports generation), job priority assignment and data grid maintenance (creating backup copies and replicas).

The highest level of security it is assured using a Certificate authority having the following responsibilities: a) to identify the entities requesting certificates; b) certificates management (issuing, removing, archiving); c) names management (by a namespace of unique names for certificate owners); d) the Certificate Authority server protection; e) to manage the signed certificates, and f) to assure the login/logout activities. Currently, the public key encryption system is used.


55

Developing a grid application requests the usage of open solutions like OGSA (Open Grid Service Architecture), OGSI (Open Grid Service Interface), OGSA-DAI (Data Access and Integration), GridFTP, WSRF (Web Services Framework), XML, WSDL, SOAP, and standards related to Web Services Interoperability.

OGSA is the general model for grid computing environments defining all requirements related to resource models, interfaces, expected behaviours, and run-time bindings. The creation of new instances of resources, global naming and references management, lifetime management, registration and discovery operations, clients notification, authorization and concurrency control are some of the key capabilities of OGSA. OGSI can be used to implement OGSA-compliant services, and deals with mechanisms for creating, managing, and exchanging information for Grid services using an extension of the WSDL (Web Service Definition Language), called GWSDL. OGSA-DAI provides the basis for “access and integration of data from separate data sources via the grid”, according to the mentioned reference. Data transfer across the grid network is supported by GridFTP. Parallel transfers and partial file transfers can be realized secure and reliable. The developers can implement high level services on top of GridFTP. Before discussing WSRF it is important to mention that Grid services are implemented using Web-services technology. However a fundamental difference among them there exists: Web services deal with persistent services, while grid services are transient, being created/destroyed dynamically. Other considerations can be found in (Berman et al, 2003).

WSRF, also, can be used to implement OGSA-compliant grid services. The Web Service Resource definitions are described using WSDL (XML style) and presents the properties of the resource (called stateful resources). Any stateful resource “is known to and accessed by one or more Web services”, and can be implemented as a file, a record in a database, or a data structure stored in memory. Its life-cycle is well defined and the data about its state is described using XML.

An OGSA-compliant middleware is Globus Toolkit (Foster, 2005), an open source software useful for building computational grids and grid applications. Binary packages of GT4 are available for Linux environments and Solaris. However, by compiling the source packages or making use of Java-based components, the GT4 can be used on other operating systems. The major components of the version 4 (GT4) address: runtime processing, security, data management, information services and execution management. There available Web service based components (as Java WS Core, C WS Core, Python WS Core, Reliable File Transfer, OGSA-DAI, RLS , WS GRAM, WebMDS, etc.), and non Web service based components (like GridFTP, C-common libraries, etc.). Java WS Core, C WS Core, or Python WS Core, consists of APIs implementing WSRF, and other grid services with Java, C, or Python. The RFT provides a Web service interface useful for transferring, and deletion of files, and is built in top of GridFTP. The RLS (Replica Location Service) provides information about the physical location s of replicated data. MDS (Monitoring and Discovering Services) is responsible with the collection, indexing, archival, distribution of information about the state of resources, services, and configurations. WebMDS is a Web-based interface to WSRF information. WS GRAM provides the remote execution and status management of the jobs.


For computing intensive jobs the Condor software which incorporates many of the emerging Grid-based computing methodologies and protocols is an important solution. Condor-G is fully interoperable with resources managed by GT4. Previous information about Condor was published by Berman et al (2003). Recent information about the last version of Condor is available on the Condor website. A powerful system for automated installation, configuration and management of clusters and farms is Quattor. A positive experience using Quator for Grid-Ireland and Irish e-Research is reported in (Gerdelan, 2008).

In the following, we describe the most valuable characteristics of the grid methodologies to be use in virtual learning solutions.

3 On supporting global university by grid computing Our study considers the usage of grid computing concepts for supporting e-learning and research in the framework of global society. The concept of global university arises in the recent time, mainly based on e-learning. However, a lot of advantages were established, but there are some disadvantages related to communication (communication between students, and between students and teachers/supervisors can not be as close as face-to-face communication), and laboratory-based activity.

Recently, more advance in creating virtual laboratories and virtual e-lessons removed such disadvantages, and the new ICT methodologies with the aid of grid computing advancement create the environment for building a global university having mission related to research and education, all levels. Collaborative learning is possible using CSCW/L-oriented grid architecture (Li et al, 2006), communication with artificial agents (Cerri, 2008; Cerri et al, 2008), by sharing artefacts based on OSCAR – the Open Source Component Artefact Repository (Boldyreff et al, 2002), using the Shared Event Model (Wang et al, 2005), developing semantic grids, as described by (Bachler et al, 2004) and (Page et al, 2005), using portals like Chiron (Bardeen et al, 2006), and other models and tools for grid or non-grid infrastructures.

The Access Grid Toolkit (AGTk) was used to implement a multi-campus live lecture environment, as described by (Arns et al, 2006). Group-to-group collaborations are supported through the integration of various resources: large-format displays, multiple camera views and audio systems, multicast functionality. AGTk is an open source project, flexible software available for various platforms/hardware setups and operating systems, including Linux and Windows.

Other learning grids were developed for science, libraries, or distance learning. The five layer architecture described by (Tsai, 2006) supports multiple learning management systems (ILIAS, Claroline, and Dokeos, installed on different locations) and GridPortlets in order to use the Grid Portal. A similar architecture was reported by (Yang and Ho, 2005) being based on Globus and AGTk.

Supporting reusability, interoperability and shareability for virtual learning is possible by using standards for resource addressing, learning object description, and object sharing (ADL/SCORM). The EU project InteliGrid (Dolenc et al, 2007) is based on OGSA, and is complied with WSRF, WS+I (Web Service Interoperability), RBAC


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(Role Based Access Control model) and uses the Web Ontology Language for describing web services. Also, semantic grids were used for the SELF project (Abbas et al, 2005), and for Mobile Learning (Woukeu, 2005). Positive experience concerning the remote access and programming of robots was reviewed by (Albeanu et al, 2008) proving that a collaboration between engineering laboratories is possible.

4 Conclusions Taking into account the interconnection of specialized laboratories to the grid infrastructure, it is only a small step to create large scale virtual learning applications supported by the grid infrastructure. The global university will use not only e-learning platforms, but also virtual learning platforms integrating virtual reality laboratories.

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How to Model the Design Efficiency of the VLE?

Patrick Wessa

Catholic University of Leuven Association, Lessius Dept. of Business Studies, BELGIUM


Abstract This article discusses the use of a predictive decision model about a new type of statistical learning technology which is based on Reproducible Computing. The model predicts discretized exam outcomes based on objectively measured learning activities that are embedded within the pedagogical paradigm of social constructivism. However, the main contribution of this study is based on a quasi-experiment in which the pedagogical efficiency of two competing software design models are compared. In the first system, all learning features are a function of the classical Virtual Learning Environment (VLE). In contrast, the second system is designed from the perspective that learning features are a function of the course's core content (c.q. statistical results). The ceteris paribus effect of the design change (from VLE-based to Content-based) is shown to substantially increase the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. These results may, if confirmed in other circumstances, have important repercussions for the design of future learning environments. Keywords: Reproducible Computing, VLE, Software Design, Communication

Introduction Beyond any doubt, there has been a growing interest in Computer Assisted Learning (CAL) in the academic community. Most pedagogical studies however take the system design of the Virtual Learning Environment (VLE) for granted. This is surprising because the efficiency of CAL may be strongly influenced by the VLE's design which is typically beyond the control of the educator.

This study aims to demonstrate that - within the context of undergraduate statistics education - the design effect is measurable and potentially substantial. In order to achieve this goal, a two-year quasi-experiment was setup within the context of an undergraduate statistics course which is embedded in a socially constructivist setting.

The typical, modern VLE integrates a wide variety of general-purpose CAL techniques which are clustered around a course. In this sense the VLE is supposed to be of a generic and course-oriented nature. While there may exist many reasons why such a design is beneficial, there are no guarantees that such VLEs are well-suited to build effective and efficient learning environments in the field of statistics. One of the reasons for this is the fact that most statistics courses involve statistical computing which is not


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readily available in the VLE. As a consequence, educators often rely on external statistical software products which are often hard - if not impossible - to “seamlessly integrate” into the VLE. It is not surprising that many statisticians have found it necessary to develop new statistical software for the purpose of building a specific-purpose Statistical Learning Environment (SLE).

In this study the VLE design is represented by Moodle which is well-known in the academic community, and has been designed within the pedagogical paradigm of social constructivism (Wessa, 2009c). Within the context of this study the design effect that is investigated relates exclusively on socially constructivist learning activities that are supported by the VLE. A design change of the peer review module (and associated communication feature) is the main component that is subjected to change and ex-post analysis. The details of the design change will be explained in the section 2.

The inability of scientists to reproduce empirical research that is published in papers, has received a great deal of attention within the academic community. Several solutions have been proposed but have not been adopted in education because of the inherent impracticalities therein (Wessa, 2009b). For this reason, a new Compendium Platform (CP), which is hosted at http://www.freestatistics.org, was developed and allows us to create constructivist learning environments which are based on reproducible computing (hosted at http://www.wessa.net), and based on the R language) and with several advantages that relate to the monitoring of actual learning processes and quality control (Wessa, 2009b).

Henceforth, the term SLE refers to the computational system that comprises the actual statistical software (R Framework), the Compendium Platform (and associated repository of reproducible computations), and all interfaces that allow users and other software systems to interact with the components that are contained therein.

Design The investigation was based on an experimental, undergraduate statistics course for business students with a strong emphasis on social constructivism. The course contained a wide variety of statistical techniques and methods. For each technique, students had one or several web-based software modules available which are based on the R Framework. In order to implement this course within a setting of social constructivism for large student populations, it was necessary to impose a strict assignment-review mechanism. This is illustrated in figure 1 which shows a series of weekly events (lectures, assignments, reviews) during a thirteen-week semester. The semester ended with a final (open book) examination about a series of objective multiple choice questions. The examination was intended to test understanding of statistical concepts rather than rote memorization.

The main sections of the statistics course were built around a series of research-based workshops (WS1, WS2, ...) that require students to reflect and communicate about a variety of statistical problems, at various levels of difficulty. The workshops have been carefully designed and tested over a period of six years. Each workshop contained questions about “common datasets” and questions about individual data series - this dual


structure of the workshops promoted both, collaboration between students, and individual work. The top (blue) puzzle pieces in figure 1 represent threaded communication (between students) about each workshop.

Each week there was a lecture (L1, L2, ...) which was held in a large lecture hall that was equipped with computer screen projection and internet facilities. During each week, students were required to work on their workshop assignment and - at the same time - perform peer reviews (Rev1, Rev2, ...) about six assignments that were submitted by peers. Each review was based on a rubric of a minimum of three criteria and involved students to submit a workshop score and an extended feedback message (yellow puzzle pieces). The grades that were generated by the peer review process did not count towards the final score of students. Instead, the educator graded the quality of the verbal feedback messages that were submitted to other students. The grading was performed based on a semi-random sampling technique which allowed the educator to grade the quality of a relatively small - but fairly representative - number of submitted feedback messages from each student.

This feedback-oriented process is similar to the peer review procedure of an article that is submitted to a scientific journal. The key idea behind this constructivist environment is that students are empowered to interact with reproducible computations from peers and the educator. Students are required to play the role of an active scientist who investigates problems, presents solutions, and reviews the work of peers. Obviously, Reproducible Computing is a conditio sine qua non that allows students to engage in such peer review activities.

Original System Design - year 0 Figure 2 displays the VLE and SLE as it was used in year 0 (fall semester of 2007). It is clearly seen that this design contained two core objects: the course (yellow) and the computation (blue) which is represented by its snapshot. The course is the core object of the VLE which implies that all features that allow students to engage in collaboration or communication are bound to the course in which they reside. Several forums and instant messaging facilities were available to ask questions or to collaborate in various ways. In addition the Peer Review & Assessment procedure was available from within the VLE.

There are however, several pedagogical problems with this type of design because students were unable to:

• engage in review activities when they view the meta information about a computation - instead they need to login to the VLE and invoke the features of the Peer Assessment module

Figure 1 Schedule of learning activities - Year 0


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• read review messages that are submitted by other students about their own work unless they use the VLE and their own Compendium simultaneously

• compare review messages of computations that preceded the ones that are currently under review

• discuss or review statistical analyses across courses or semesters - as soon as the course is closed, all communications contained therein are lost forever

In addition, the collaborative communications about the workshops (blue puzzle pieces in fig. 1) and the feedback messages of the peer reviews (yellow puzzle pieces) were completely separated which implies that working on assignments and learning through peer review were completely detached activities. Finally, and notwithstanding the fact that sequential workshops were related in various ways, there was no structural information about the dynamics of collaborative and review-based communications across workshops. For instance, if students were required to test a certain statistical assumption in an early workshop that was an essential condition to perform some type of analysis in a subsequent workshop, then there was no link between the communications of both. The only way that could have been used to solve this problem (within the current design) was to repeat previous analyses in all related, subsequent workshops. Unfortunately, such an approach would have been highly inefficient and unfeasible because of many practical limitations.

Figure 2 VLE/SLE Design - Year 0

Figure 3 VLE/SLE Design - Year 1

Alternative System Design - year 1 Figure 3 displays the alternative design that was implemented in year 1 (fall semester of 2008). The most important design changes are as follows:

• there is only one core object: the computational snapshot • all (threaded) collaborative communications about the workshops are available

within the computational snapshot (which becomes a dynamic webpage) • all review messages are associated with the computational snapshot

The consequences of this design change had important consequences for the students because all collaborative and review-related communications were available from within the same source (the computation) which clearly highlights how they are related - as is shown in figure 4, the blue and yellow puzzle pieces within each computation are connected. This is not only true for a single computation - it also applies to


discussion/review communications that relate to different computations, irrespective of the time frame, course, or workshop in which they originated. The reason for this is the fact that the Compendium Platform automatically stores and maintains the parent-child relationships that exist between computations. For instance, if the educator creates a Compendium with a worked example that is based on an original computation C1 (see figure 4) then a student may reuse this computations (with changed parameters or data) for the purpose of working on an assignment task (C2). At a later stage, the same (or any other) student may reproduce C2 (and create C3) in order to check the assumptions of a statistical analysis that is embedded in a subsequent workshop. Other students (across courses and years) may reuse C2 for similar purposes (computations C4-C6).

The bottom line is that everyone who looks at C2 will have all the information that is available about computations C1-C6, including the hierarchical dependencies of computations and communications associated with them. This design change should increase the efficiency by which users can gain an understanding of statistical concepts and the dynamics of how computations evolve (and improve) over time. Unlike in the traditional setting (year 0) no information is ever lost after the semester because the

communications are independent of the courses. In general words, the fundamental principle that is applied in this VLE/SLE design is

that the educational system is subject-oriented instead of course-oriented. In statistics education, it is the statistical computation that is subjected to study - the course is entirely irrelevant. The traditional VLE is an educator-centered system that allows the educator to manage students, and resources that belong to the course. The new SLE design is more student-centered because it is focused on the learning content which implies that all learning features (including communication, peer review, etc...) depend on the (subject-oriented) core object.

Methodology

Measurements The empirical data was collected through an experimental undergraduate statistics course which was provided during two consecutive years. In each year, the conditions that are under the control of the educator (and the institution) were kept equal except for the system design. The (quasi) experiment is not under perfect control but given the fact that the characteristics of the student population did not change, it is fair to assume that

Figure 4 Hierarchical structure of computations - Year 1


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conditions were equal in both years. Therefore it is fair to attribute any changes in learning efficiency (ceteris paribus) to the change in system design.

The measurements were obtained from a Business Studies department in Belgium during two consecutive years (labeled “year 0” and “year 1”). In each year there were two cohorts: bachelor students, and students from the preparatory program which allows graduates from a professional bachelor program to switch to an academic master. In general, bachelor students have better prior understanding of mathematical concepts than prep-students. However, prep-students tend to have a higher degree of maturity and self-motivation than bachelor students.

Table 1 Student Population

Year 0 Year 1 Female Male Female Male Bachelor 58 53 41 42 Prep. 53 76 45 74 Total 240 202 In order to be able to compare the dependencies of exam scores from exogenous

variables that are based on objective measurements of (constructivist) learning activities, it is necessary to apply optimal exam score transformations for both years. The methodology that allows us to do this is based on a mathematical model which is described in (Wessa, 2009) and has been shown to yield models that improve the predictability of learning outcomes substantially.

After the objective exam score transformation has been applied, it is possible to proceed to the next step which involves the creation of predictive models (c.q. regression trees) that allow us to discover the rules that determine whether students will pass or not. In this study, the degree of predictability is maximized (through the transformation methodology) but is otherwise irrelevant to answer the main research hypothesis: “does the changed VLE/SLE design improve the efficiency of learning activities (such as peer review) in the undergraduate statistics course?” In other words, we are mainly interested in the (efficiency-related) parameters of the decision rules, not the original (untransformed) exam scores (which are incomparable), nor the overall degree of predictability.

Regression Trees For the purpose of computing a rule-based regression tree, the endogenous variable must be discretized. Therefore, three categories are defined which are called “guess”, “fail”, and “pass” respectively. The “guess” category represents the lowest exam scores which can be attributed to chance (or guessing). Exam scores in the “fail” category are lower than what is needed to pass the exam but higher than what can be (reasonably) explained by chance. The “pass” category contains scores that are sufficiently high to be considered satisfactory even if the numerical value is below 50% of the maximum attainable score. The reason for this is the fact that the exam questions had varying degrees of difficulty


and were (overall) designed to be much more difficult than what could be reasonably expected from undergraduate students in business studies.

Introducing a high degree of difficulty in the exam questions is necessary in order to ensure that:

• rote learners are not likely to pass the exam • we are able to identify the maximum level of understanding • students are unable to quickly find answers in printed resources that are allowed

during the exam The exam in the second year was slightly more difficult than in the first year (the

transformed exam scores in year 1 were slightly lower than in year 0). Therefore it is not possible to simply use identical threshold values for the categories in the transformed exam scores from both years - an objective benchmark is need to generate fair and comparable categories.

The threshold values that define the categories are not arbitrarily chosen but depend on exam score statistics of the previous four years (with exams of similar difficulty). On average the proportion of lowest scores (which fall in the “guess” category) was little less than 10%. The proportion of “guess and fail” scores was approximately one third of all exam scores. These proportions had been quite stable over the time frame of those four years. Therefore it is fair to assume that they represent appropriate, “unconditional” probabilities to pass or fail the exam. As a consequence the threshold values that define the three categories (for each year) are computed as the 1/10 and 1/3 quantiles of the (optimally weighted) exam scores in year 0 and 1.

Even if we wouldn't believe that the threshold values are adequate there is another justification of using the same quantiles (rather than identical exam scores) to determine the categories. The rationale is simply that we want to predict if students fall in the “high”, “low”, or “extremely low” proportion of all students in the same year (who took the same exam). The parameters in the rule-based regression trees quantify the amount of learning efforts (number of peer review messages, and number of computations) that are required to achieve an exam score that falls within the top 2/3 of all scores.

The rule-based regression trees were computed with the statistical engine called Weka which is available from within the R Framework through the RWeka interface (Hornik et al., 2009).

Empirical Results

Table 2 Nomenclature in rule-based regression trees

Variable name Description nnzfg # of non-empty, meaningful feedback messages that were submitted nnzfr # of non-empty, meaningful feedback massages that were received Bcount # of reproducible computations that were generated Gender binary gender variable (0 = females, 1 = males) Pop binary cohort variable (0 = bachelor students, 1 = prep. students)


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Table 2 shows the exogenous variables that were chosen to create rule-based regression trees. The first three variables are positive, numeric integers. The last two variables are binaries that indicate to which cohort the student belongs. Note that the same exogenous variables were used in the objective exam score transformations based on the three-stage regression approach and with all possible interaction effects included.

Figure 5 Regression Tree - Year 0

Figure 6 Regression Tree - Year 1

The first rule-based regression tree (fig. 5) displays the situation for year 0 in which the traditional VLE design is used. The most important rule that determines success (c.q. falling into the top 2/3 proportion of all students in year 0) is the number of submitted feedback messages (related to peer review). It can be clearly seen that students pass if nnzfg > 118 which means that they need to submit more than 118 feedback messages in order to pass the exam. The other students (with nnzfg ≤ 118) fall into two categories, depending on the number of reproducible computations they generated. Students with nnzfg ≤ 118 and Bcount > 10 are predicted to pass the exam - in other words, students who did not engage sufficiently in feedback activities could compensate this by reproducing more than 10 archived computations. However, the accuracy of this particular prediction is not very good because there where only 37 cases correctly attributed to the “pass” category whereas 15 cases were incorrectly predicted (the number of in/correctly classified cases can be seen in the gray boxes).

There are two specific rules in the regression tree that cause concern. The first one, is the rule that states that male students who did not spend a sufficient amount of effort in terms of feedback and reproducing computations (nnzfg ≤ 118 and Bcount ≤ 10 and Gender = 1) either fall into the “guess” or “fail” category (depending on the Pop cohort they belong to). The second rule that causes concern is the one that states that female students may pass the exam, even if they have only between 52 and 118 submitted feedback messages (nnzfg ≤ 118 and Bcount ≤ 10 and Gender = 0 and nnzfg > 51).

The bottom line is that both rules imply that the VLE/SLE system in year 0 favors female students and discriminates against males. This may be surprising because it is often believed that male students have “better” attitudes towards computing than females.


In this situation however, it is shown that female students are better able to cope with the detached structure between collaborative and review-based communication on the one hand, and reproducible computing on the other hand. This phenomenon may have psychological causes that are related to the fact that there are gender differences in how students use communication in learning. Within the context of this study, such an explanation remains speculative and unanswered. However, and more importantly, it is clear that the design of the VLE and SLE is not optimal - at least for an important part of the student population.

Figure 6 shows the rule-based regression tree for year 1 (in which the new VLE/SLE design was implemented). It can be easily observed that the structure is fundamentally different from the previous situation. By far, the most important property of this regression tree is the root rule which states that students pass if they submit more than 57 meaningful feedback messages. This is less than half the amount that was necessary with the previous system design and demonstrates a spectacular increase in review-based learning efficiency. More importantly, the discrimination effect has completely disappeared which implies that males are now equally well able to make good use of the learning environment. Students who did not submit a sufficient number of feedback messages and only received 16 messages (or less) fall into the “guess” category. This makes a lot of sense because students who don't submit workshop papers, don't get reviews.

There is a striking resemblance between female prep-students and male bachelor students (fig. 6): they both pass the exam when a sufficient number of computations have been reproduced. In addition, the female bachelor students and male prep-students are also similar with respect to the number of received feedback messages: if this number is too high, then the student does not pass because it indicates that they are making too many mistakes or are not making good use of inbound messages.

As explained before the overall predictability (of both rule-based regression trees) is not an important aspect which determines if the design effect had any impact on learning efficiency. Nevertheless, an overview of within and out-of-sample prediction performance is provided in table 3 because it is important to show that the models do not suffer from severe “over-fitting” which might invalidate all conclusions made on the basis of the regression tree's parameters.

Table 3 Prediction Performance of Regression Trees

Statistic Year 0 Year 1 Within

Sample Cross Validation

Within Sample

Cross Validation

Correctly Classified 78.3% 72.5% 87.1% 74.8% Incorrectly Classified 21.7% 27.5% 12.9% 25.2% Number of Leaves 7 11 Size of Tree 13 21 Total Number of Cases 240 202

The results in table 3 clearly illustrate that the out-of-sample prediction quality is

adequate. In case of over-fitting, one would observe high percentages of correctly


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classified instances within sample and a (very) low percentage out-of-sample. The out-of-sample prediction quality is computed by applying a so-called Cross Validation technique which randomly divides the data set into a large training subset and a testing subset. The parameters are estimated, based on the training sample and the prediction is computed for the testing subset. This procedure is repeated 10 times (10-fold Cross Validation) to obtain an average measure of out-of-sample prediction quality.

Conclusions The empirical analysis has clearly shown that the change in VLE/SLE design had a very beneficial effect in terms of increasing the learning efficiency of submitting peer review messages. More importantly, the design change has resulted in the elimination of a discrimination effect which was embedded in the original design where communication and computation was separated. In any case, the methodology that was outlined can be used to test for any software-related or content-based aspect as long as it is controllable by the educator or designer of the learning system. However, one should take care to take into account that exam scores are properly treated in order to avoid the pitfalls that are associated with exam questions.

Obviously, this study is limited to the case of our undergraduate statistics course for business students. Also, there was a strong focus on one specific type of constructivist learning activity (peer review) which implies that other pedagogical approaches might have resulted to other conclusions.

Nevertheless, it is interesting to formulate a general conjecture about a fundamental principle of good VLE design. The proposed conjecture states that good VLE design requires the developer to define a single subject-based, core object instead of using the traditional, educator-centered course object. In simple words, it is better to integrate learning features (forums, messaging, peer review, etc...) into the software that treats the subject under study than to build general-purpose VLEs. If this conjecture would turn out to be true, it would have important repercussions for the design of VLEs in general and specific-purpose software (such as: statistical software, wikis, CAD/CAM applications, programming environments, etc...) in particular.

REFERENCES

HORNIK K., ZEILEIS A., HOTHORN T., BUCHTA C. (2009). RWeka: An R Interface to Weka. R package

version 0.3-16. URL http://CRAN.R-project.org/package=RWeka ROMERO C., VENTURA S., GARCIA E. (2008), Data mining in course management systems: Moodle case

study and tutorial, Computers & Education, 51, 368-384 WESSA, P. (2009a), Quality Control of Statistical Learning Environments and Prediction of Learning

Outcomes through Reproducible Computing, International Journal of Computers, Communications & Control 4(2)

WESSA, P. (2009b), Reproducible Computing: a new Technology for Statistics Education and Educational Research, IAENG Transactions on Engineering Technologies, American Institute of Physics, Eds: Rieger, Burghard, Amouzegar, Mahyar A., and Ao, Sio-Iong

WESSA, P. (2009c), How Reproducible Computing Leads to Non-Rote Learning Within Socially Constructivist Statistics Education, Electronic Journal of e-Learning 7(2)

A model for the evaluation of learning styles design effectiveness

G. Bruno Ronsivalle1, Massimo Conte2

1La Sapienza University of Rome, Italian Banking Association E-mail: [email protected]

2Label Formazione E-mail: [email protected]

Abstract Assessing the customized system of a formative path, on the basis of cognitive styles, needs two fundamental requirements:

a) the choice of a strong learning design model, built on conceptual maps, didactic objective trees and observable behaviours taxonomies (Bloom, Anderson, Romiszowski and Marzano);

b) the utilisation of the Kolb Learning Style Inventory to evaluate the preferences individuals show in the learning context.

In the micro design phase each learning style is related to a different didactic strategy to manage the cognitive dissonance: - Diverging: the negative case; - Assimilating: the Quaestio; - Converging: the Reductio ad absurdum; - Accommodating: the linear simulation.

The activities performed to evaluate a traditional class sample compared to an on line course sample (WBT) are: - the administration of the Kolb Learning Style Inventory to identify students learning

styles; - the class delivery based on the learning styles (differentiated according to the

population sample of traditional and on line courses); - the assessment of the I, II and III level learning effectiveness index in relation to the

two kinds of course and the four learning styles; - the administration of a Satisfaction Questionnaire; - the calculation of the learning time (in traditional class and on line course as well); - the efficiency calculation; - the comparison between effectiveness and efficiency.

The research goal is verifying how the customisation of formative paths, based on students learning styles, can affect not only the formative effectiveness but also the efficiency in the learning design and the cost impact. Keywords: Learning Styles, Learning Effectiveness, Efficiency

1 Formative quality and micro design Formative quality depends on many factors and involves different phases of the design process: from general strategy formulation to specific choices in micro design phases.


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Just in relation with the micro design phase, an experimental hypothesis will be here introduced: an applicative model has been designed to optimize and standardize decisional processes in order to define single strategies for several courses didactic units. Such model summarizes former design method – based on cognitive dissonance – and learning styles Kolb theories. Main goal is defining a micro design method, a reference theoretical frame and a precise procedure to assess the model itself and get the best formative quality. 2 Micro design dimension: complexity, cognitive styles and learning styles In micro design phase the most suitable strategy to single individuals has to motivate them to accept new input and get the course didactic objectives. This choice, crucial for creating storyboards and get satisfactory effectiveness levels, is based on three fundamental principles:

1. The didactic path must be perceived as useful, functional and suitable for user professional needs; which means formative contents must be calibrated on different complexity levels to get. This implies classifying contents complexity levels through a taxonomy allowing to interpret competencies features in five specific factors: (1) Four levels of Knowledge: Atomic mental models, Logic connection, Nomic relationships, Probabilistic connections; (2) Typology of Perception: Attention, Perceptive analysis, Perceptive synthesis; (3) Mnemonic process: Recognition, Recall; (4) Typology of Elaboration: Analysis, Synthesis, Evaluation, Creation; (5) Typology of Behaviour: Reproduction with support, Autonomous reproduction, Orientation to the objective, Strategic behaviour, Automonitoring (Bloom, 1956; Romiszowski, 1999; Anderson and Krathwohl, 2001; Marzano and Kendall, 2007).

2. The didactic path must generate a cognitive dissonance status in user’s mind motivating him to research and select potentially consonant information, reduce dissonance and/or avoid information potentially increasing dissonance (Ronsivalle and Metus 2005). In 2004 a set of four plots has been designed to create differentiated storyboards and effectively manage cognitive dissonance.

3. The didactic path must adopt a formal model coherent with user learning styles. Such principles and their detailed definition in building didactic units are a strong

point in micro design phase.

3 Learning Styles Assessment Let’s try to delve into the third principle.

Kolb distinguishes four different learning styles (or preferences) based on a four steps learning cycle, in which concrete experiences are observed and integrated in abstract concepts involving actions in order to create new experiences (Kolb 1984).

Ideally the process represents a learning cycle or a spiral where the subject tests, thinks and acts. The above-mentioned steps are: (1) Concrete Experience – (CE); (2) Reflective Observation – (RO); (3) Abstract Conceptualization – (AC); (4) Active Experimentation – (AE).


Experiential Learning is a process where constructing knowledge involves a creative tension among the four learning modes responsive to contextual demands (Kolb et al 1999).

Because of our hereditary equipment, particular life experiences and present environment demands, we develop preferred ways of choosing among the four learning modes. Kolb Learning Style Inventory - Version 3.1 (Kolb 2005) is used to assess individual learning styles. Each style is associated with a different learning approach (Diverging, Assimilating, Converging and Accommodating).

LSI is a useful tool to recognize uniqueness, complexity and variability in learning personal approaches. It can be used as a support to customise the learning design in strength of users learning styles.

If personal preferences have a stable nature, it’s possible to hypothesize a formative path still unique but including the four learning styles.

4 The path customisation o Didactic strategies differentiation In order to define motivation techniques with Kolb theory, four different didactic strategies have been linked to the learning styles to customise a class (traditional or on line as well):

Learning Style Characteristics Strengths

Education

al Strategy

Scheme Function

Diverging

Ability to take in information through concrete experience and processing it

through observation. Imaginative ability to generate many alternative ideas

Brainstorming, feeling-oriented

Case study

Negative case

Involving through

dissonant factors

Assimilating

Ability to abstractly take in new information and process disparate

observations into an integrated rational explanation. Good at inductive reasoning and the creation of models and theories

Systematic planning, goal

setting

Tutorial/

inductive

Quaestio

Involving through slightly

dissonant factors

Converging

Ability to take in new information in the abstract and process it into a concrete

solution. Hypothetical deductive reasoning get the best solution to a

question or problem

Solving problems and

making decisions

Tutorial/

deductive

Reductio ad

absurdum

Defining the theoretical scenario

Accommodating

Ability to concretely take in new information and actively transform it, considering circumstances changes

Carrying out tasks, learning

through practical

experience

Simulation

Linear simulati

on

Simulating an interaction context, in order to get

operative tools to reproduce

the real world

Table 4 Learning Style-Didactic strategies Matrix

In our research, after analysing learning styles features we defined different educational strategies through Kolb Learning Styles Diagram, customizing the original version.


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Figure 7 Educational strategies connected with Kolb Learning Styles Diagram

As subjects learn how to identify their personal learning styles, the hypothesis we bring forward is the customisation of the cognitive dissonance management, considering learning styles features.

Identifying learning styles can help manage cognitive dissonance and the resistance to learning: specific algorithms can actually optimize the learning effectiveness.

o Flexible micro-design cognitive styles oriented In order to define a first laboratory session to test the model here introduced, a didactic unit has been micro designed about different effectiveness index levels (Ronsivalle et al, 2009; Ronsivalle and Donno 2009). The didactic unit, addressed to instructional designers, was structured as on line or traditional class as well.

Following contents, written according to four different learning styles, here describe the general formula to get the first level effectiveness index:

Figure 8 Micro design contents


The underlying didactic objectives tree structure granted a unitary path, even if four didactic strategies were used as design modalities to get storyboard variations in relation with different learning styles. Following model principles every learning style can match with a specific learning strategy. Final results are four different cases.

Negative Case oriented storyboard In reference to the model, Diverging style (Concrete Experience – Reflective Observation) was associated to Negative Case and storyboard was structured as follows:

− page 1: general introduction of a negative case (in the given example building a training course) very close to students reality;

− page 2: further information were given to illustrate how to manage the problem; − page 3: new information become necessary; to correctly solve the problem a

formula to calculate the effectiveness index is described; − page 4: interaction to allow student to identify Negative Case issues: resolution is

possible only after considering the explained Theory.

Figure 3 Negative Case oriented storyboard – Page 2

Student approaches the case in a concrete scenario. As external observer he can collect information, analyse the problem, summarize the theory and answer the interaction.

5 Quaestio oriented storyboard Assimilating Style (Abstract Conceptualization – Reflective Observation) was associated to Quaestio strategy:

− page 1: the problem is introduced by some questions; − page 2-3: a scheme defines elements to calculate effectiveness level; − page 4: the index definition allows answering questions from page 1.

People learning by Assimilating Style understand and manage many information in a logical way: they’re interested in abstract concepts and theoretical strength, more than practical application of a theory. In our case the didactic strategy was illustrating, through schemes and images, elements to define the effectiveness index.


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Figure 4 Quaestio oriented storyboard – Page3

6 Reductio ad absurdum oriented storyboard Converging Style (Abstract Conceptualization – Active Experimentation) was associated to Reductio ad Absurdum strategy:

− page 1: an hypothesis A is introduced; − page 2: an absurd conclusion is given; − page 3: a new, correct hypothesis B is introduced (tertium non datur).

Figure 5 Reductio ad Absurdum oriented storyboard – Page 3

This strategy is suitable to people inclined to solve problems and make decisions by searching solutions. Reductio ad Absurdum consists of validating a theory/hypothesis through the falsification of the wrong theory/hypothesis. Analysing many solutions is more complicated but clearly suits such learning style the best.


7 Linear Simulation oriented storyboard Accommodating Learning Style (Concrete Experience – Active Experimentation) is associated to a linear simulation.

− page 1: scenario introduction (student in charge of designing learning courses); − page 2: step 1 objective (to calculate the course effectiveness index); − page 3: step 1 interaction (to individuate the correct formula).

Figure 6 Linear Simulation oriented storyboard – Page 3

A simulation reproduces a concrete situation. In this “laboratory”, protected from external factors, user can test a “soft” version of his/her professional life, interacting with actors, context and observing his/her actions effects. People learning by this style are oriented to refer to their personal experience: the story is told in second-person narrative mode, user is the protagonist and every step represents a decisional moment.

8 Conclusions: Framework to meta-evaluate micro design model The experimental validity of the hypothesis here introduced is related to some quality indicators, useful to evaluate the model suitability:

− 1° level index: the ratio between course added value and student formative need; − 2° level index: allows pondering the general effectiveness taking into account the

expected increase of knowledge/competencies homogeneity level; − 3° level index implies considering learning time and includes a further correction

factor in line with average and a priori expected learning time: higher the gap between the expected and actual temporal values, lower the 3° level effectiveness index;

− popularity rating consists of quantitatively composing a rank scale by analysing values in relation with variables such as users subjective perception;

− efficiency level derives from the ratio between production costs (including or corresponding to production time) and 3° effectiveness index level.


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The experimental framework validating the model foresees the following procedure: (1) selecting among 100 people two isomorphic samples A and B, considering LSI administration results; (2) delivering contents by different learning styles strategies to users sample A; (3) randomly delivering contents to users sample B, not considering learning styles; (4) calculating quality indicators for each sample; (5) comparing the analysis of different results to establish best effectiveness and efficiency levels.

Verifying experimentally our model was a requirement to define a strong micro design tool in order to reconcile cognitive dissonance management techniques with students learning styles. The five dimensions taxonomy above introduced matches the model as the micro design strategic option is transversal to complexity levels. In fact, there’s no direct relation among complexity levels (knowledge, perception, memory, elaboration and application), dissonance schemes and learning styles: the first ones are directly related to contents, the second ones depend on external variables and the last ones concern individual features.

REFERENCES

Anderson, L.W., Krathwohl D. R. (2001): A taxonomy of learning, teaching and assessment: a revision of

Bloom's taxonomy of educational objectives. Longman, New York. Bloom, B.S. (1956): Taxonomy of Educational Objectives: The Cognitive Domain. Giunti e Lisciani, David

McKay Co Inc New York. Coffield F. et al. (2004): Learning styles and pedagogy in post 16 learning. Learning & Skills Research

Centre, London. Kolb, D. A. (1984). Experiential Learning: Experience as the source of learning and development. Prentice-

Hall, Englewood Cliffs, N. J. Kolb A. Y. and Kolb D. A. (2005), The Kolb Learning Style Inventory, Version 3.1, 2005 Technical

Specifications. Kolb, D. A., Boyatzis, R. E., Mainemelis, C. (2002). Experiential learning theory: Previous research and new

directions. In Sternberg R. J., and Zhang L. F., (Eds.). Perspectives on cognitive, learning, and thinking styles. Mahwah, NJ: Lawrence Erlbaum.

Marzano, R.J., Kendall, J.S., (2007): The New Taxonomy of Educational Objectives (2nd Edition). Corwin Press, Thousand Oaks, CA.

Romiszowski, A.J. (1999): Designing Instructional Systems. Kogan, Page, London. Ronsivalle, G.B., Carta, S., Metus, V. (2009): L’arte della progettazione didattica. Franco Angeli, Milano. Ronsivalle, G.B., Donno, V. (2009): A model for the evaluation of learning effectiveness in Second Life. In

Proceedings of 4° Encontro Internacional Artibytes, Santarem. Ronsivalle G.B., Metus V. (2005): Motivation and micro-design models and techniques. In Proceedings of

TACONET Conference Self regulated learning in Technology Enhanced Learning Environments, Lisbon, 28-42.

Metrics and requierements in Learning Management System

Ion Roceanu1, Virgil Popescu2

1Advanced Distributed Learning Department, Bucharest, Panduri Street, 68-72, Romania, [email protected]

2Expert Trade Company, Lipscani Street, Bucharest, [email protected]

Abstract This papers in focused on the operational requirements in choosing the proper Learning Management Systems to support the on-line educational services in the academia. The general and specific requirements are compared with a set of metrics settled by the stakeholders in the stage of prepare the decision of what kind of LMS is fitted to the institutions educational objectives.

1. Introduction

This paper is based on the National Defence University of Romania experience in developing a set of capabilities to create, to deliver and to manage the educational on-line services. The NDU`s eLearning project started in autumn 2004 and became operational in the spring of the 2006.

At the beginning of this project we aimed to create an integrated system in order to make effectiveness the educational activity based on IT&C and generate, develop and manage the distance learning curricula under the national educational laws and fully according with the NATO ADL principles. It is not necessary to mention at that time we did not have a strong support and of course no budget, from higher decision level, the situation well known by the eLearning stakeholders in the world. Consequently, we made the first step trying to buy-in support, and we considered that we can do this only by demonstrating the utility, viability and performance of the results of our new educational approach.

The LMS is considered being one of the most important things in eLearning and for sure it is the only means to manage the content delivering inside the educational system. For several reasons we had a very hard decision to take as to which LMS is proper for our educational purposes. In this respect, at the beginning of our enterprise to develop an eLearning system, we tested more LMS, both commercial and open-source. Finally, we chose open-source one, not due to budget restrictions reasons but for its features offered to the home developers and tutors facilities. In this way, we selected the ILIAS LMS to be implemented at the National Defence University. This LMS is used in the others military universities eLearning systems, as well.

Since 2005 we employ ILIAS and are very satisfied with the results of educational services provided trough it and the feed-back from our students and tutors evaluation.


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2. Process of choosing the proper LMS Choosing a LMS is not a very easy job, it has to be based very strictly on requirements, metrics and standards. For this reason we created three different sets of requirements and for each of them we generate a test bed.

1. Tools and capabilities to support the content and course management 2. Tools and capabilities to support students activity and learning tracking progress 3. Technical aspects regarding the installation, administration, update, customization

and others. “A very good LMS is not the best of the market it is only perfectly fitted with your

needs”. To put in practice this motto, first of all, we defined very clearly what kind of on-line educational services we want to deliver in the next few years. Practically, our institution has three different categories of on-line educational services:

1. Full on-line courses. All kind of activities, from subscription to final evaluation are carried out on-line. The course content is fully compliant with SCORM standards. From this result that the LMS has to support SCORM content and all features around SCORM development.

2. Blended learning. Parts of educational activities are made on-site and other, at least 66 %, are supported on-line. Consequently, the LMS has to provide the possibility to combine within one single curriculum SCORM content and other formats of content, such as: html, word, excel, ppt. file, pdf, pictures, video and so on.

3. Educational services support for master and doctoral studies. The LMS has to provide a very good virtual collaborative space between teachers and students and among them.

The table below contains an overview over the results of our evaluation broken down by required functionality.

Functionality Requirement Range Score

General

Overview Content repository Data export/import

Low = 1 High = 5

ILIAS – 4 OOS* - 4

COTS** - 4

SCORM compliant

SCORM 1.2 SCORM 2004

Full both=5 Only one = 3

No one =0


COTS** - 3

Learning tracking progress

Per student Per course Per item

Low = 1 High = 5


COTS** - 4

Content formats

Text Images Video

Low = 1 High = 5


COTS** - 4

User interface

Friendly Intuitive

Help support

Low = 1 High = 5


COTS** - 4

Customization Personalize

Integration in the portal Course management

Low = 1 High = 5


COTS** - 2


Collaborative tools

Chat, Forum Sync collaborative

Mail

Low = 1 High = 5


COTS** - 5 Technical administration

Different OS Security

Backup auto

Low = 1 High = 5


COTS** - 3 Maintenance and cost

On-line support Experience

Others military institution

Low = 1 High = 5

ILIAS - 4 OOS* - 4

COTS** - 2

Average ILIAS – 3,88 OOS* - 3,66

COTS** - 3,44 * OOS – Other Open Source LMS ** - Commercial On The Shelf

Form our perspective there are some strengths and weaknesses of ILIAS: Good points: 1. The ILIAS is a scalable, highly configurable platform for creating and managing

classroom-based and e-learning activities, curriculum, and courseware. 2. Very good course, content, students and learning tracking progress management

tools. 3. Customizable interface (multilanguage and presentations) and course domains 4. Content multi-format supported 5. Multilingual Need to be improved or added: 1. Context-senistive user help provided by the LMS 2. Synchronous module for collaborative space 3. SCORM sequencing capabilities 4. Virtual classroom is missing

3. ILIAS at the Romanian National Defence University It is installed on LINUX machine and it is integrated in the eLearnig portal such as the learner has a single gate of access to any kind of learning resources: courses, virtual library, conference and so on, figure no1.

Using the course and content repository we provide varied curricula and courses together with on-line educational services support: full on-line courses, military professional courses, long-term curricula, doctoral and master studies, figure no.2.

Below, figure no.3, is presented the SCORM content managed by this LMS in order to support full on-line course “Conflict Management and Negotiation”. The course has 13 items, each of them are divided in other small learning objects accompanied by specific educational objectives.

As was mentioned in the selection criteria, the learning tracking progress tools offered by the LMS were of utmost importance for us. In this sense, the ILIAS offers several tools providing us with the possibility to the status of the learning progress for each student, figure no. 4. Also, we have the possibility to have a number of other data considered very important by our tutors: time spent for each learning objects, links followed, how many collaborative tools used and so on. Based on this information, the tutor can coordinate the learning activity of each student in a very personalized way.


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Figure no.1 – User registration

Figure no. 2 – Course and content repository

Figure no.3 – SCORM content on the ILIAS


Figure no.4 – Learning tracking tools

Conclusions We do not want to say that the LMS chosen by us is perfect but at this moment it offers us the best solution for our needs. In the same time, for synchronous didactical activity delivered inside our eLearning laboratory or on-line by Internet we use another LMS, commercial one produced in Romania. It is AeL from SIVECO Romania. It is very difficult to find a solution which covers at high parameters all educational on-line activity and in many cases is recommended to use two or three LMSs.

As we mentioned, at the beginning of our eLearning project, we tested more LMSs, both open source and commercial, but we cannot give a recommendation that one is better than another. Open source comes with some positive aspects, such us: costs, flexibility, community support and so on, but brings others negative points: requires more technical skills from the stakeholders, no warranty about bugs or updates and so on. The commercial LMS could be expensive or very expensive if some personalized features are desired but in the same time offers technical support and assistance.

In according with those written above, and taking in consideration that the eLearning market is very dynamic, we decided that is better for us to make permanent tests on different LMS and probably in one or two years we will take a long term decision.

REFERENCES

Mircea Muresan, Ion Roceanu – Security Through Knowledge – Network Based Security Education, Berlin EDUCA 2006, ISBN 3-9810562-3-x

Ion Roceanu, Citizens` security education based on e-learning technology, Berlin, EDUCA 2007, ISBN 3-9810562-7-2

Ion Roceanu, Alexandra Toedt, Managing the information deliver the knowledge. Steps in developing the digital content, eLSE Conference, Bucharest, 2008 Ion Roceanu, ADL master Plan Development, NATO ADL Forum, Norfolk, SUA 2006 Learning Management Systems: A Teacher's, Australia, 2003, at http://community.flexiblelearning.

net.au/TeachingTrainingLearners/content/ http://adl.unap.ro http://www.ilias.de/

Mapping the Spaces of Virtual Learning Environments

Ioannis Paliokas

Democritus University of Thrace, Department of Primary Education N. Chili, Alexandroupolis, GR-68100, GREECE


Abstract Virtual Learning Environments (VLEs) are an expression of the post-modern school. In this paper we discover how the functional requirements of the VLEs affect and are being affected by the educational, ethnographic and social spaces. It is supported that educational effectiveness of VLE is not proportional only to the quality of learning material, but also to the general educational context of the VLE regarding social characteristics that should be in line with the normal school life. In order to eliminate certain negative issues related to empty and boring VLEs we study the mapping of educational, mental and social spaces into modern virtual environment’s philosophy of use.

Keywords: VLE, Blended Learning, Virtual Identities

1. Introduction The increasing availability of communication technologies in all aspects of everyday life has maximized the expectations from technology in general. The same thing happened to VLEs when introduced to school environments: aalthough they started as experimental projects, soon they became very popular. VLEs allow the multiple levels of engagement and they are transforming the roles of teachers and students as well as their motivation (Lennon and Maurer, 2003). Moreover, they propose a ‘socially constructed presence’ (Arminen et al, 2008) and thus they constitute an irreversible change in school environments history, just like cell phones has changed the meaning of distant communication.

Teaching with VLEs includes the use of a wide range of software tools, personal computers and PDAs, curriculum design, management of student’s profiles, online help and documentation to gain better learning outcomes. From a technological point of view, VLEs could be seen as the evolution of educational software. It has been reported that there are four generations of VLEs (Ivanova and Smrikarov, 2004):

1. First generation which mainly include databases of learning material, testing systems and discussion forums.

2. Second generation which is based on integrated databases and organized learning processes, administrating policies, statistics and metadata.

3. The cutting-edge third generation which supports audio and video conferences, student collaboration over one project and integrated learning services.

University of Bucharest and “Gh. Asachi” Tehnical University of Iasi

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4. For future development, the forth generation is about personalization, adaptation to the needs of students using artificial intelligence, multi-agent technology, etc.

On the other hand, Blended learning appears today more realistic than pure online web based learning according to students responses (Garrison and Kanuka, 2004). Based on promising indications, this will continue to be true in the near future not only because it broadens the learning environment and blurs the limits between virtual and physical space, but mainly because it allows the continuation of pre-existing community ethics. Blended Learning as term is not clearly defined because of contrasting definitions (Oliver and Trigwell, 2005). In this paper the term is used to indicate the integrated combination of face-to-face traditional with web based online teaching and learning activities.

Having discovered the recent VLE technologies and research findings about Blended Learning published in the international literature, this paper aims to shed more light into important aspects of virtual school life and blended learning experiences. In particular, the main question is: which common spaces traditional and virtual learning environments share? How student’s experiences are shaped when both environments are used simultaneously?

2. From Locality to Diversity (and back)

2.1 Exploring the learning spaces VLEs create learning spaces where distant students and teachers collaborate with each other in order to reach goals. The geographical distance is not any more a factor that can influence learner’s participation in a negative way. In VLEs, distances are measured in number of clicks. On the other hand, the feeling of students being close to their instructor is called transactional distance (Coopman, 2009). This distance can be eliminated in VLEs because of the fact that participants adopt new identities which represent themselves in a less socially structured or differently structured environment. For example, while being very important as an organizer and having a high symbolic value, the instructor is not the only source of information. Actually, the diversity of information is such, that when someone says ‘I study at some fine university or school’, he/she actually specifies the institution which will honour him/her with a diploma. There is no doubt that educational institutions create other kind of qualities to separate themselves from others. What is really mentioned here is that the actual learning environment for each individual is not limited to a specific campus and nobody can tell exactly how many teachers are involved in a course. A typical student normally spends more time searching on the Internet than attending lectures. He/she also reads articles, forums and participates in conversations with other students who share similar interests.

In the last generations of VLEs the diversity of information is maximized. Learning resources from inside or outside of the VLE can be structured and delivered in such a way that give to participants a sense of information continuation. Also, the learning resources are enriched by the participant’s active enrolment. Finally, the content of a given VLE include mixed textual, vocal and pictorial material where the distinction of the ‘formal’ educational material may not be the most important thing. Although technologically it is easy to notate the official course material given by the instructor and the official libraries, finally in a mixed information space this is not the primary purpose of learners. For


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example, learners are highly interested in finding the other people’s explanations and evaluations of a given set of learning material trying to figure out what to do with it.

2.2 The need for ‘localities’ in the information space The effectiveness of VLEs is analogous to the frequency of their use. When rarely used, they become frozen environments with low importance. Researchers propose the structured information space, careful learning activities design and motivation as ways to avoid the phenomenon of ‘Virtual Ghost Town’ (Kapp, 2009). Diverse users who share the same information space prefer to create localities. Those localities can be social like a virtual community or a small group of friends sharing the same forum or chat room. This is typical to human behaviour. Actually, it has been reported that relationships among members have the potentiality to grow faster than the absolute number of members (Golbeck, 2007). These self-organizing communities create their own shared identities (Lombardi and McCahill, 2004). Other type of localities in information space is personal user profiles. Each learner creates his/her own user profile and provides, apart form personal information, information about interests, courses, finished projects, communities he/she belongs. It is a unique set of structured information and metadata describing a person as a student and this is the first step to create a virtual identity. Virtual identities help us to realize our existence into virtual spaces and probably it is the only way to start socializing with others. Other localities are personalized digital libraries, where diverse pieces of information have something in common: they belong to a specific user’s preferences.

The diverse space of information looks like something infinite to users even if they already have an identity and community membership. VLE designers do not always paid much attention in creating to their users the feeling of ‘home’. In 3D immersive VLE a home can be a virtual house or an apartment in a skyscraper. In non 3D environments home can be the web page of user profile. In general, home can be a space what hosts information that other users cannot access without our permission. To make an analogy to physical life, home is a place where we have secrets. We see, use, own things and behave away from other people’s attention. We can invite friends and share this special place when we feel we trust someone. In most online social networks, when you are invited to be a friend to someone you have access to (you are allowed to know) all other friends of that person. Some users do not feel comfortable by this feature because these social processes are not stepped enough and they are not always adaptive to different cultures. Modern generations of VLEs create similar social networks, so the designers should take into account that in personal spaces (homes) users need to have the control and need to be the ones who create the rules. The same principles apply to any VLE in order to be attractive to learners.

2.3 Reinforcing personal and group identities As a conclusion to this section, when students and teachers share a common learning virtual space, strategies need to be developed to eliminate the phenomenon of empty and boring VLEs. Richardson & Turner came to conclusion that students feel less part of a learning community and among other solutions they propose the more successful use of the courserooms (Richardson and Turner, 2000). In addition to this, a courseroom can be


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successful only if participants are getting involved with their personal identities and information spaces and finally allow themselves to be part of the social context of the VLE sharing the same group identity in virtual communities.

This personal way of participation is also influenced by the attitudes users create for their own enrolment. For example, people who enter Second Life are referred to as residents, not as users, players or visitors. Residents can socially express themselves by transfering their own personalities to Second Life (Tashner, et al, 2005; Holmberg and Huvila, 2008). This is a good example of reinforcing virtual identities. Matei et al. support that virtual and real spaces are not mutually exclusive and the social life of all virtual reality environments is a hybrid artifact (Matei et al, 2007). Similarly, students get involved in traditional and virtual learning experiences using hybrid identities.

3. From Students to Participants

3.1 Online and offline life We learn from whatever we do in our everyday life. Knowledge, abilities and personal aesthetics are cultivated from our experiences (Korn-Bursztyn, 2002). In virtual environments students may engage in roles totally different than in real life. But life also has changed and includes virtual life and virtual identities too. Certain qualities of VLEs create new places which have nothing in common with physical world. One of the most interesting issues here is to study how online life is affecting offline life and vice versa. For example, the architecture of schools is perceived as a meaning to students implying that schools are important parts of our society and the school environment is a way to construct a meaning about themselves (Williams, 1998). What meanings are created from VLEs to imply that virtual learning is equally important as traditional learning? What meanings students construct about themselves living a part of their school life into virtual environments? Titman (1994) has shown that children have common reactions to specific meanings because the receive messages from the learning environment which is translated into a common cultural framework. In VLEs technology and culture are affecting each other in a primitive way.

At the beginning, pparticipants are expected to spend an important part of their time to knowing each other and trying to be self-organized in communities than spend time in actual learning activities. Also students develop managing and promoting strategies to make their user profiles famous among their communities. But why someone should spend time and effort to create his/her user profile and share identity to others if he/she is already known in a community of physical world? Personal identities and social structure are the most difficult elements to be transferred in a VLE when Blended Learning is applied. This could explain why although VLEs allow the creation of totally different social structures, finally they are based around the traditional teacher-classroom model (Weller, 2006).

3.2 User Models VLEs are basically designed for distant participants (learners & teachers) but they are not restricted to distance education (Dillenbourg, 2000). Even in cases users are not geographically separated, the rules and processes remain the same. Moreover, educational


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material is created by various and/or unknown authors and ‘the whole web ecosystem produce wikidentities’ (Mallan and Giardina, 2009). Especially in Blended Learning, the different levels of user geographical separation and the reversing roles between content consumers and content creators indicate that current user models must be re-examined. The recent history of various educational tools and the related teaching methods has shown that any new ICT-based approach is closely related to user model evolution.

A comparison between the student model used in general educational software development and participant model in VLE design can be seen in table1 as an example. The plus sign (+) in the second column indicates what should be included over and above the first column. Designers should answer questions like: ‘how official virtual learning environments (those supported by the institution) indicate their differences in comparison to other virtual environments?’, or ‘why student’s behaviour in VLE should be different than in Second Life or Facebook?’. Answering those questions is beyond the scopes of this paper, while the indication of which questions should be answered is the main contribution.

Table 1. Comparison between models of ‘student’ and ‘participant’

General student model in Educational Software

Participant model in Virtual Learning Environment

Previous knowledge and abilities +Computer driving abilities

Age +Gender

Cultural background +Personal interests and preferences

Personal learning style + Perceptions and attitudes about technology, videogames, communication

gadgets Social and family environment + Friends he/she make within the learning

environment Full time or part time student + Free time, other obligations

In-campus life Home computer availability and technical characteristics, internet connection

4. From massive downloading to personalization VLEs of the first generation were created around databases of learning material. Their primary use was the massive downloading of educational resources and most of the forum discussions were moving around technical issues regarding access difficulties, identification processes and information exchange about ‘who is teaching what’. Traditionally, students were treated as consumers of the educational material. Rules and processes forced students to follow specific behavior routes and thus VLEs were perceived as major downloaders.

Today VLEs are based on learning objects and metadata to deliver information and integrated learning services in a structured way. Students have access to multiple learning resources and under the support of the instructor they participate in content creation to make possible independent learning (Graham, 2005). VLEs are no more simple


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communication tools or major downloaders, they are ‘spaces for negotiation’ (Dillenbourg and Baker, 1996). Their design is involved with multiple institutional strategies and finally with an open educational context. But behaviour routes are still being affected by processes. For example students may have the expectation that participation ‘here and there’ is enough to reach their goals. In a similar way teachers may evaluate projects and not their students. Strict plagiarism checking (a lot of VLEs include such tools and procedures) may deviate teachers from their initial role and create insuperable emotional obstacles in relationship with their students.

There is not enough space for real personalization in content and processes as VLE designers argue. Personalization is not restricted to personal profile settings, not to user driven responses of the system based on database queries. The high degree of integration of personalization into VLE should form learning services for specific personal goals. The lack of personalization on learning services drives content creators to make assumptions based only on curricula and teachers to recall their previous experience before even meeting their students and know their needs. Most virtual courses are introductory courses in IT skills because the learning content and activities are easier to be addressed (Koskela et al, 2005).

There is also a lot of security issues arise regarding personalized learning services. At first generations of VLEs security was limited to user authentication and access rights to educational resources. Last generations have to deal with collecting information about student’s actions, profiles, social networks and uploaded projects. User’s privacy issues involve improper storage and information transfer of personal information without the learner’s consent. To protect student privacy institutions that rely part of their educational activities on VLEs must post their privacy practices.

5. Conclusions and Discussion Virtual learning communities are about sharing experiences, not just information and communication messages. Generally, we should not have over-expectations from the use of VLE. Their effectiveness is maximized when Blended Learning principles and practices are in use. But, to be perceived by participants as socializing environments VLEs need to allow participants to express their feelings, wishes, level of satisfaction or complains and apply personal rules in information management. Moreover, all those issues must be seen as personal routes in school life. Comparing the traditional learning environments and VLEs as they are used simultaneously, we can depict the following contradictory pairs in cases of poor design and bad practices of sharing the information space:

• From knowledge authority represented by the teacher we move to the information managing authority represented by the administrator.

• From the social welfare and intellectualism of schools and academic communities we move to the individual welfare and user hierarchies regarding access rights and privileges.


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• From the behavioral ethics and the construction of ideas about the world and ourselves we move to adoption of contradictory identities and the flat representation of ourselves. In other worlds from conceptualism to formalism.

• From evaluation of student effort and the formulation of personal goals we move to mechanistic file checking and the formulation of course goals.

• From living moments of social presence we move to spending time in reading past discussions in virtual spaces searching for evidence of being there.

Based on the above, VLE design and the everyday use in Blended Learning must allow participants to ‘image’ their school in a holistic way. Those mental images of the mixed school environment will affect the future use of VLE in a positive way because they will create personal memories. For example, if someone asks today students to show their school, it is much more possible that students will show the school building, than show its website. In future this may change as the physical environment and the virtual one will be more blended. Virtual identities are something more than user profiles, usernames and passwords. VLEs will be re-established as environments full of instinctive action when learners will realize the potentiality of their presence and will use it to create parts of school life history.

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On line environments to enhance entrepreneurial mindsets in young students

Allegra Mario, Fulantelli Giovanni, Gentile Manuel,

La Guardia Dario, Taibi Davide

Italian National Research Council, Institute for Educational Technology, Palermo, Italy E-mail: [email protected], [email protected], [email protected],

[email protected], [email protected]

Abstract Setting up an enterprise requires enthusiasm, creativity and perseverance, while afterwards the gradual expansion of a company calls instead for management skills like efficiency, efficacy and reliability. Since both personality and management skills are decisive factors in determining success, personal skills connected to an entrepreneurial spirit should be taught early on and cultivated up to university level, where it will be possible concentrating on the acquisition of management skills. Recently, the European Commission has revealed that most member states are involved in several ways in promoting the teaching of entrepreneurship within their own educational systems. Our research starts from the Oslo conference and agenda on "Entrepreneurship Education in Europe: Fostering Entrepreneurial Mindsets through Education and Learning", highlighting the main experiences in Europe and their outcomes regarding the promotion of entrepreneurship in education. The main research objective is to define an educational model to support students in the development both of personal qualities and attitudes and of formal knowledge and skills. The model will adopt entrepreneurial environments based on social educational games. Entrepreneurial networking is more than just collaboration since it stimulates the ability to find and create new relationships, the ability and the know how to identify the key competencies that can be useful in developing entrepreneurial mindsets.

Keywords: Management Game, Business Game, Multi-learner Online Learning Environment

1 Introduction In the last few years, some activities have been carried out to introduce and promote awareness in young people of the culture and methodologies used by global enterprises. This awareness is fundamental to allow them to develop the competencies required in an evolving labour market as it responds to the development of the ‘knowledge society’. Many young people become disenchanted with their school experience as what they learn at school is often of little relevance to their lives in the outside world and they seek to develop a different range of competences from those offered in the traditional school curriculum (Selandar 2008; Ziegler 2007; and Selwyn 2007). The main aim of our research is designing a training model to stimulate an entrepreneurial mindset in young


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people and to help them acquire the “modern skills” required by the knowledge society, based on the findings of research in this area. The training model will be run in collaboration with professional/entrepreneurial organizations rather than solely by schools, and will also make use of new ICT tools defined to create innovative and motivating learning activities. In fact, the model will include a new software platform, defined to support students in developing the necessary skills and stimulating their ability to find and create new relationships, the ability and the know how to identify the key competencies and resources that can be useful in developing their ideas.

The professional qualities which are most highly considered today are those typical of an entrepreneur, even in a context of subordinate work (Armbuster 2008). These qualities are conceptualised for this study as: motivation to achieve results and take initiative, tenacity, flexibility and creativity (based on various interpretations of the term ‘professional’ including Friedson 1994; Quinn et al 1996; Macdonald 1995; Moore 1970 and Abbott 1998). These will be achieved through the involvement of students by the setting up of the training laboratories, making use of active and motivational learning methodologies and technologies to raise young people’s level of competences. The laboratories will allow them to acquire the skills required by the knowledge society, while enabling them to take control of their learning processes and giving them the opportunity of expressing their aptitudes and potentialities to make better informed choices.

Our research starts from the analysis of key elements of successful Enterprise Education Programs in Secondary Schools in Europe and, in particular, from the projects indicated in the Oslo agenda and the following experiences in other European countries. The model we are going to define will include active learning experiences, and ICT based environments, so providing pupils with a more rewarding way of acquiring knowledge. In fact, ICT have always played a key role in managerial education, especially in the creation of simulation environments. For this reason the model will include the use of a software platform that will support students in developing the necessary skills identified to foster entrepreneurial mindsets.

Education and professional training should contribute to encouraging an entrepreneurial spirit, promoting a suitable mindset, awareness of the opportunities of following an entrepreneurial career and professional skills.

The Eurobarometer survey (European Commission 2007) indicates that 37% of Europeans would like or would have liked to follow an entrepreneurial career, but only 15% have achieved their ambition. The surveys show that being familiar with the procedures for setting up an enterprise increases the probability of becoming an entrepreneur. In the surveys carried out by Eurobarometer, the interviewees whose parents were self employed were more inclined towards self employment than those whose parents are employees. According to the GEM survey people who are confident about their skills and their experience are from two to seven times more likely to be involved in setting up or managing a new enterprise; for those who know a young entrepreneur the probability is three or four times greater. On the basis of the British Household Survey, people who have more contact with the business world (through friends, relatives or education) are more likely to consider setting up an enterprise. The educational system must help to promote an entrepreneurial spirit by providing competences and contacts.


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An important experience in this field, was carried out in Greece, at the technical school "Sivitanidios" in Athens, where virtual enterprises were used as educational tools. The students divide their time between theoretical lessons and management of a virtual enterprise. Since the results are extremely favourable the programme will be extended to all technical schools and will include a new course on entrepreneurship that will consider theoretical aspects and practical notions regarding the drawing up of business plans. Job centres then guarantee students advice and support in choosing an entrepreneurial career.

In this paper we will focus on the ICT solution identified to support the development of entrepreneurial mindsets. Firstly we will describe the general characteristics of some effective on line educational environments and in particular of role playing games. Then we will illustrate the solution identified in our research.

2 Role-playing games Role-playing games originate as a particular kind of board game, in which players act as characters of an adventure that often has a fantastic setting. Under the guidance of a game master (Dungeon Master or DM), that has the task of interpreting not player character roles, and describes for other players what they see and hear in this imaginary world (Fine, A. 1983), players have to move in a theatre of epic fights and monstrous creatures to conquer points and complete their missions.

The first one and the most known role-playing game is “Dungeon and Dragons” (D&D), published in 1974 by authors Gary Gygax e Dave Arneson, fascinated more the 20 millions players.

The world of games, the development of personal computers and of the Internet, have greatly increased the development of role-playing games, improving their expressivity and user involvement. The result has been the creation of MUD (Multi User Dungeons&Dragons, computer version of D&D) and after MMORPG (Massive Multiplayer Online Role–Playing Game), evolution of MUD with massive use of graphic and audio contents.

MMORPG belong to the category of MMOG (Massive Multi-player Online Game); one of the most famous present-day MMORPG is World of Warcraft; in its virtual environment every day millions of players interact to achieve personal or common goals and develop their own character (Papagiannidis, S. 2008).

This phenomenon didn’t go unnoticed to training sector; role-play techniques focused on the student and his learning process, originating from Moreno’s psychodrama and spontaneous theatre (Moreno, J. L. 1946), have been used as methodologies which are alternative to traditional teacher and content centered strategies. Serious games (those with educational aims) developed from this technique include simulation and role-playing environments facilitating emotive and experiential learning (such as “learning by doing”, “learning by failing” and “discovery learning”) (Kebritchi, M. 2008)”. Besides, by using simulated environments which are specifically created to achieve an educational goal, students can learn in a secure context, where their mistakes do not have damaging consequences (Dieleman H., 2006). As confirmation of the validity of this training approach, nowadays serious games are widely adopted both in the field of business training (Pannese L., 2007) and in military training (McDowell P., 2006), for the rapidity with which competences and knowledge can be acquired.


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3 Massively Multi-learner Online Learning Environment (MMOLE) An MMOLE is a multiuser environment allowing spontaneous and enjoyable learning, thanks to a serious MMOG (game with educational goals) (Foreman, J., 2007).

The social aspects of this kind of environment are extremely important; players can collaborate with other players to reach a common objective. Multiuser environments are preferable to single user ones because they can activate collaborative learning, or rather the acquisition by individuals of knowledge, skills and attitudes resulting from group interactions or individual learning as a result of a group process (Kaye A.R. 1992). The social aspect of the games is therefore one of the most important elements to stimulate since it promotes learning. Collaboration to achieve a common objective requires a clearer and more careful clarification of one’s ideas in order to share them more easily with other players; besides, confrontation with other people’s ideas produces critical reflection and advanced reasoning, leading to more meaningful and permanent learning. The opportunity to have heterogeneous groups, consisting of experts and beginners, promotes what Lave (Lave J. 1991) defines as legitimate peripheral participation. The presence of a beginner in the community of practice must be legitimized by the possibility of having a role within the group, even if the role is peripheral; his wish to become an active and central participant, will develop in a socio-cultural activity that will lead him to interact with expert members, and will allow him to move from the periphery to the center of the community of practice, in a process that enables him to become more expert in an informal way.

An MMOLE has the following characteristics: − An MMOG integrated with a Learning Management System − Communication tools − Progress tracking − Tutor supervision

LMS integration provides links to traditional e-learning course and resources to deepen game issues. Communication tools allow students to receive feedback both from other students and tutors following the game evolution. An immediate feedback helps students to reinforce desired behaviors. Tracking systems are useful to teachers to follow students’ progress. Tutors supervise learning processes, manage the starting phase, provide feedback to players and stimulate collaboration among them.

4 A new learning environment to enhance entrepreneurial mindsets Nowadays, millions people in all the world play with MMORPG (A.Meredith, 2009); Yee demonstrates that 22% of players are young students (N.Yee, 2006). Users are in continuous growth and the market is a source of great economic interest (Papagiannidis, S. 2008).

An MMOLE for entrepreneurial education can allow the so-called “virtual situated learning”; in fact, this kind of setting, where the student is immersed in a simulated environment as close as possible to the real world, promotes more rapid learning and provides the necessary confidence for putting into practice in the real world what he has learned in the virtual world (Jones, S. 2007).


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For these reasons, the use of multiuser learning environments can support the creation of motivating and attractive settings for enterprise education for young students.

Baldassin analyzed principal market management games and concluded that MMORPG’s are their natural evolution, because they overcome limitations regarding the flexibility of the model and the complexity of the business (Baldissin, N. 2007).

Considering the pedagogical and attraction potentialities of the MMORPG and considering Baldassin’s studies results, we have decided to develop an MMOLE platform based on a MMORPG to create an environment to enhance entrepreneurial mindsets in young students.

The game will be designed to manage different levels of complexity, in relation to the experience acquired by the players. Players start at a basic level in which they have a simple role, and then, as they acquire more experience, they have new resources that can be used to play at an advanced level where their role is more complex. In this way, at different times a player can occupy a variety of roles and observe and simulate different conditions.

Our solution also focuses on the creation of a networked entrepreneurial environment combining aspects of social networking with relevant aspects from the use of business games. Entrepreneurial networking is more than just collaboration since it stimulates the ability to find and create new relationships, the ability and the know how to identify the key competencies that can be useful in developing their ideas.

Entrepreneurship in education is broadly defined and includes economic, social and cultural factors. Starting from the definition: “Entrepreneurship is a dynamic and social process where individuals, alone or in collaboration, identify opportunities for innovation and act upon these by transforming ideas into practical and targeted activities, whether in a social cultural or economic context”, the educational environment, and the model in which it is integrated, must support students in the development both of personal qualities and attitudes and of formal knowledge and skills. These two main elements will give pupils/students competence in entrepreneurship:

- Personal qualities and attitudes increase the probability of a person seeing opportunities and acting on them,

- Knowledge and skills concerning what must be done to establish a new enterprise, and how to be successful in developing an idea into a practical, goal-oriented enterprise.

The MMORPG we are going to develop will be centered on operative enterprise phases (supplying, production, sale, human resource management), but with a strong orientation on the market. It will not be a zero-sum game, that is to say that the winning of a player does not necessary corresponds to the other’s defeat; on the contrary, many activities of the game will be studied to promote cooperation among players to reach a common goal.

From a technical point of view we chose to develop a browser game MMORPG; in fact, browser games provide a compromise between complexity of the development (there are a great number of framework for the optimization of web based application development) and pedagogical potentialities. Today’s browsers have the necessary


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features to carry audio, video and textual contents that, according to Roden (Roden, S. 1991), if opportunely combined increase of the 30% the learning speed of the student.

Another important aspect, comparing our environment to other business games, is that it is not only a simulation game but an on line world. In a simulation game only one person is interacting with the software at a time; instead, in an on line world the user has to interact and cooperate with other users, to improve their business, to make decisions, to reach objectives that they cannot reach alone. The learners are inside a simulated environment, interacting both with the software and other users; so their activities can have effect both on their own enterprise and on the others.

The browser game we are going to develop will include some non-player characters (NPC), designed to perform some tasks guiding students to understand some important mechanisms of the market. For example, if there is an NPC creating obstacles to the development of a company, the owner has to understand the best strategy to defeat it, learning how to protect his/her business from that kind of problems. Besides, NPCs will allow the simulation of important actors of the market. NPC are also useful tools for instructors to facilitate learning events and activate/manage some interactions within the environment.

It is important to notice that the learning environment we are going to develop will be a game in which students will play autonomously, improving their skills and knowledge. But in some phases or situations, instructors can activate managed learning events to bring students to reflect on particular aspects, making the game more effective for learing.

5 Conclusion and future work Educational MMORPG are now beginning to emerge. In particular, games based on browser MMORPG can allow the development of on line educational environments reducing the cost of production, respect to the first experiences with this kind of games. Considering that nowadays million of people in all the world play with MMORPG and an increasing percentage of them are young students, we think that these environments can have great prospective for learning purposes, especially in some contexts where the simulation of the real world and the interactions with other subjects are crucial. For these reasons we have thought to develop a new model for enterprise education, based on a browser MMORPG, for young students, to make them acquire entrepreneurial mindsets.

Although we will develop a simplified model of the environment in which enterprises work, it will be able to provide students the chance to:

− Learn, through learning by doing and learning by failing methodologies, dynamics in an open market and the main factors influencing the start-up and the success of an enterprise

− Learn cooperative work with other players, to reach common aims − Develop inductive reasoning attitudes (what-if analysis), analysis, planning

and verifying capability and problem solving. It is important to highlight that the new learning environment probably will be able to

involve students in the first phase and, if it is well structured and attractive, also in the


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following levels of the game; the integration of the game in very well known social networks will be another way of attracting and engaging young students. But to be an effective learning environment it is crucial in the design phase to create the right “rules” to interact in the virtual community, guiding students trough the key factors of the complex world of the market. However, to make students acquire entrepreneurial mindsets it will be important to involve them in all the activities of the educational model we are designing with educational institutions and associations of enterprises.

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Baldissin, N. and De Toni, A. F. and Nonino, F. (2007): Evolution of the Management Games: Towards the

Massive Multiplayer Online Role Playing Games?. International Conference Learning with Games, Sophia Antipolis (France), 24-26 September 2007.

Dieleman, H. and Huisingh, D. (2006): Games by which to learn and teach about sustainable development: exploring the relevance of games and experiential learning for sustainability. Journal of Cleaner Production 14, 9-11, 837-847.

European Commission (2007): Flash Eurobarometer N.192. Entrepreneurship Survey of the EU (25 Member States), United States, Iceland and Norway, The Gallup Organization Hungary/Europe

Fine, G. A. (1983): Shared Fantasy. Role-Playing Game as Social Worlds. The University of Chicago Press, Chicago.

Foreman, J., & Borkman, T. (2007): Learning Sociology in a Massively Multistudent Online Learning Environment. In D. Gibson, C. Aldrich, & M. Prensky (Eds.), Games and Simulations in Online Learning: Research and Development Frameworks. (pp. 49-58). Hershey, PA: Information Science Publishing.

Jones, S. (2007). Adding value to online role-plays: Virtual situated learning environments. ICT: Providing choices for learners and learning, Proceedings Ascilite Singapore, 2-5 December 2007.

Kaye, A.R. (1992): Collaborative learning through computer conferencing: the Najaden papers. Springer-Verlag.

Kebritchi, M. and Hirumi A. (2008): Examining the pedagogical foundations of modern educational computer games. Computers & Education, 51, 4, 1729-1743.

Lave J. and Wenger E. (1991): Situated Learning: Legitimate Peripheral Participation. New York: Cambridge University Press.

McDowell, P. and Darken, R. and Sullivan, J. and Johnson, E. (2006): A Complete Open Source Game and Simulation Engine for Building Military Training Systems. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 3, 143-154.

Meredith, A. and Hussain, Z. and Griffiths M. D. (2009): Online gaming: a scoping study of massive multi-player online role playing games. Electronic Commerce Research, 9, 1-2, 3-26.

Moreno, J. L. (1946): Psychodrama. Vol I. Beacon House, New York (tr. It.: Manuale di psicodramma. Il teatro come terapia, Astrolabio-Ubaldini Ed., Roma, 1985).

Pannese, L. and Carlesi, M. and Riente, L. (2007): Mettersi in gioco: Serious Games e apprendimento esperenziale per la fomazione in azienda. In Marconato G. (Ed): Le tecnologie nella didattica, Erickson.

Papagiannidis, S. and Bourlakis, M. and Li F. (2008): Making real money in virtual worlds: MMORPGs and emerging business opportunities, challenges and ethical implications in metaverses. Technological Forecasting & Social Change 75, 5, 610-622.

Roden, S. (1991):Multimedia: the future of training. Ultimedia Digest, 1, 1991-92,78–81. Yee, N. (2006): The demographics, motivations and derived experiences of users of massivelymultiuser

online graphical environments. PRESENCE: Teleoperators and Virtual Environments, 15, 309–329.

Future of Virtual Learning Methods and User Expectations – Can Present Methods Flourish Without Change?

Indika Perera

Department of Computer Science & Engineering,

University of Moratuwa, SRI LANKA E-mail: [email protected]

Abstract The ever changing Information and Communication Technologies (ICT) add enormous approaches of utilizing computing in to our lives, daily. Every aspect of social needs have been touched with ICT, including Virtual Learning (VL). VL, with life span of slightly above a decade, still looks for possible approaches to enhance its functions with significant pressure from related disciplines for continual improvements. Very recently with the introduction of Web 2.0, Semantic Web, and 3-Dimensional Virtual Environments users expand their horizons of expectations. Along with this technology advancement, there has been a noticeable social and demographic transformation from recent years. Sociologist, refer these as new generations of human kind with high intellect, Multitasking nature, and high awareness of their environments. At the moment they are getting into the education stream with high eager for creativity, flexibility and entertainment. Most of present primary and secondary students show such characteristics and advance their expectations frequently. On the other hand VL still not accommodating new social networking and entertainment approaches as it confined to limitations from traditional learning pedagogies and administrative rules. So far only successful step it could step forward is the blended learning which now fading its novelty. The simple yet foremost essential question is, how far could we retain our students willingly with present Virtual Learning methods? Or will it becomes another unimpressive rigid approach of learning to our future generations. This paper discusses possible approaches to evolve Virtual Learning Methods and Models to make the future learning enjoyable yet comprehensive task.

Keywords: Virtual Learning Methods, Learning Preferences, Generation Y and Z, Social Networking, Learning Strategy Development

1 Introduction Education is considered as a fundamental necessity for any human being. Most of the developed societies consider it as the main qualification for being competitive among the others. As a result, enormous efforts have been made, throughout our civilizations for enhancing the education processes. ICT has shown a remarkable potential for making educational activities more effective and efficient, when used along with educational pedagogies. ICT affects many systematic disciplines to alter and revise their traditional workflows to improve their productivity. Hence the e-Learning is a growing area where


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many universities are focused on to gain the maximum benefits through ICT. During past decades, there were significant works to improve the related technology (Perera, 2009). It is not only the e-Learning that made things better, but many believe blended approach would produce even better results. The term blended learning is used to describe a learning situation that combines several delivery methods with the goal of providing the most efficient and effective instruction experience by such combination (Williams, 2003). Many Higher-Education institutions have adopted the use of virtual learning environments and incorporate e-learning into their traditional teaching mechanisms as part of a blended-learning approach (Evans, 2008). Blended learning combines multiple delivery media that are designed to complement each other and promote learning behaviour (Singh, 2003). In fact blended learning tries to provide a common platform for traditional learning aspects with possible combinations from virtual learning technologies. “Potential for a greater learner autonomy where learners are more empowered through control of tools and content development” (Field, 2007), can be seen with advanced technological development, especially ICT related. So far the blended learning tried to mix traditional aspects of learning with technology, but missing this vital concept of learner autonomy. In fact the technological advancement is so rapid and it moves further deviating from the learning approaches that we use today, making a more autonomous and creative person. It is now indeed the time for the requirement of another paradigm shift for learning activities to bridge the gap between our learning methods and today’s technology offerings. Essentially, it is meaningless to focus on situational aspects from time to time and find many different solutions as we could never able to develop sustainable learning methods. “To effectively accommodate, support, and promote the knowledge production process, instructors need to select appropriate learning models and strategies” (Dabbagh, 2007). Therefore, the main motivation of this paper is to introduce strategic guidance for future planning for learning approach improvements irrespective of technological changes time to time, while offering education to new generations meeting their behavioural preferences. This paper is organized as follows. The section 2 discusses the present problem with virtual learning from the view of socio-behavioural concerns. Then in the section 3, the paper introduces a strategic model for analyze learning methods and their strategic positions respect to key aspects of today’s virtual learning. Section 4 gives a brief summary of possible technologies to move forward with virtual learning improvements, where as the section 5 discuss the issues we are going to encounter with these learning enhancements. Thereafter, the Conclusion summarizes the possible policy implications and finally the references will complete the paper.

2 Problem Due to the increasingly diverse population, education is changing toward a more global, technology-rich environment designed to meet these diverse and changing needs of students (Gunter, 2007). As a result, many isolated researchers try different methods for incorporating new technological methods as they are, without following a proper


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behavioural analysis on student preferences and technological suitability. In general any system approach needs to convince its users through different methodologies with sufficient amount of customizations to achieve the adaptability of the system. Adaptability is one of the important factors which help to yield the acceptance of an e-learning system. The issues of how to support adaptability in learning systems, and provide students with personalized learning materials, can be partially solved by providing student-centred, self-paced, interactive learning materials along with introducing automatic and dynamically adaptive learning methods (Sun, 2005). Recent studies have shown that “the successful implementation of educational technologies depends largely on the attitudes of educators, who eventually determine how they are used” (Albarini, 2006). This is another important issue as educators are going to use the available new technologies with their preferred way, but student expect it differently. This is where the socio-behavioural input is needed to train educators to work with digitally oriented new generations.

2.1 New Generations’ Learning Tastes Demographic and Socio-Behavioural analyses show, three major generation groups at present; namely Generation X, Generation Y and Generation Z (still at the definition level). In present context Generation X refers to people with age around and above 30 years born up to 1980. They expect more self esteem and flexibility of what they do in the same time with less technology preference. Most of present learning methods are focused with this group and pedagogical confinements aligned with their requirements. Generation Y, usually defined as those between the ages of 11 and 25 or up to 30 at present context. They care less about salaries, and more about flexible working, time to travel and a better work-life balance. And employers have to meet their demands (Asthana, 2008). Generation Y is described as self-confident, self-reliant, independent, and goal oriented ... Perhaps the generation may put a bigger premium on having fun, and is more relaxed and able to take uncertainty in stride. They are special, sheltered, confident, team-oriented, achieving, pressured, and conventional (McIntosh-Elkins, 2007). Generation Y members have used computers since a young age and are e-learners (Allerton, 2001). They live to be trained, enjoy the challenge of new opportunities, seek work-life balance and like to be involved in decision making (Allerton, 2001). Present high school and university students are in this category and show different interests than what they have been offered in learning. Generation Z, are the present youngest generation of human race who born after the internet information and communication became the mainstream of our lives, i.e. after mid 90’s. There are not much behavioural characteristics clearly identified with this generation, as they are still around 12 – 13 years of age at most and many of them are in the present primary education system. Palfrey & Gasser (2008, p.41) define this generation as digitally born humans. They have digital identities from their birth, and every activity of their lives, digitally related and will have heaps of digital records of their life as grow. What we can anticipate is that they will be more autonomic, entertaining themselves and create their own environment irrespective of what happens around them and less tolerable with rigid, routinely, stereotypic activities.


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Both Y and Z generations are more extraverts with highly connected to social networks. Extraversion refers to high activity, assertiveness, and a tendency towards social behaviour (Furnham et al., 2007). Individuals high in extraversion enjoy human interactions and take pleasure in activities that involve large social gatherings. Indeed, work-life balance is one of the top priorities of students (Comeau-Kirschner and Wah, 1999). Proserpio and Gioia (2007) argued that we will no longer teaching a verbal, or even just a visual, but a virtual generation of students with digitally oriented mindsets. The clear differences between Generation X with Y and Z indicate it is highly essential to alter present learning methods to accommodate new generations’ requirements.

2.2 Impact of Transitional Learning Activities Whenever there is a new and affordable technology available, we tend to apply it for our education system thinking that we could solve infrastructure and social issues affecting education through that. However, we never foresee, what is the technological situation in learning context as well as in near future. We could observe this situation with most of the learning development activities as educators trying to introduce dozens of new teaching approaches with different technological infrastructure to overcome learning difficulties. This make students to confuse on technologies they use and ironically always the technology they are using to learn lags with what available for them in the society. This makes those students to lack their interest on the technologies used for teaching. Unfortunately, with resource constraints, teachers could not afford the latest technology either. But if we carefully examine, we could produce similar results to latest technological approaches, using what we have, in most cases. For that we need to examine student’s preferences without confining ourselves to rigid learning processes. Having discussed the main problem area for this analysis, the next sections try to provide a strategic solution with potential technical approaches for implementation.

3 Proposed Model for Analysis It is really difficult to foresee the learner requirement in a situational manner, without a strategic drive for analyzing. Trying to tailor-made learning methods as new technologies emerge only give temporarily solutions and could be more probable to affect learners negatively. As we saw in above, without considering appropriate factors with suitable combinations, we would not able to get optimum learning methods to entertain students with new technologies. The model which is proposed here correlates the three prime aspects of virtual learning. Most of the scholars have acknowledged the pedagogical aspects and technological aspects, but not the socio-behavioural aspects. Here the model introduces the socio-behavioural as a new paradigm to the learning methods analysis. Some may think that this aspect was already there with the learning activities. Even if it was the case it never used for thorough analysis at policy level. With this model, we could analyse many possible outcomes when different aspects gets dominating, allowing us to design our learning methods more appropriately and consistently, without getting affected from frequent technological changes or pedagogical constraints.


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The model shown in the figure 1 below is the abstract view of how these three aspects combine each other for a future virtual learning environment. According to the proposed model, more overlapping of aspects altogether, gives ideal virtual learning environments. If the combinations are not balanced with all aspects, prominent aspects will make the learning activities less effective.

Figure 1: Conceptual model to analyze learning process improvements

3.1 Areas to Avoid There are three sub areas according to the model shown as 1, 2, and 3 indicating possible problem areas. For the best results in future learning methods we have to avoid these situations and try to make them acceptable to all aspects. Overlapping Area 1 - This indicates the combination of Pedagogical Aspects with Socio-Behavioural Preferences, but no consideration with available advanced technologies for improving learning methods. The course environments may somewhat attractive to students and meet pedagogical requirements, but not operating productively due to the overhead learning processes without technological support. Overlapping Area 2 - This area represents the combination of Pedagogical Aspects with Advanced Technological solutions, but no consideration for making the learning process attractive to the audience. In fact, today’s typical virtual learning environments have high vulnerability to fall into this category, and in future things would be worsen with new generation’s preferences. Unfortunately, today what we are doing is, trying to make virtual learning align with pedagogical constraints and including blended aspects to widen the virtual learning scope, without taking into account on how students perceive our methods. Overlapping Area 3 – This indicates the combination of Advanced Technologies and student preferences, without the Pedagogical Aspects of learning. Most of the latest pervasive and social networking solutions come under this category. We cannot use them as it is since they do not provide any formal learning methods.


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4 Possible Solutions The greater ubiquity of open standards-based e-tools and services is prompting a range of integrated and collaborative tools and functionality (de Freitas and Neumann, 2009). Indeed these tools provide good platforms to link both pedagogical aspects with user preferences. Social networking solutions are very popular at the moment with younger generation. Facebook, MySpace, Twitter, and many similar social networking solutions have penetrated into students’ lives, where most of them spent reasonable time with their preferred systems. Not only that, but also students use these as informal methods to share their opinions, plan group activities, participate in virtual events, sharing contents, etc. Edirisingha and Salmon (2007) found that pod-casts contributed to informality and engagement. Pod-casting can also make learning more appealing to a diversity of learners and can generate greater inclusive nature (Cebeci and Tekdal, 2006). Rich media content through pod-casting and mobile sharing is another possible solution to make learning activities more attractive to users while making their learning more autonomous. 3-D virtual learning environments are another possibility to incorporate game flavour with learning activities. The "digital classroom” provided by 2D tools does not resemble the reality of the conventional classroom (de Lucia et al. 2009). There are many successful implementations of 3-D virtual learning environments available from universities and trend will move to the school education in near future. Finally, moving further Mixed Realities would generate extraordinary results with combining all possible virtual and real technologies for comprehensive learning. “Mixed Reality is a new technology to edutainment, with potential to revolutionise learning and teaching with more engagement” (Liu et al., 2007). However, we also have to consider the relative cost of introducing new technologies to the learning arena for better results. Any Technology that students are widely using already for their entertainment would be a great option.

5 Issues to Overcome Introducing, social networking, user generated content and heterogeneous technologies, results dozens of issues to emerge with present learning methods, indeed it would make the most of educators worry too. Some of the most prominent potential issues and possible remedial actions are discussed briefly, here. “Many studies have specifically examined how an instructor’s feedback impacted on student–student interactions and satisfaction and Wize and others have found that a moderated online discussion community by an instructor can elicit greater participation among students than an un-moderated one” (Heejung et al., 2009). As the educational activities should be formal in nature, it may be not possible to use new entertaining technologies without moderation. For an example, the way social networking forum postings (language, spellings, short words, abusive words etc.) made by students among their friends may not suitable for proper learning. A moderator must be present to ensure appropriate learning mix with formal learning.


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“In education, there is a growing concern with the Internet triggered dishonesty sparked by the massive use of the Internet” (Akbulut et al., 2008). The Internet can facilitate many kinds of unethical behaviours such as plagiarism, piracy, fraudulence, falsification, misuse, etc. (Ross, 2005). With the social networking and rich content sharing methods, students could easily alter available content and claim the ownership for assessments. Also, it would be really difficult to access control on student activities to ensure proper assessment based learning activities. Future research is essential to implement technological solutions to overcome these issues. Yet again, it is the educator who governs the methods and models used in learning process, and therefore they have to be convinced with the new approaches. They have to be trained and provided with sufficient guidance on how to work with new generational students and new technologies. There are one or two generational gaps with present educators and students, making the delivery of education happen according to the educators’ mindsets even the methods accommodate all aspects in balanced nature. Therefore, to achieve, effective results from these improvements, present academia must be openly convinced on the benefits of changes.

6 Conclusion This paper has very briefly, yet comprehensively, rationalized the problems that existing virtual learning methods and models, would experience in near future with new student generations, if they do not accommodate necessary improvements. Since the situational approaches for analysing these issues would not yield sustainable solutions, paper has introduced a strategic model to analyze virtual learning methods with prime aspects and their combinations. The technologies and potential issues discussed here would only guide the pathway, but essentially need further research on possible avenues of improvements with suitable technical customization. There are enormous untapped potential researches relating to future learning methods improvements. Unfortunately, so far researches focusing more on isolated technical approaches without considering the broad spectrum to provide sustainable solutions to next generations. Whether we evolve the present learning methods or not would decide their acceptance from future students.

REFERENCES

Albarini A., (2006), Cultural perceptions: The missing element in the implementation of ICT in developing

countries, International Journal of Education and Development using ICT , 2(1):49–65 Akbulut Y., Sendag S., Birinci G., Kilicer K., Sahin M.C. and Odabasi H.F., (2008) Exploring the types and

reasons of Internet-triggered academic dishonesty among Turkish undergraduate students: Development of Internet-Triggered Academic Dishonesty Scale (ITADS), Computers & Education 51(1):463–473.

Allerton, H.E. (2001), Generation why, Training & Development, 55(11):56-60 Asthana A. (2008), They don't live for work...they work to live, Generation Y, The Guardian, 25th May 2008,

[accessed on 02.06.2008] [available at] http://www.guardian.co.uk/money/2008/ may/25/workandcareers.worklifebalance,

Cebeci, Z. and Tekdal, M. (2006) Using Pod casts as Audio Learning Objects, Interdisciplinary Journal of Knowledge and Learning Objects, 2: 7-57


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Comeau-Kirschner, C., & Wah, L. (1999) Holistic management. Management Review, 88(11):26-32. Dabbagh N., (2007), The online learner: Characteristics and pedagogical implications, Contemporary Issues

in Technology and Teacher Education 7(3), online [available at] http://www.citejournal.org/vol7/iss3/general/article1.cfm

de Freitas S., Neumann T., (2009), The use of ‘exploratory learning’ for supporting immersive learning in virtual environments Computers & Education 52(2), 343-352

De Lucia A., Francese R., Passero I., Tortora G. (2009), Development and evaluation of a virtual campus on Second Life: The case of SecondDMI, Computers & Education, 52(1):220–233

Edirisingha, P., & Salmon, G. (2007) Pedagogical models for pod-casts in higher education [online] [available at] http://hdl.handle.net/2381/405 [Accessed 14.05.2009]

Evans C. (2008), The effectiveness of m-learning in the form of pod-cast revision lectures in higher education, Computers & Education, 50(2):491-498

Field J., (2007), Looking outwards, not inwards, ELT Journal 61(1):30–38 Furnham A., Dissou G., Sloan P. and Chamorro-Premuzic T., (2007) Personality and intelligence in business

people: A Study of two personalities and two intelligence measures, Journal of Business Psychology, (22): 99–109.

Gunter G. A., (2007), The Effects of the Impact of Instructional Immediacy on Cognition and Learning in Online Classes, International Journal of Social Science, 2(3):196-202

Heejung A., Shin S., Lim K., (2009), The effects of different instructor facilitation approaches on students’ interactions during asynchronous online discussions, Computers & Education, 53(3):749-760

Liu, W., Cheok, A. D., Mei-Ling, C. L., Theng, Y., (2007), Mixed reality classroom: learning from entertainment. In Proc. of the 2nd international Conference on Digital interactive Media in Entertainment and Arts, DIMEA '07, ACM, 274:65-72

McIntosh-Elkins, J., McRitchie, K., and Scoones, M. (2007), From the silent generation to generation x, y and z: strategies for managing the generation mix, In Proc. of the 35th Annual ACM SIGUCCS Conference on User Services, SIGUCCS '07. ACM, New York, NY, 240-246.

Palfrey J., Gasser U. (2008), Born Digital: Understanding the First Generation of Digital Natives, Basic Books, Perseus, New York, p.41

Perera G.I.U.S. (2009), “Key Success Factors for e-Learning Acceptability: A Case Based Analysis on Blended Learning End-User Experience”, In Proc. of IEEE International Advance Computing Conference, IACC’09, 2379-2384

Proserpio L., Gioia D., (2007), Teaching the virtual generation, Academy of Management Learning and Education, 6(1): 69–80

Ross K., (2005), Academic dishonesty and the Internet, Communications of the ACM, 48(10), 29–31 Singh H., (2003) Building Effective Blended Learning Programs. Educational Technology November-

December, 43(6): 51-54 Sun S., Mike J., Griffiths N., (2005) To Support Adaptivity in Agent-Based Learning Systems – The Use of

Learning Objects and Learning Style, 5th IEEE International Conference on Advanced Learning Technologies (ICALT’05)

Williams S., (2003) Clerical medical feeds back on blended learning, Industrial and Commercial Training, 35(1): 22–25

Learn of the Network Concepts Using Project Based Learning

Costel Aldea, Ion Florea

University Transilvania of Brasov 50, Iuliu Maniu, Brasov, 500091, ROMANIA

[email protected] [email protected]

Abstract The paper presents an application used by the students in the learning of networks communication and configuration functions. Based on the idea that only by interrogating and displaying of the network properties the student does not perceive the basics of networks and due to the fact that the number of possibilities in networks are large a skeleton project is proposed where the student contribute to a team implementation of a network resource management project and better understand basic principles of networking. Such that using project based learning aspects the student are further developing the skeleton project as a team. Keywords: Computer Networks, Project based learning, network

1 Introduction E-learning contains modern methods and technics based on information tachnology components like: multimedia, synchron and asynchron communication (Sangeorzan, 2003). All this components help user to obtain new knowledges in different domains.

Through the rapid access to the knowledges the educational software is an alternative to the classical learning methods. In a simple approach, the educational software divides in:

- Simple interactive presentations and tools which are making more efficient and attractive the teaching of the same knowledge that can be told in the classic mode too;

- Computer simulators which are reproducing a bounce of real process from all the domains, including those related to computer networks. These simulators offer the user the possibility to simulate critical processes and to better understand their business logic without producing any damage to the real system; in this class are also included certain themes about the administration of a computer network, when the students don’t have the administration rights (Florea, 2003; Aldea, 2006).

In (Florea, 2003) is presented the simulation of some basic network administration operations, such the the installing of the network operating system, Microsoft Windows Xp, the IP adress alocation, the administration of account settings.

The XP firewall is a simple application which doesn’t contain a tremendous menu with options for its own configuration. The user can only filter the ports, addresses and to establish the status for the log operations.


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In the current paper a skeleton project is proposed where the student contribute to a team implementation of a network resource management project and better understand basic principles of networking.

It has to mention that the skeleton project is written in the programing language C#. The project offers samples of some basic API’s and the users must extend the

functionalities. For example in the proposesd verison are implemented function for managing user and groups with a minimal number of parametrs and the user should further extend the implementation to establish the propertie for the new created user (for example it must set the logon script). The user can also see the functionalities offered by the operating system itself by accessing the administrative tools components which are started directly from the menu of the program.

2 Network Resource Management Project (NRMan) In this section is presented the project on which the students collaborate to learn network aspects. The students have to deal with knowledge’s about devices, computers, and protocols, programming in networks and team working to solve network problems. So that the learners have to understands concepts and principles related to networks (Florea, 2004). 2.1 User requirements It is required to implement/extend an application for network resource management. Using the application one has the following possibilities:

- list local services; - star/stop local services; - list open port for a workstation; - read the networked station; - list the remote processes; - ping any station; - manage local users and groups; - manage network user and groups; - resolve hosts (using DNS queries); - see installed software; - save the list with the installed software in xml files; - compare lists with installed software; - remotely install software; - remotely upgrade software; - trace route to other hosts – see the route for the packets form current station to a

destination work station, etc. While the project is a learning project the students have to specify other functionalities

for the project and to collaborate to implement the new proposed requirements

2.2 Implementation The project is implemented using C#. The user has to add new menu items with new functionalities or has to extend the existing functionalities. Some of the implemented functionalities are presented in the figure 1 and figure 2.


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Figure 1. Application main menu In the figure 1 it can see the application main menu. By using the main menu the user has access to the most of the implemented operations. Some important operations are those from the menu Operatii – using this operation the user start external processes and use external tools like: remote desktop connection, TCP Viewer, Windows user manager, Windows server manager, etc. In the figure 2 are presented possible operations after selecting a workstation. As shown in the figure the user can do the following: see details about the work station, see running services, installed network interfaces, TCP connections, ping other station or the selected station, see the open ports, user account and groups, see the operating system version and see Win32 API functions parameters. While important functionalities are based on the Win32 API’s the application offers a list with their parameter so that the user can consult them when it wants to add a new functionality to the project which is based on the API function call. 2.3 Project structure The project is organized using the methodology and the schema proposed by the Visual Studio IDE (figure 3).

One can see in the figure 3 that the user can easily add new function in the project and also extend the existing ones.

In the logic directory of the project is implemented the logic of the application. It contains the classes that are doing the network operation.

The view classes (the forms) are in the main directory of the projects.

Figure 2. Workstation operations


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Figure 3. NRMan structure

So that when a user implement a new functionality it adds the API calls and his implementation in a class in the directory login and then it adds also a view class to present graphically his implemented functionalities. It can also add new resources to the project like images or external tools. The external tools are stored in the directory other. While the project is collaborative the developer must respect some minimal editing rules which are already used in the other classes of the implemented solutions. While in the .NET framework only some of the network API functions are defined in the namespaces, the user can use the network API calls like in the figure 4 to add different network functionalities.

To have the possibility to make the detection of vulnerabilities it has to save images with different lists (processes, connection, applications, etc). These lists can be saved in XML format or can be saved in database for further compares.

Figure 4. Network API call 2.4 Application functioning The user can run other tools or system tools to interrogate the workstation status and then can compare the results with the NRMan results. For example in the figure 5 are presented the local user accounts and some information about account, on the station INSTITUTBV, obtained using the NRMan functionalities.


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Figure 5. NRMan Workstation user accounts

The common implementation and work to the project build the community of students around the network principles and issues. Team work allows the integration into the project of different point of view and modes of understating of concept. Any user has access to the information put by the other student. Also the students can concurrently work in developing of bigger functionalities.

3 Project based learning A project based learning method is a comprehensive approach to instruction. The students participate in projects and practice an array of skills from basic concepts, protocols, programming primitives and devices. The collaborative nature of the investigation enhances the student’s implication. The Project Based Learning techniques imply in this situation that a skeleton project for administering the network was created. The skeleton covers a bounce of operations,


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administration issues, commands, etc. The user which has basic knowledge’s cannot conceive such a project with all the interrelations between the task and operations. So that the project permits to the student to acquire knowledge’s about the whole administrated network not only one specific operation. The students collaborate to solve the tasks. The interaction with other people which have other type of knowledge’s give the student to possibility to express itself and to discuss and better understand the studied aspects. One of the main teacher concerns is to equilibrate the assignments and to make clear and general accepted difference between given and proposed functionalities of the implemented application (NRMan) so that the grade system keeps his characteristics.

4 Conclusion Using the project based learning principles the teacher is able to incorporate numerous teaching and learning strategies into project planning and implementation. By offering the students the possibility to develop their own assignment and to write their own tasks, they are deeply implied in the learning process. The students are part of the teaching process and they don’t feel that the tasks are external task while they are included into the process.

Between other advantages is also the fact that the written code in reviewed by other coders implied directly in the project so that the students functionalities must have a high quality level to satisfy all the implied members into the project.

REFERENCES

L. Sangeorzan, C. Aldea (2003): Tehnologii Internet, University Transilvania Publishing House, Braşov. Florea I. (2004): ReŃele de calculatoare - concepte fundamentale, University Transilvania Publishing House,

Braşov. C. Aldea, Bobancu A. (2006): IT Security Tutorial with Animated Examples, Proceedings of the

International Conference on Virtual Learning - ICVL2006, ISBN 973737218-2, Bucuresti, 275-282. Florea I., Aldea C. (2003): Soft multimedia pentru pregătirea materialelor de curs, Proceedings of the

“ConferinŃa NaŃională de ÎnvăŃământ Virtual”, EdiŃia I, Universitatea din Bucureşti, Facultatea de Matematică, 189-196.

http://www.4teachers.org/: Project Based Learning and evaluation (2009)

Computational Physics with Python

Rubin H. Landau1, Cristian C. Bordeianu2* , Manuel J. Paez3

Oregon State University, Physics Department, Corvallis, OR 97331, USA

University of Bucharest, Faculty of Physics, Bucharest-Măgurele, P.O. Box MG 11, 077125, Romania

University of Antioquia, Medellin, Colombia *E-mail: [email protected]

Abstract A coherent set of material for upper-division university education in computational physics/science has been developed at Oregon State University, USA. It contains an introductory course in scientific computing, a course in Computational Physics, and a coordinated collection of multimedia interactive animations which enhance the book and the courses. Computational Physics programs using Python programming language are presented and displayed. It is proposed that presentation using Python is a more effective and efficient way to teach physics than the traditional one.

1 The Need for Computational Education We start by looking at the results of a survey of physics bachelors conducted by the American Institute of Physics that determined which aspects of their education are most valuable in their current employment five years after graduation (AIP, 1995). The results, shown in Figure 1, indicate that for graduates whose primary field of employment is engineering, mathematics and science, the three most important skills are scientific problem solving, synthesizing information, and mathematical skills. These skills are also highly important for graduates who find employment related to software. While it is to be expected that knowledge of software and programming are most important for graduates in software development, notice how, otherwise, synthesizing information is the most important skill for both groups, and that knowledge of physics is essentially the least important.

2 Framework for Teaching Physics with Computation Figure 2 illustrates the scientific problem - solving paradigm that is at the core of computational research. Although such diagrams have been shown often enough to become visual clichés, they remain relevant to the focus of this paper since they provide the general structure for computational education. In fact, we believe that the commonality of tools across the computational sciences combined with the common problem-solving mindset is a truly liberating and attractive aspect of computational science because it permits its practitioners to understand and participate in a much wider set of problems than occurs otherwise in the sub specialization of science.


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Figure 1. Importance of knowledge areas for physics bachelors 5 - 7 years after graduation.

In general, we recommend that computational educational materials be structured

around the scientific problem-solving paradigm in Figure 2. This demonstrates where the multiples disciplines are relevant, provides concrete examples that assist in understanding the abstract concepts, and stresses the importance of assessment of the various components through visualization. From a pedagogical perspective, we believe that a Computational Physics education following the problem-solving paradigm is a more efficient approach to undergraduate education than a pure Physics education. Although students may take fewer Physics classes, they tend to learn Physics, Computer Science, and math better when placed in context, and thus get more out of their courses. So even if the number of Physics courses needs to be reduced to make room for teaching computation, this is compensated for by the increased efficiency of the pedagogy. Furthermore, this approach has been shown to be appealing to a more diverse group than those presently attracted to computer science or physics.

The materials and classes we’ve built along the way reflect our own rules of education, which are personal observations gleaned from decades of teaching:

• Most of education is learning what the words mean; the concepts are usually simple if only you can understand what is being said.

• Confusion is the first step to understanding. • Traumatic experiences tend to be educational. • Scholarly and pedagogical presentations are often designed to either impress the

audience with the presenter’s brilliance and depth or to make the materials appear simple and logical (we opt for the latter).


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Figure 2. The scientific problem-solving paradigm. A problem is set, the tools from

multiple disciplines are employed within context, and

the continual assessment aides debugging and steering.

A key component of many computational programs is having students get actively

engaged with projects as if each were an original scientific investigation, and having projects in a large number of areas. In this way students experience the excitement of their personal research, get familiar with a large number of approaches, acquire confidence in making a complex system work for them, and continually build upon their accomplishments. We have found the project approach to be flexible and to encourage students to take pride in their work and their creativity. It also works well for independent study or distant learning. In order to teach a Projects-based course, we employ a combination of lectures and “over the shoulder” labs. The students work on and discuss their projects with an instructor, and then write them up as an “executive summary” containing sections for

• Problem • Algorithm • Visualization• Equations employed • Code • Discussion & Critique

The emphasis is professional, much like reporting to manager in a workplace. Visualizations are important for all the classes, and we teach the use of Maple/ Mathematica, PtPlot, gnuplot, AceGr, and OpenDX (Figure 3) for 2D, 3D, and animated plots. Taken together, this approach produces significant learning, even though we may be “teaching with our mouths shut''. Also we teach modern digital signal processing techniques as wavelet analyses (Bordeianu, 2009).

Figure 3. Example visualizations produced with

OpenDX. (a) The 3D state of hydrogen, (b)

an equipotential surface for a toroidal

capacitor with the resulting electric field,

and (c) the visual program that produced the

hydrogen visualization.


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3 What to teach In Figure 4 we present a concept map for our Computational Physics course and text (Landau et al, 2008). After two years in administrative processing, in October 2001 the Oregon State Board of Higher Education approved a Bachelor degree in Computational Physics (Landau, 2004). The first students entered in fall 2002, the first graduate left in June 2003, and 3-5 students typically graduate each year. Although these numbers are small, the classes are well attended by physics majors, graduate students, and engineering students. A sample of the Computational Physics curriculum is given in Table 1. It is an example of how a complete package of computation classes can be fit into a four-year curriculum that is still strong in its mother discipline.

Table 1. A sample Computational Physics for Undergraduates (CPUG) curriculum This curriculum has been built up course by course since 1989 as we proposed,

developed, taught, and modified new courses. The computer classes (bold) are seen to be


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distributed throughout all years of study. In total, the curriculum is a mix of existing applied math and CS classes, with the new computation classes acting as the glue that holds it together.

There is another way to answer the questions “What to teach?” and “How to teach it?” That way is to provide computation-based textbooks that help define which topics constitute proper computational education, and provide a coherent presentation of the subject. The OSU Computational Physics Education group has been trying to do that for the last 15 years. Lists of more than 50 texts and other resources are to be found in a recent resource letter (Landau, 2008). Although most of those resources and most of this paper focus on more specialized computational topics, there is still very much an open question on what and how to teach computation to beginning college science students, and who should be doing the teaching. Our attempt takes the form of an Introductory Scientific Computing course designed to provide first and second year students with the computational tools needed throughout their undergraduate careers, and its associated text, A First Course in Scientific Computing (Landau, 2005). In recognition of the widespread disagreement over which computing tools lower division college students should learn, the paper text covers Maple and Java, while the accompanying CD contained essentially identical texts in Mathematica and Fortran90, as well as the associated notebooks, worksheets, programs, and data sets. The combination of A First Course in Scientific Computing and A Survey of Computational Physics (Landau et al, 2008) pave a continuous computational path throughout the undergraduate curriculum.

Figure 4. Concept map. Shows hardware and software components from computer

science, applied mathematics algorithms, and physics applications.


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4 Online Courses and Digital Books In addition to publishing text books, another way of encouraging the inclusion of more computation into curricula is to make at least the basic elements of computation courses available to faculty. As part of a demonstration project for establishing a national repository of computational science courses (EPIC), we have produced video based modules for our Introductory Computational Science course (Video, 2008). We already used them with good results in our teaching, while we are told that faculty and students at other schools are also finding them useful. In light of the previously documented large overlap among different computational classes, the plan is to have modules cover individual topics which then can be assembled and used in a variety of classes and in a variety of schools. (A full course would require problem sets, quizzes, assessment exercises, and possibly supplementary materials in a specific discipline.) Although we do not view the web as a good teaching medium for general education, or for students with weak self discipline or limited motivation, it is appropriate for computational science where the best way to learn it is while sitting at a computer in a trial and error mode. Actually, the web is essentially ideal for computational science (it was invented for particle physics analysis): projects are always in a centralized place for students and faculty to observe, codes and data are there to run or modify, and interactive visualizations can be striking with 3D, color, sound, and animation.

5 Using Python Python is a popular programming language used for both standalone programs and scripting applications in a wide variety of domains. It is free, portable, powerful, and remarkably easy to use.

One of the reasons why we decided to migrate to Python in our CP books and courses is that it provides a really nice balance between the practical and the conceptual (Downey et al, 2008). Since Python is interpreted, beginners can pick up the language and start doing neat things almost immediately without getting lost in the problems of compilation and linking. Furthermore, Python comes with a large library of modules that can be used to do all sorts of tasks ranging from web-programming to graphics. Having such a practical focus is a great way to engage students and it allows them to complete significant projects. However, Python can also serve as an excellent foundation for introducing important computer science concepts. Since Python fully supports procedures and classes, students can be gradually introduced to topics such as procedural abstraction, data structures, and object-oriented programming.

Another reason is the fact that Python is freely available for download. Versions are available for almost every operating system, including UNIX, Windows, Macintosh, and Java. In addition, the Python website includes links to documentation, how-to guides, and a wide assortment of third-party software.

The tools we have used in preparing the visualizations are: Matplotlib: Matplotlib is a very powerful library of plotting functions callable from

within Python that is capable of producing publication quality figures in a number of output formats. It is, by design, similar to the plotting packages with Matlab, and is made


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more powerful by its use of the numpy package for numerical work. In addition to 2-D plots, Matplotlib can also create interactive, 3-D visualizations of data.

Visual (VPython): The programming language “Python” is so often employed with the Visual graphics module and the IDLE interface that the combination is often referred to as Vpython. Much of the use of the Visual extension has been to create 3-D demonstrations and animations for education, which are surprisingly easy to make and useful.

Tkinter: Python also contains a graphical user interface (GUI) programming module called Tkinter or Tk.

6 Conclusions We think that only time will judge the viability of computational physics programs such as ours. However they do appear to attract new students and to provide them with broad preparation for future career choices. Also the use of Python programming language seems to be a good choice judging by the feedback of the students.

REFERENCES

AIP (1995): Skills Used Frequently by Physics Bachelors in Selected Employment Sectors. Technical report: American Institute of Physics Education and Employment Statistics Division. BORDEIANU, C. C., LANDAU, R. H. and PAEZ, M. J. (2009): Wavelet analyses and applications.

European Journal of Physics 30, 1049-1062. DOWNEY, A., ELKNER, J and MEYERS, C. (2008): How to Think Like a Computer Scientist.Learning with

Python. Green Tea Press. http://www.greenteapress.com/thinkpython/thinkCSpy/thinkCSpy.pdf EPIC: Engaging People in Cyberinfrastructure, www.eotepic.org LANDAU, R. H. (2004): Computational Physics for Undergraduates, the CPUG Degree Program at Oregon

State University. Computing in Science and Engineering. 6. LANDAU, R.H. (2005): A First Course in Scientific Computing. Princeton University Press, www.physics.oregonstate.edu/~rubin/IntroBook/. LANDAU, R. H., PAEZ, M. J. and BORDEIANU, C. C. (2007): Computational Physics. Problem Solving

with Computers, 2nd, Wiley VCH. LANDAU, R. H., PAEZ, M. J. and BORDEIANU, C. C. (2008): A Survey of Computational Physics.

Introductory Computational Science. Princeton University Press. LANDAU, R. H. (2008), Resource Letter CP-2: Computational Physics, American Journal of Physics 76,

296-306. VIDEO (2008): Video Lectures in Intro Computational Science, www.physics.oregonstate.edu/~rubin/COURSES/VideoLecs/

SRoL - Web-based Resources and Tools used for e-Learning of Languages and Language Technology

Silvia Monica Feraru1, Horia-Nicolai Teodorescu1,2

(1) Institute for Computer Science, Romanian Academy, Bd. Carol I nr. 8, Iaşi, România

(2) Gheorghe Asachi Technical University of Iaşi, Iaşi, România E-mail: [email protected]

Abstract The SRoL Web-based spoken language repository and tool collection was developed during several years by the collaboration of groups from the Institute for Computer Science of the Romanian Academy, CERFS Excellence Center in "Gheorghe Asachi" Technical University of Iasi and staff of the discipline of Language Technology, Computer Science Faculty, "Al.I. Cuza" University. The web site includes thousands of voice recordings grouped on sections like "Basic sounds of the Romanian language", "Emotional voices", "Specific language processes", "Pathological voices", "Comparison of natural and synthetic speech", "Gnathophonics and Gnathosonics". The recordings are annotated and documented according to proprietary methodology and protocols. Moreover, we included on the site extended documentation on the Romanian language, speech technology, and tools produced by us, for voice analysis. The resources are a part of the CLARIN European Network for Language Resources. The resources and tools are useful in virtual learning for phonetics of the Romanian language, speech technology and medical subjects related to voice. We report on several applications in language learning and voice technology classes. Keywords: spoken language resources, voice education, speech and language, “dictionary of sounds", educational and research purposes

1 Introduction In a world where the Web / Internet communication is pervasive, computer is more than a study topic for everyone, it is a ubiquitous tool. Computers serve for more than doing computations, they are now one of most used means of communication and interaction – the very basis of any educational system. As a consequence, computer-based education is an obvious choice whenever a distance separates the learner and the learning person. In a general sense, computer-based education and virtual education based on Internet is today an undeniable fact of life in every academic campus. While computers and the network are the means, the spoken language represents the prevalent support of communication in the teaching-learning process. Hence the natural need to address e-learning and virtual learning of languages, voice and phonetics, voice pathology, and other aspects related to voice and spoken language.

In view of the above, we built during a timeframe of about five years a web site that offers the possibility of teaching and learning various aspects on the Romanian language


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based on an annotated corpus freely accessible on the Internet. The corpus is complemented with in-depth phonetic and linguistic analyses, moreover with specific tools accessible by users from everywhere through the web (Zbancioc, M., 2006), (Teodorescu et al., 2006), (Teodorescu et al., 2007b), (Teodorescu H.N., Feraru M., 2007), (Teodorescu H.N., Feraru M., 2008). This instrument has a high level of dimensionality and aims to numerous aspects of the language that are not typical features in language corpora. This makes this “corpus-tool” the unique instrument of its kind existing today in the domain (Teodorescu et al., 2007a).

Since the second author initiated, five years ago, the Project “The Sounds of Romanian Language” (SRoL), the team increased to 8 researches. During the recent years, we studied different emotional speech database which can help in education and re-education of speech, in diagnosis and treatment, in learning a language aided by computer; examples of results published are (Teodorescu H.N. et al., 2007a), (Feraru M., Teodorescu H.N., 2008) etc.

Voice and language e-education is a topic addressed by many research and educational groups. Solomon studied the possibilities and issues of learning with and about computers in schools or in any other learning environment (Solomon C., 1988). The Eric Education Resources Page shows the importance of computer assisted education of speech and voice (Wise, B.W., Olson, R.K, 1994). On the other side, web-based educational resources and training have received attention during the last decade. Åke Olofsson offers a simple method of compensation for word decoding problems, by having the micro-computer which pronounces the words which can not be read. Olofsson uses a program developed for the IBM-PC/AT and a Scandinavian multilingual text-to-speech unit, and children can read a textfile on the monitor, and use a mouse to request the immediate pronunciation of a word (Olofsson Å., 1992).

The computer-assisted learning language software helps the interaction between student and computer by speech, by sound effects, by animation, by video, not only text. On the other hand, these are restricted by the mouse and keyboard, hence it is necessary an active interaction by spoken language through computer (Cameron K., 1999). Speech recognition offers the possibilities to computer-assisted learning language to have an active participation by oral reading and conversation. CALL system has recordings spelling by the native speaker. The user compares the quality of her pronunciation with model recordings.

In another direction of research, Warschaue observes the uses of online communications for language teaching. He determined that the interest in this domain grows day by day. He proposed a conceptual framework for understanding the role of the interaction assisted by computer (Warschaue M., 1997). Lundberg considers the computer a tool of remediation in the education of students with reading disabilities as dyslexic students which can benefit by computer training in correct reading and spelling the words (Lundberg I., 1995).

A speech database is a collection of files with sounds, structured after its own purpose. The SRoL resource (corpus) is located at the address (http://www.etc.tuiasi.ro/sibm/ romanian_spoken_language/index.htm). The initiator conceived SRoL as an Internet-based "dictionary of sounds and words" for the Romanian language supplemented with specific manifestations of voice (including pathologies) and various tools. The SRoL


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database includes files with vowels, consonants, diphthongs, sentences with emotional states, linguistic particularities for the Romanian language, dialectal voices, and gnathosonic and gnathophonic sounds. It is the first Internet based annotated database of emotional speech for the Romanian language which contains more than 1500 recordings in different coding formats (wav, ogg, txt / 22 kHz/ 24bit/ 16 bits). The phonetic recordings which refer to an annotated emotional speech corpus (database) are registered to ORDA. Figure 1 illustrates the home page of the SRoL speech database, which has English and French versions as well.

Figure 1. The frontpage of the SRoL project on the

web, at http://www.etc.tuiasi.ro/sib

m/romanian_spoken_language/index.htm.

In this paper, we provide details about the applications of this database and about the SRoL-web database, available to the address http://www.etc.tuiasi.ro/sibm/ romanian_spoken_language/index.htm.

2 Applications for learning Romanian language One of the goals of SRoL the web site is to provide a free Romanian database for students and researchers, for linguists, for teachers, in view of teaching, learning and analysis the Romanian language sounds. The database includes the pronunciation corpus and related documentation. The database contains among others, sections with:

- recordings of syllables and words pronounced in various contexts, like accentuated word, interrogative sentences, exclamations, various emotions conveyed by the speaker, etc. This part of the database is aimed as a source for concatenative synthesizers and as benchmark for the voice recognition systems – isolated words;

- files of sounds, syllables and words pronounced by persons with various pathologies; this section may be useful in medical and phonological researches;

- files with professional voices (“perfect” pronunciations), as well as non-professional voices, the “voices of the people in the street”. For the moment, we concentrate on voices from the Iaşi region (East Romania) and middle area of Moldova.

Learning and teaching languages require well documented audio-visual tools that exemplify and fully explain spelling for a large variety of voices and contextual and emotional states. While former methods, like tape recordings and audio disks have been


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helpful, the multimedia Internet-based tools offer tremendously increased capabilities. SRoL represents such a tool for the Romanian language. Not only it is the first for the Romanian language, but its multidimensionality makes it somewhat unique and novel in concept for language learning and teaching in general.

Consider the case of a foreign student who wants to improve her Romanian pronunciation by comparing the prosody of her voice with the prosody of native speakers. The student utters a sentence (from those included in the site), then opens Wasp or another similar tool and displays the energy and fundamental frequency in her voice. She then compares these prosodic features to the ones of native speakers and tries to improve her prosody until she produces correct prosodic patterns. Also, the student can compare formant values and try improving the formants of the vowels she pronounces.

This instrument is useful for learning to improve communication, moreover for human-computer speech interaction, for security, for medical applications, for video-games and interactive TV, for teachers, in the study of the Romanian language, etc.

3 Applications in medical education and re-education of speech Voice education is needed whenever a voice pathology including some neurologic and psychiatric disorders or pathology of the vocal tract occurs. Several groups have addressed the voice re-education topic (Lundberg I., 1995), (Olofsson Å., 1992).

Till now, we included in SRoL words pronounced by persons with minor pathologies as trembling voice. We have demonstrated in our research that splitting the signal in frequency bands that correspond to the peak of F0 – F1 formants and respectively to the peak of F2 – F3 formants helps improving the discrimination process in a significant way. The use of fractal dimensions in assessing the jitter or shimmer in voice produce mixed results. Adding other fractal dimension, the rate of recognition of the tremor segments in voice improves, but it still low (Teodorescu H.N. et al, 2005). This section of the database is useful in medical and phonological researches. Also for medical education use, the site comprises a gnathosonic and gnathophonic corpus. It offers opportunities for diagnosis and treating of speech by hearing the correct pronunciation of the words. In figure 2, we exemplify a gnathophonic (a) and gnathosonic (b) recording sounds (of the speaker 19743m). In figure 2(a), we exemplified recordings of the words: “vata”, “fata”, “var”.

a b

Figure 2. Gnathophonic (a) and gnathosonic (b) recording with details, tool GoldWaveTM. By analyzing such recordings available at SRoL, students can learn how

to differentiate the normal and pathological states


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Figure 2(b) illustrates a double occlusive sound. These two occlusive sounds are separated in time and denote two contact points. This is a type of occlusive sound which can produce in time a deficiency in the mandibulary movement and erosion of teeth. The educators and students can use many the statistical studies regarding the pathological sounds in the Romanian language and recordings of persons with different pathologies (see section: Gnathosonic and Gnathophonic Archive) that the site includes.

Emotions rending in voice and emotion analysis is increasingly addressed in recent years, including for medical and psychiatric diagnosis and treatment (Lundberg I., 1995), (Olofsson Å., 1992). The recordings from the emotional database at Max-Planck-Institute of Cognitive Neuroscience are made by a female fluent speaker; they made an electroencephalogram (EEG); the validation commission has twenty persons; they didn’t offer information about the listeners; they judged the semantic content and the prosodic feature on five-point scale; the goal was to relate the emotions and to recognize a location in the human brain (Polzin, T.S., Waibel, A.H., 1998). We have addressed the topic in SRoL. The SRoL database contains feminine and masculine emotional voices; the speakers are aged between 25-35 years and they have no manifested pathologies. We analyzed only the audio voice signal. We did not make analyses like EEG, EMG, electroglottogram, etc., as those contained in other databases, like the Magdeburger Prosodie Korpus (Wendt B., Scheich H., 2002).

Every recording from the SRoL database is accompanied by the speaker profile and by the questionnaire concerning vocal pathology and objective factors for every speaker (Feraru, M., Teodorescu, H.N., 2008). The speaker’s profile offers linguistic, ethnic, medical, educational, professional information about the speaker. The questionnaire presents details regarding the health state of the speaker (http://www.etc.tuiasi.ro/sibm/romanian_spoken_language/ro/protocol_nou.htm).

4 Applications in teaching the voice signal technology classes Signal technology classes are taught around the world. For examples, the Center for Spoken Language Understanding (CSLU) offers available language database from speech area and hearing science. These resources are important for analyzing the speech, for diagnosing and treating speech and language problems, for training students and so on. The tools and the corpora are distributed to over 2000 sites in 65 countries (Cole R.A., 1999). In education these tools help students learn about speech, learn a new language, learn through interactive media systems, or to become accustomed to hearing the normal and abnormal voice signal.

The SRoL team developed instruments for vocal signal processing regarding the extraction of patterns from this signal, and the computing of the fundamental frequency trace, respectively the traces of formants F1, F2, F3. The site offers, beside executables programs, descriptions for each of these tools. Those descriptions are intended for a “medium user”, offering elementary explications and relevant references for a deeper understanding (Teodorescu H.N. et al., 2007), (Cristea D. et al, 2004).

The second author currently uses the SRoL corpus in teaching and laboratory activities in the class “Speech Technology” given for the master degree in “Computational


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Linguistics” at the Faculty of Computer Science, “Al.I. Cuza” University of Iaşi. Details on the use in Voice Technology classes of some topics from SRoL are described in (Cristea D. et al, 2004). At the international EUROLAN 2007 summer school, the second author used the SRoL site to present “Traces of emotion, intentions and meaning in spoken Romanian” (http://eurolan.info.uaic.ro/html/ profs/HNTeodorescu.html). The second author taught the specific methodology aspects, results obtained on the characterization of emotions in speech, possibilities of recognition of emotions and intentions in speech, and the relationship between specific meanings and the prosody in specific constructions in the Romanian language. The lesson exemplified applications of analysis of the speech emotional prosody to social, psycho-social, educational and psycho-medical topics.

5 Discussion and conclusions Our team has a long standing experience with using novel technologies in teaching, hosting for three decades (Teodorescu H.N., Sofron E., 1987), (De Coulon et al., 1996), (Teodorescu H.N., 1998), (Teodorescu H.N. et al, 2000a,b), (Teodorescu H.N., 2001). We applied that experience to the SRoL e-teaching and e-learning resource.

The SRoL resource is a vast annotated corpus of speech files complemented by tutorials, papers and additional files, moreover with tools for speech processing. If used by an experimented student or teacher, it may become a powerful tool for instruction and learning the Romanian language pronunciation, speech technology, and voice pathology and re-education. The SRoL sound voice resource is useful in many domains, including phonology, applied computer science, and medicine. Students and researchers have the opportunity to have a freely accessible site, for learning the pronunciation of Romanian language, for making comparative study between Romanian and other language, for development of synthetic systems, for other linguistic, phonetic, socio-linguistic or medicine applications.

This database is structured corresponding to precise criteria, documented and annotated according to a well defined methodology. The site has more then 1500 recordings of syllable, word, sentence with different tonalities and pronounced with different emotional states. The database contains recordings of professional and normal voice, from the Nord – East region of Romania, without dialectal accent.

The SRoL resources have been recognized by several bodies, beyond the scientific publications that included our papers on SRoL. CLARIN European Network of Language Resources accepted SRoL as a member; ORDA (the Romanian Office for Authorship Rights) registered the original recordings, and the SRoL received a gold medal and media attention at the INVENTICA 2009 fair for inventions and creativity. Also, the website of Ambassade de France in Romania briefly described in its Bulletin the SRoL site and its use in education (http://www.bulletins-electroniques.com/actualites/58811.htm). Technical University „Gheorghe Asachi” of Iasi, Faculty of Electronics, Telecommunications and Information Technology) intends to use SRoL in helping foreign students enrolled at this university learn Romanian pronunciation.


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We hope the SRoL resources will be used in all the universities in Romania by foreign students who learn the Romanian language, moreover in other academic media and as an online tool by foreign students and teachers. We welcome any request for help and educational advice from all those who wish to use our SRoL language-related web resources in virtual e-teaching and learning.

Acknowledgments. Research partly performed for the Romanian Academy “priority research” theme “Cognitive Systems” and to CEEX grant nr 46/2005. We thank those who contributed to SRoL, primarily D. TrandabăŃ, M. Zbancioc, R. Luca, and L. Pistol.

REFERENCES

Wendt, B. and Scheich, H. (2002): The Magdeburger Prosodie-Korpus. Proc. Speech Prosody Conf. Aix-en-Provence, France, pp. 699-701.

Polzin, T.S. and Waibel, A.H. (1998): Detecting emotions in speech, Conference on Cooperative Multimodal Communication - Proc. CMC., Tilburg, The Netherlands.

Cole R.A. (1999): Tools for Research and Education in Speech Science, Proc. Int. Conf. for Physics Students, www.cslu.ogi.edu/toolkit/pubs/pdf/cole_ICPS_99.pdf.

Wise B.W. and Olson R.K. (1994): Computer Speech and the Remediation of Reading and Spelling Problems, J. Special Education Technology, vol. 12, nr. 3, pp. 207-220.

Olofsson Å. (1992): Synthetic speech and computer aided reading for reading disabled children, Journal: Reading and Writing, vol. 4, nr. 2, pp. 165-178, ISSN: 09224777, (http://www.springerlink.com/content/ j521536n135x2864/).

Lundberg I. (1995): The Computer as a Tool of Remediation in the Education of Students with Reading Disabilities: A Theory-Based Approach, Learning Disability Quarterly, vol. 18, nr. 2, Technology for Persons with Learning Disabilities (1995), pp. 89-99, http://www.jstor.org/pss/1511197.

Cameron K. (1999): Computer Assisted Language Learning (CALL): Media, Design, and Applications, Taylor & Francis, ISBN: 902651543X, http://www.google.com/books?id=dO_sNQlWhrsC& printsec=frontcover&dq=related:ISBN0940753030&hl=ro&source=gbs_similarbooks_s&cad=1

Warschaue M. (1997): Computer-Mediated Collaborative Learning: Theory and Practice, The Modern Language Journal, Vol. 81, No. 4, Special Issue: Interaction, Collaboration, and Cooperation: Learning Languages and Preparing Language Teachers (Winter, 1997), pp. 470-481, http://www.jstor.org/ pss/328890

Solomon C. (1988): Computer Environments for Children –A Reflection of Theories of Learning and Education, www.google.com/books?id=EonPZ9A81kkC&printsec= frontcover&hl=ro&source=gbs_v2_ summary_r&cad=0

Feraru M. and Teodorescu H.N. (2008): The Emotional Speech Section of the Romanian Spoken Language Archive, Proc. 5th European Conf. on Intelligent Systems and Technologies, Iaşi, România, ISBN 978973730497.

Cristea, D., Teodorescu, H.N., Tufiş, D.I. (2004): Student Projects in Language and Speech Processing, Workshop on Language Resources: Integration and Development in E-learning and in Teaching Computational Linguistics, pp. 17-22, 4th Conf. on Language Resources and Evaluation, Lisbon, Portugal - http://nats-www.informatik.uni-hamburg.de/view/Main/AcceptedPapers.

Teodorescu, H.N., TandabăŃ, D., Feraru, M., Zbancioc, M., Luca, R. (2007): A corpus of the sounds in the Romanian spoken language for language-related education. Ch. 6, pp. 73-89. In: C.P. Pascual (Ed.), “Revisiting Language Learning Resources”, Cambridge Scholars Pub. (CSP), UK, ISBN 1847181562; pp. 73-89.

Teodorescu, H.N., Dobrea, D.M., Forte, E., Wentland-Forte, M. (2000a): A High Sensitivity Sensor for Proximity Measurements and Its Use in Virtual Reality Applications, Proceedings of the European Conference of Intelligent Technologies, Iaşi, România, ISBN 973-95156-1-4.

De Coulon, F., Forte, E., Mlynek, D., Teodorescu, H.N., Suceveanu, Şt. (1996): Subject State Analysis by Computer in CAE, Proc. Int. Conf. on Intelligent Technologies in Human-Related Sciences, Leon, Spain. vol. 2, pp. 243-250.


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Teodorescu, H.N., Ganea, R., Feraru, M., Burlui, A. (2005): Assement of Voice quality based on nonlinear dynamic analysis, Proceedings of The 15th Int. Conf. on Control Syst. & Computer Sci., Bucharest, România, pp. 536-542, ISBN 9738449898.

Teodorescu H.N. (1998): Computer semiotics: understanding meanings and parallel languages (Refereed invited paper). In: T. Yamakawa, G. Matsumoto (Eds.): Proc. Int. Conf. IIZUKA’98, World Scientific Publ., pp. 279-283.

Teodorescu, H.N., Kandel, A., Paschall, B. (2000b): Teaching Modern Chapters in Automata Theory and Formal Languages, Symp. 21 Century Teaching Technologies, March 20, Univ. South Florida, Tampa, USA (abstract in booklet of the Symposium.).

Zbancioc M. (2006): Tools for the Archive of the Romanian Language Sounds Project, 4th European Conf. on Intelligent Systems and Technologies, Iaşi, România, ISBN 973-730-265-6.

Teodorescu, H.N., Zbancioc, M., Mihăilescu, E. (2006): Speech Technology and Bio-Medical Engineering Teaching Based on the Web-A new Tool and Case Study, International Conference on Interactive Computed Aided Learning, Sept. 27-29, Villach, Austria.

Teodorescu, H.N, Feraru, M., TrandabăŃ, D. (2007b): Studies on the Prosody of the Romanian Language: The Emotional Prosody and the Prosody of Double-Subject Sentences, C., Teodorescu, H-N (Eds.) Advances in Spoken Language Technology, The Publishing House of the Romanian Academy, Bucharest, România, ISBN 978-973-27-1516-1, pp. 171-182.

Teodorescu, H.N. and Feraru, M. (2007): Micro-corpus de sunete gnatosonice şi gnatofonice, Pistol, Cristea, Tufiş (eds.) Resurse lingvistice şi instrumente pentru prelucrarea limbii române. Editura UniversităŃii “Al. I. Cuza” Iaşi, pp. 21-30, ISBN 978-973-703-297-3.

Teodorescu, H.N. and Feraru, M. (2008): Classification in Gnathophonics – Preliminary Results, The Second Symposium on Electrical and Electronics Engineering, GalaŃi University Press, pp 525-530, ISBN 1842-8046.

Teodorescu H.N. (2001): Interrelationships Communication Semiotics, in vol. “What Should be Computed to Understand and Model Brain Function: From Robotics, Soft Computing, Biology and Neuroscience to Cognitive Philosophy”, (Ed.) Tadashi Kitamura. World Scientific, ISBN 9810245181, pp. 115-148.

Teodorescu, H.N. and Sofron, E. (1987): Demonstrating dislocations evolution, Int. Journal Applied Engineering Education. vol. 3, nr. 2, pp. 189 -192.

Note. Due to the character of this article and to space limits, more references from the literature

could not be included, as needed by the topic of the paper.

Virtual Learning, Blended Learning and Modern Foreign Languages: Let’s listen to the students!

Nathalie Ticheler

London Metropolitan University, Faculty of Humanities, Arts, Languages and

Education, LC110, 236-250 Holloway Road, London N7 6PP (UK) [email protected]

http://www.londonmet.ac.uk/olp

Abstract The Open Language Programme (OLP) at London Metropolitan University is an Institution-Wide Language Programme which offers credit-bearing modules to undergraduates and post-graduates of all subjects, staff from the university, as well as members of the general public. The programme is available in eight languages (General and Business English, Arabic, French, Italian, Japanese, German, Mandarin Chinese and Spanish) at up to ten different levels. All modules are based on a blended learning formula, a package of face-to-face group tuition and self-study. Since October 2008, all OLP students have had access to Weblearn, our Virtual Learning Environment (VLE), which provides essential course information, together with specially-tailored blended learning materials. A study was conducted among students of Japanese for beginners and post-beginners in spring 2009 and sought to evaluate their experience of Weblearn in the context of blended learning, using largely their own reported accounts and a mixed method approach to research. This paper presents initial findings, with a particular focus on collaborative learning.

Keywords: VLE, blended learning, collaborative learning, students’ experience

1 Background of the study The precarious situation of Modern Foreign Languages in the United Kingdom, with issues such as the decreasing number of students on specialist language degree courses and the closure of university departments, is reported by numerous organisations such as the National Centre for Languages (CILT) and the Higher Education Funding Council for England (HEFCE).

CILT with support from the Association for Language Learning and the Independent Schools’ Modern Language Association conducted a survey based on a questionnaire sent to a representative sample of 2,000 schools in England, with a response rate of 43%. The survey has been carried out annually since 2002 to track developments in language provision and take-up in secondary schools. The 2008 survey indicates that

The declines of the past few years have been halted, although not yet reversed, but the picture is one of turbulence rather than stability. There are signs of shifts and upheavals, both positive and negative, as schools adjust to having to “make the case” for languages to students. (CILT, 2008)


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Regarding Higher Education, the CILT analysis (2008) of HESA data, based on annual enrolment figures, reveals a decline of 5.3% overall on first degree language students in Higher Education between 2002-2003 and 2006-2007. In contrast, enrolments for first degrees increased by 29.9% for Japanese. Enrolments on Japanese language modules as part of non-language specific degrees increased by 37.8% between 2002-2003 and 2006-2007. Kelly (2008) explains that

languages remain vulnerable, despite being strategically important for the future of the country. But there are signs that government initiatives and the efforts of language educators are beginning to have an effect, at least in slowing the decline.

In this context, various initiatives have been launched at national level. For example,

the DFES National Languages Strategy (2002) has implications at all stages of the education system and extends beyond the classroom, including at international level

In the knowledge society of the 21st century, language competence and intercultural understanding are not optional extras, they are an essential part of being a citizen. (Ashton 2002)

HEFCE has agreed to fund Routes into Languages to encourage the take-up of

language courses in England. The programme, led by the Subject Centre for Languages, Linguistics and Area Studies (LLAS), in a partnership with the University Council of Modern Languages (UCML) and CILT, is scheduled to run until 2009/2010.

The study is firmly anchored in a context of promotion of e-learning and evaluation of the student experience at governmental and institutional levels. Following the publication in March 2005 of the HEFCE ten-year e-learning strategy, the Higher Education Academy was invited to lead a benchmarking exercise and related Pathfinder programme in partnership with the Joint Information Systems Committee (JISC). The benchmarking exercise was intended to help institutions establish where they were in regard to embedding e-learning. The Pathfinder programme, by contrast, was specifically designed to help selected institutions, on behalf of the sector, identify, implement and evaluate different approaches to the embedding of technology-enhanced learning in ways that result in positive institutional change. In a context of widening participation within Higher Education Institutions, coupled with budgetary constraints, e-learning is frequently presented in educational circles as of clear benefit, at governmental level, at institutional level and at student level. Indeed, Hurd (2002) comments

Increasing diversity in the student population, through widening participation, new technologies and new, more cost-efficient practices in course production are forcing a re-think of current activity and providing a challenge to all those involved in the design and delivery of learning constantly seek out ways of ensuring that the needs of our language learners are met.

At London Metropolitan University, OLP students are presented with a blended learning package of three hours per week of face-to-face group tuition over twelve weeks, supplemented with specially-tailored e-learning materials (online packs) available on Weblearn, the university’s VLE, together with other course documentation.


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The study seeks to evaluate students’ experience of Weblearn among students of Japanese, with a particular focus on the transition from beginners to post-beginners, in the context of blended learning, using largely students’ own reported accounts and a mixed method approach to research, heavily based on theories of collaborative learning.

2 Key concepts in context Learning is linked intrinsically to life and happens both consciously and unconsciously, in formal and informal settings. It varies according to the individuals, their intended outcome, is influenced by factors both internal and external to the learners and fluctuates over time. Here, learning focuses on students’ interaction with technologies, in a semi-formal setting and draws on self-study skills, language learning skills, computer skills and use of technologies.

All OLP students are presented with a blended learning package of 3 hours of lessons per week over 12 weeks, supplemented with self-study materials based on Weblearn. MacDonald (2006:2) defines blended learning as 'associated with the introduction of online media into a course or programme whilst recognising merit in retaining face-to-face contact. ' Here, I will define blended learning more precisely as the combination of face-to-face scheduled lessons taking place at the university, supplemented by tailored e-learning activities based on the VLE.

In addition, I take the view that collaborative learning is essential to students’ progress. I will define collaborative learning as the possibility for the learners to learn from one another, and for the learners to learn from the tutor using communication tools available on the VLE (which includes training of students by tutors in the use of VLEs). In agreement with socio-constructivist models of learning, I believe that the human factor plays a major part in the students’ learning experience. Beale (2004) highlights the importance of communication tools and collaborative learning as forms of support to maximise students’ learning

'For many people, what is required is the digital equivalent of the street corner-where people can come and go; requiring little knowledge to participate in; and where people can learn and gain support and advice from their colleagues. '

For Naismith et al (2006), the potential of learning technologies can only be considered either embedded in classroom practice or as part of a learning experience outside the classroom. In addition, they recognise their capabilities for social interactions and foresee that

Learning will move more and more outside of the classroom and into the learner’s environments, both real and virtual, thus becoming more situated, personal, collaborative and lifelong. (Naismith et al 2006)

3 Methodology The objective was to collect data on students’ lived experiences and to identify the meanings behind their reported behaviours and attitudes. Therefore, I followed a


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perspective based on hermeneutical phenomenology, which focuses on interpretive structures of experience, how we understand and engage in our human world.

Phenomenological research, in which the researcher identifies the 'essence' of human experiences concerning a phenomenon, as described by participants in a study. Understanding the lived experiences marks phenomenology as a philosophy as well as a method. (Creswell 2003)

This was reinforced by a combined positivist and interpretative approach, coupled with a qualitative and quantitative treatment of data, using student self-completion questionnaires, learning diaries and the tracking function on the VLE.

Positivism is an approach to social research which seeks to apply the natural science model of research to investigations of the social world. It is based on the assumption that there are patterns and regularities, causes, and consequences in the social world, just as there are in the natural world. (Denscombe 2003)

In line with a positivist framework, quantitative data was obtained from the closed questions included in the questionnaire and the tracking function. Open questions related to students’ experience of Weblearn and data from the learning diaries lent themselves to a qualitative treatment, in agreement with an interpretative approach.

The sample population included 34 students, 21 beginners and 13 post-beginners, studying Japanese on the OLP in spring semester 2009, with significant proportions of part-time and external students (members of the general public enrolled on OLP modules). Most post-beginners had previous experience of Weblearn. Overall, 67% of participants completed the self-study component of their Japanese module from home, away from their peers, tutors and university facilities.

4 Experience of Weblearn Approximately 50% of participants thought Weblearn contributed to their progress. 27% of beginners were satisfied or very satisfied with the provision and 36% thought 'it was ok'. Figures reached 60% and 25% respectively, among post-beginners.

Participants admitted to spend only a limited amount of time on Weblearn, less than one hour per week for 52% of beginners and 77% of post-beginners. Reasons for the limited use of Weblearn deserve further investigation and may include personal or professional commitments, the possibility to use the online packs without logging to Weblearn, negative views towards the VLE, lack of integration of Weblearn into the taught component or simply different learning preferences.

Weblearn contains Japanese learning materials and course documentation, such as module handbooks, weekly course syllabi and details of assessment. Both beginners (76%) and post-beginners (92%) declared referring to the module handbook. Regarding the weekly syllabi, figures reached 39% and 60% respectively. Online announcements appeared to be neglected by students, as beginners (52%) and post-beginners (46%) only read them 'once in a while'.


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5 Experience of the online packs Online packs are specially-tailored e-learning materials which students should use for self-study and homework, once they have attended their weekly class. They contain a variety of exercises with answers included (listening, reading, writing, vocabulary, grammar, practice of the Japanese script) and additional web links. Online packs are available as a link on Weblearn and students access them as web pages with usernames and passwords.

65% of beginners (against 27% of post-beginners) declared being satisfied or very satisfied with the online packs. The study focused on specific aspects of these materials such as their user-friendliness, visual aspect, choice of topics and variety. In all these areas, the proportion of students who were satisfied or very satisfied declined as they progressed to post-beginners’ level. 72% of beginners (against 55% of post-beginners) thought the online packs were user-friendly or very user-friendly. 50% of beginners and 20% of post-beginners were happy or very happy with the presentation of the online packs. For the choice of topics, figures go down from 67% to 38% and finally there is a decline from 56% to 45% regarding the variety of tasks.

Few students (15% of beginners and 20% of post-beginners) submitted to their tutors written tasks included in the online packs. In addition, 50% of beginners and 70% of post-beginners were rarely or never taking notes as part of their 'homework'. Students as a whole preferred to use their own lecture notes and set coursebook, as a source of help. Beginners also referred to other coursebooks while post-beginners started showing an interest in dictionaries. Students’ preferences for the use of the set coursebook and own lecture notes may be explained by the fact that classes are scheduled in the evenings only and most students (67%) admittedly complete their Weblearn work off-site, as opposed to using the university’s self-access facility (Language Centre).

6 Interpretation Decisions were made at institutional and departmental levels to use a VLE. Indeed, London Metropolitan University has launched a blended learning strategy through Weblearn. Both teaching staff and students have received some introductory training in this area. Participants have expressed the following views regarding Weblearn

Weblearn is excellent and gives very good opportunities for extra practice Exercises on weblearn are very useful; I like the section on Manga Weblearn contains all the material needed to help language learners Weblearn is very useful to improve my Japanese. It has everything I want to learn, is fun and interesting Weblearn is very interesting and fun. It makes me enjoy the course. Everything we learn is shown on weblearn

However, figures regarding the frequency of use, the submission of written tasks and the consultation of online announcements show a fairly limited use of Weblearn. Bearing in mind constraints faced by both staff and students, data indicates some possible reasons for these findings such a perceived lack of connection between taught contents and the self-study component by the students, coupled with tutors’ choice to distribute additional


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materials which follow more closely actual lesson contents. Indeed, 5 students would have liked Weblearn to match up more closely with lessons and another 2 students were satisfied with handouts only. In addition, 9 students stated a preference for using alternative materials such as books they purchased themselves (in addition to their set coursebook) or other printed materials of their choice.

As part of the qualitative treatment of data, 6 students reported technical difficulties such as the inability to login, dead links in the online packs and problems to download materials or display the Japanese script properly. Another 6 students commented on the difficulty to navigate and find materials.

Finally, quantitative data on students’ experience of the online packs indicates that updating the materials may be beneficial in various areas, as indicated in an earlier section.

Students appeared to respond more positively to web links available on Weblearn. In this area, beginners had a preference for the links towards the online packs (26%), flashcards (15%), and sites such as Kids Web Japan (14%), as well as Hiragana charts and Web Japan Culture (12%). Post-beginners used the Hiragana charts (23%) and online packs, flashcards and Web Japan were of equal interest (17%). Here again, figures seem to indicate a shift away from the online packs towards a greater variety of web-based materials.

7 Recommendations Beginners (85%) and post-beginners (54%) would like to use online packs in pdf and mp3 format, which would resolve difficulties related to the display of the Japanese characters.

Participants would generally welcome additional materials to download from Weblearn (such as helpsheets with key vocabulary and grammar, or Hiragana/Katakana tables and practice sheets). In this study, figures ranged from 14 to 16% among beginners for each of the extra materials listed above; and 12 to 17% among post-beginners. Communication tools only attracted 5% of the cohort. These issues would benefit from further investigation, as they have implications regarding material development, collaborative learning and both staff and student training.

Regular updates, following students’ feedback, is likely to assist in maintaining students’ motivation and satisfaction. Indeed, students who are active participants of their own learning, in terms of what, when and how they learn, are more likely to keep motivated. The Flexi-pack project launched at SOAS-UCL CETL Languages of the Wider World is of particular interest here (Ticheler & Sachdev 2008).

Ideally, authors of materials, including updates, should be tutors with current or previous experience of the modules, to ensure a greater compatibility of materials with taught sessions. Principles of teacher empowerment and theories of collaborative learning indicate that a greater involvement of tutors at the production stage is likely to boost the normalisation of materials among students.

Indeed, I would suggest taking direct action to foster a greater normalisation of the VLE among teaching staff and students, both in and out of the lessons. I take the view


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that teaching staff need to guide and motivate students to make regular use of the Weblearn provision presented to them by giving them a demo early in the course, together with regular learning tips in class and adding materials and information to be consulted both in and out of class. In short, the key is to embed e-learning in regular learning and teaching activities, to seek feedback from stakeholders at regular intervals and to ensure flexibility of the provision, in hand with careful training.

8 Conclusion This study focused on students’ experience of Weblearn in connection with their Japanese module on the OLP at London Metropolitan University. A mixed method research strategy combining a qualitative and quantitative treatment of data pointed out difficulties in areas such as e-learning design and learning preferences and a case was made for the benefits of collaborative learning. In particular, the normalisation of Weblearn is of significant importance for blended learning to succeed. Another necessity is to integrate regular feedback from staff and students to practice-based research projects.

REFERENCES

Beale, R. (2004): Wireless Learning Community Hub. In Conference Proceedings of M-Learn 2004, M-Learn, Rome, 23-24.

CILT. (2008): Language Trends 2008. CILT, London. CILT. (2008): First Degree Student Enrolments in the United Kingdom, 2002-2003 to 2006-2007 Including

Language Analysis. CILT, London. http://www.cilt.org.uk/research/statistics/education/higher. htm#higher1 Canning, J. (2008): Five Years on: The Language Landscape in 2007.Subject Centre for Languages,

Linguistics and Area Studies, Southampton. Creswell, J. (2003): Research Design: Qualitative, Quantitative and Mixed Methods Approaches (2nd

edition). Sage Publications, Thousand Oaks, California. Denscombe, M. (2003): The Good Research Guide for Small-Scale Social Research Projects (2nd edition).

Open University Press, Maidenhead. Department for Education and Science. (2002): Languages for All: Languages for Life. A Strategy for England, http://www.teachernet.gov.uk/_doc/11879/ LanguagesForAll.pdf

Higher Education Funding Council For England, Joint Information Systems Committee and Higher Education Academy. (2005): E-Learning Strategy. http://www.hefce.ac.uk/pubs/hefce/2005/05_12/05_12.pdf

Higher Education Funding Council for England. (2009): Enhancing Learning and Teaching Through the Use of Technology. A Revised Approach to HEFCE’s Strategy for E-Learning. HEFCE, Bristol.

Hurd, S. (2002): Learner Difference in Independent Language Learning Contexts. Good Practice Guide. Subject Centre for Languages, Linguistics and Area Studies, Southampton. http://www.llas.ac.uk/ resources/gpg/1573

Joint Information Systems Committee. (2008): E-Learning Benchmarking and Pathfinder Programme 2005-2008: An Overview. The Higher Education Academy, York.

Macdonald, J. (2006): Blended Learning and Online Tutoring. A Good Practice Guide.Gower Publishing, USA. Naismith, L. (2006): Literature Review. In Mobile Technologies and Learning. Futurelab, Birmingham.

Routes into Languages http://www.routesintolanguages.ac.uk Subject Centre for Languages, Linguistics and Area Studies http://www.llas.ac.uk The National Centre for Languages http://www.cilt.org.uk Ticheler, N & Sachdev, I. (2008): Mobile Learning, Collaborative Learning and World Languages. The Flexi-

Pack Project at SOAS-UCL CETL Languages of the Wider World http://www.llas.ac.uk/ resources/paper/3128

The eLiTA (e-Learning in Textiles & Apparel) Project

Mirela Blaga1, Simon Harlock2

(1) Assoc. Prof., Ph. D, CText ATI, Gheorghe Asachi Technical University of Iasi,

Romania, E-mail: [email protected] (2) B.Sc. Ph.D., Media Innovations Ltd, UK,


Abstract This paper will present the eLiTA (e-Learning in Textiles & Apparel) Project to develop elearning modules in textiles and apparel for use in education and training in Europe. The project is being undertaken by a consortium of academic organisations in Greece, Latvia, Portugal, Romania and Slovenia, a training organisation and a company in the UK and is supported with funding from the Leonardo da Vinci programme in the European Union. The aim of the project is to build on the earlier work of two previous Leonardo da Vinci funded projects which developed elearning materials on apparel technology, carpet technology, hosiery technology and dyeing printing and finishing in Czech, English, French, Lithuanian and Turkish. The eLiTA project will update the content and produce the elearning materials in English, Greek, Latvian, Portuguese, Romanian and Slovenian. The project will provide a new Internet-Based European wide learning tool to provide a user friendly way of learning at a place, pace and time to suit the needs of the individual and extend the opportunity to study in this way to more companies and organisations throughout Europe. Keywords: e-Learning, Textiles & Apparel, Leonardo da Vinci programme

1 Introduction

This paper will present the eLiTA (e-Learning in Textiles & Apparel) Project to develop elearning modules in textiles and apparel for use in education and training in Europe. The project is being undertaken by a consortium of the following academic and training organisations and companies in Greece, Latvia, Portugal, Romania, Slovenia and the UK.

TEI OF PIRAEUS, Department of Textiles University Greece Riga Technical University Institute of Textile Materials Technology and Design

University Latvia

University of Minho University Portugal Gheorghe Asachi Technical University of Iasi Faculty of Textiles and Leather Engineering

University Romania

University of Maribor, Faculty of Mechanical Engineering (UMFS)

University Slovenia

KLITRA Limited Training Organisation

UK

Media Innovations Ltd Private Company UK


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The project is supported with funding from the Leonardo da Vinci programme in the European Union.

2. Aims and objectives of the project

The European Economic Community has established a Lifelong Learning Programme (LLP) to “enable individuals at all stages of their lives to pursue stimulating learning opportunities across Europe”.

The LLP comprises several sub-programmes, of which the Leonardo da Vinci programme address vocational education and training.

The eLiTA project aims to address the following objectives within the Leonardo da Vinci programme:

• General Objective - “To support improvements in quality and innovation in vocational education and training systems, institutions and practices”.

• Operational Objective - “To support the development of innovative ICT-based content, services, pedagogies and practice for lifelong learning.”

• In addition, the project addresses the Call Priority 4 “Skills development of adults in the labor market”.

• The project will primarily address the National Priority 4 “Applications which demonstrate close links and relevance to national VET systems.”

• In addition the project will address one secondary National Priority (Priority 1) • “Applications which promote the transfer and recognition of qualifications and

competences in the UK and across Europe.” The eLiTA project will address these by updating innovative interactive ICT-based

learning tools developed in previous Leonardo da Vinci projects. In addition the project will adapt the tools so that they can be used in new partner countries compared to those in previous projects. This in turn will support lifelong learning within the partner countries to help overcome gaps in provision. The tools will provide a user friendly way of learning at a place, pace and time to suit the needs of the individual and extend the opportunity to study in this way to more companies and organisations throughout Europe.

The breadth and depth of content will make the modules suitable for study at both fundamental and more advanced levels and are intended for use by employees within organisations involved in the design, manufacturing and retailing sectors as well as students at school and further and higher educational institutions. In addition, the tools will help to improve the recognition and validation of work-based learning which will in turn support career development and lifelong learning within the European Textiles sector.

3. The need for the project There is much published data to show the need for this project. The importance of the textile sector to the European Union is underlined by the report European Technology Platform for the future of textiles and clothing - A vision for 2020 p.4 states “the European Textiles and Clothing industry … continues to represent one of Europe’s major


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industrial sectors with an annual turnover of 215 billion Euro and a total workforce of 2.6 million”.

The need for the Project to produce Internet based training tools is highlighted in the Final Evaluation Report (March 2006) for the “European Textiles Learning Tools”

Project as evaluated by Glendevon Associates. The report p.4 states “Perhaps more importantly is the potential of the product design and any future on-line versions; evaluation suggests that they will be capable of supporting the development of a range of vocational competences throughout the industry in Europe”.

In addition, the report by Advottex Network (Investigating Strategic

Needs For Advanced Vocational Training In The European Textile And Clothing (T&C) Industry) found that the types of training tools preferred were …Internet (31%) based products. (Page 25). These findings have helped to reaffirm the design of the project in confirming that the use of Internet based training materials is effective in helping SMEs in the textile industry to improve competitiveness.

The project targets workers in the European textile sector at operative level. In the Textile sector although there have been a number of job losses, there is a significant demand for new workers due to the age of the workforce. This replacement demand is highlighted in the Skills for Business Working Futures 2004-2014: National Report p.130 “the largest level of replacement demand will arise amongst machine and transport operatives … on average around a third of the current workforce will need to be replaced over the next 10 years”.

4. Background to the project The learning tools to be used and updated in the eLiTA project have their origins in a suite of computer based learning modules developed in 1995 in the Department of Textile Industries at the University of Leeds, UK for undergraduate and postgraduate students to study the fundamental principles of textile technology. This “Introduction to Textiles” suite of modules provided an estimated 80 hours of learning material covering:

Yarn Manufacture Knitting Technology Weaving Technology Woven Structures Non- Woven Fabric Manufacture Dyeing, Printing and Finishing Technology Clothing Technology

Textile Testing and Quality Assurance In 1996 further modules were developed including:

Clothing Technology 2 Weft Knitted Fabric Analysis Textile Material Identification Fashion Technology - a version of Introduction to Textiles tailored for students

studying fashion design.


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Subsequently in 2000 The Knitting and Lace Industries Training Association (KLITRA) in the U.K. piloted Introduction to Textiles within companies who manufacture, mostly cashmere, knitwear in the Borders region of England and Scotland to evaluate it as a means to provide the fundamental textile education for their employees studying for National Vocational Qualifications. They also collaborated in the development of a Knitwear Technology module component specifically for this group of companies.

In 2002, the Confederation of British Wool Textiles commissioned the development of a more advanced Weaving Technology module for the woven fabric sector of the industry. This was followed by a more advanced module on Nonwoven Technology and a module on Textile Testing.

In 2004, in response to a call for proposals within the Leonardo da Vinci programme, KLITRA led a consortium of European educational and training organisations and companies to develop two modules on Carpet Technology and Hosiery Technology. These were the first modules developed in languages other than English. The consortium included Euratex, The Technical Universities of Liberec and Kaunas, KLITRA and Media Innovations Ltd (a spin-out company from the University of Leeds). Incorporating some content from previously developed modules and new content with contributions from industrial experts, these learning tools had to be produced in a completely new format requiring the development of new delivery technology to allow the content to be offered in Czech, French, Lithuanian and English.

Up to this stage, all the modules had been made available for study only through CD Roms. This was because the modules contained a substantial amount of video content and it is essential, to retain the learners interest, that the learner has almost instant access to the video without needing to wait lengthy periods for it to be downloaded. However, with the advent of increasing broadband speeds to 4 and subsequently 8 Mb/second, test showed that the content could be delivered via the internet with acceptable download times and performance levels. Therefore, in 2006, the same consortium, with the addition of Suleyman Demirel University and subsequently Namak Kemal University in Turkey commenced a project to develop two modules in Apparel Technology and Dyeing, Printing and Finishing Technology in the same languages and Turkish.

It is these four modules, Apparel Technology, Carpet Technology, Dyeing, Printing and Finishing and Hosiery Technology that are being updated, converted for internet delivery (Carpet and Hosiery Technology) and translated into Greek, Latvian, Portuguese, Romanian and Slovenian to provide the interactive learning tools within the eLiTA project.

5. The anticipated outcomes for the project The anticipated outcomes for the project are:

- A research report into ICT tools currently available to support textile qualifications in partner countries;

- A new learning module in Dyeing & Finishing – English, Greek, Latvian, Portuguese, Romanian & Slovenian;

- A new learning module in Garment Technologies – languages as above;


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- A new learning module in Hosiery Production – languages as above; - A new learning module in Carpet Manufacture – languages as above.

6. Format of the learning tools Throughout the development of the learning tools, the objective has always been to provide both a structured learning environment and a browse able resource.

Consequently the content had to be presented in a pedagogically logical sequence to lead the learner along a knowledge path. However, once the learner became familiar with the content, it should also be easy to locate and access information needed to refresh the user’s knowledge. Furthermore the learner should be able to evaluate their learning through challenging and stimulating questions which would also serve to focus on important points.

In addition, the content should not only provide information it should describe and explain concepts and encourage the learner to think and apply the knowledge gained. Where possible, the objective has also been to present and structure the information in sufficient breadth and depth to cover both basic and more advanced concepts. With the opportunity for internet delivery, the aim has now become for each module to be an online learning portal with direct links to other sources of information, notably companies who provide the technology. This enables the earner to familiarise themselves with applications of the technology and also to get information about the latest developments which also helps to keep the content up to date.

In summary therefore the features of the system are: - It has dual functionality: it provides both an exclusive structured learning

environment and a reference resource browser; - It assumes no prior knowledge of Textiles or Apparel; - It assumes no prior knowledge of computers; - It is simple to use with interactive features; - It enables learners to evaluate their learning and provides feedback to reinforce

their learning; - It has quick response - a minimum download time; - It has links to further information;

7. Structure of the learning tools The modules will be delivered through the learning portal www.elearning-textiles.co.uk (Figure 1).

Each module has an opening page with links to credits which presents an overview of the module (Figure 2) Access to the module content and other features is via clickable buttons and selectable text using a computer mouse.

To satisfy the requirements of being both a structured learning environment and a browse able reference resource the delivery of the content is menu driven as shown in Figure 3. Each subject is divided into topics that are ordered into as logical and sensible pedagogical order as possible. Likewise, within each topic there are pages compiled in a sequence that presents the information on each topic in a pedagogical sequence.


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Where appropriate, hypertext links (Figure 4) on specific text are included to take the learner to related pages in the same or other topics to provide them with further information.

Figure 1 elearning portal

Figure 2 – Opening page of Hosiery technology module


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Figure 3 – Module menu

Figure 4 - Video


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8. Future provision for textile and apparel education There is no doubt that elearning offers many benefits in terms of providing cost-effective education and training that suits both the time conscious needs of the learner and the employer when used to support training in the workplace. However it is also clear that, whilst it is very good in presenting factual and visual descriptive information and, as a learning portal, can provide ready access to other sources of information, it needs to be complemented by other modes of delivery. Therefore a blended learning approach is advocated incorporating: E-learning, Video delivery, Classroom, Books, Synchronous and asynchronous communication e.g. Internet chat rooms, email, In-company practical training.

The aim of such an approach is to utilise the most appropriate learning tool for the type of knowledge and information to be imparted.

9. Summary and conclusion This paper has presented an overview of the eLiTA project.

The aim of the project is “To support improvements in quality and innovation in vocational education and training systems, institutions and practices” through the further development of elearning modules in textiles and apparel.

“The European Textiles and Clothing industry … continues to represent one of Europe’s major industrial sectors with an annual turnover of 215 billion Euro and a total workforce of 2.6 million”. However, despite job losses in the Eurozone Textile sector, there is a significant demand for new workers due to the age of the workforce. This replacement demand is highlighted in the Skills for Business Working Futures 2004-

2014: National Report p.130 “the largest level of replacement demand will arise amongst machine and transport operatives … on average around a third of the current workforce will need to be replaced over the next 10 years”.

It is essential therefore, that elearning tools, such as those in the eLiTA suite of modules, are developed if the workforce is to be recruited, educated and trained to the level required to enable companies within the EU compete globally.

REFERENCES

[1] “TEXTAG” Final Evaluation Report for KLITRA Ltd, February 2009 – Glendevon Associates [2] www.elearning-textiles.co.uk

Recommender Systems for Smart Lifelong Learning

Ahmad A. Kardan, Omid R. B. Speily, Somayyeh Modaberi

Department of Computer Engineering and Information Technology

Amirkabir University of Technology, Tehran, Iran Email:aakardan, speily, [email protected]

Abstract The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. In this paper, we propose an evolving web-based learning system which can adapt itself to its users. More specifically, the novelty with respect to the system lies in its ability to find relevant content on the web, and its ability to personalize and adapt this content based on the system's observation of its learners and the accumulated ratings given by the learners. Hence, although learners do not have direct interaction with the open Web, the system can retrieve relevant information related to them and their situated learning characteristics. Lifelong learning scenarios have particular differences in their need for personalized recommendations that make not possible reusing existing general approaches of recommender systems. The paper describes those challenges and presents a hybrid proposal that combines different recommendation techniques to navigate learner in learning process and make lifelong learning system personalized.

Keywords: lifelong learning, recommender systems, personalization

1 Introduction Research on e-learning has gained more and more attention thanks to the recent explosive use of the Internet. The Lifelong Learning (LLL) paradigm supports the idea that learning should occur throughout a person’s lifetime (Santos and Boticario, 2008). This paradigm promotes a user-centered approach that removes social, physical and cognitive barriers, where dynamic support may foster attitudes and skills to improve the effectiveness of the learning process. In mediating this process, technology is playing an important role. In this sense, a dynamic support that recommends learners what to do to achieve their learning goals is desirable. Traditionally, Intelligent Tutoring Systems (ITS) intend to provide direct customized instruction to students by finding the mismatches between the knowledge of the expert and the actions that reflect the assimilation of that knowledge by the student (Santos and Boticario, 2008). Their main limitations are: 1) ITS are specific of the domain for which they have been designed (since they have to be provided with the expert knowledge) and 2) it is unrealistic to think that it is possible to code in a system all


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the possible responses to cover the specific needs of each student at any situation of the course.

However, the majority of current web-based learning systems are closed learning environments, where courses and materials are fixed and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. In this paper, we will propose an evolving web-based learning system which can adapt itself not only to its users, but also to the open Web in response to the usage of its learning materials. Our system is open in the sense that learning items related to the course could be added, adapted, or deleted. Our proposed e-learning system adapts both to learners and the open Web. In a traditional adaptive e-learning system, the delivery of learning material is personalized according to the learner model. However, the materials inside the system are a priori determined by the system designer/tutor. In open lifelong system, learning materials are automatically found on the web and integrated into the system based on users' interactions with the system. Therefore, although users do not have direct interaction with the open Web, new or different learning materials in the open Web can enrich their learning experiences through personalized paper recommendations( Tang and Mccalla, 2004). Other ability of our systems is working powerful in critical fields and high tolerance in unknown situation like new generation of science with related information shortage or new user with no specification of his interests. Another superiority of our systems is suitable architecture for social networks like facebook1. There is similarity between social networks and lifelong learning therefore we think we can use social networks in learning. We propose combination of different adapted recommendation algorithms to address lifelong systems requirements.

The organization of the paper is as follows: in section 2 we overview the related work done in recommender systems in lifelong learning (LLL), focusing more on recent systems. We introduce our solution including high level architecture and required details in section 3. The conclusion of the paper comes in section 4 along with some recommendations for future work.

2 Related work: Work on LLL systems is in initial stage, but improve quickly. In (Santos and Boticario, 2008) introduce inclusive scenarios of recommender systems and LLL and propose recommending strategies for LLL. In (Derachesler and Hummel and koper, 2007) propose a combination of memory-based recommendation techniques that appear suitable to realize personalized recommendation on learning activities in context of e-learning. As described earlier, our proposed e-learning system makes individualized recommendations of materials for learners chosen from a dynamically evolving paper repository. There are several related works concerning tracking and recommending technical papers. Basu (Basu et al,2001) define the paper recommendation problem as: "Given a representation of my interests, find me relevant papers." They studied this issue in the context of assigning conference paper submissions to reviewing committee members. Reviewers do

1 www.facebook.com


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not need to key in their research interests as they usually do; instead, a novel autonomous procedure is incorporated in order to collect reviewer interest information from the web. Bollacker (Bollacker et al, 1999)refine CiteSeer, through an automatic personalized paper tracking module which retrieves each user's interests from well-maintained heterogeneous user profiles. Woodruff (Woodruff et al, 2000) discuss an enhanced digital book with a spreading-activation mechanism to make customized recommendations for readers with different types of background and knowledge. McNee (McNee et al, 2002) investigate the adoption of collaborative filtering techniques to recommend papers for researchers. They do not address the issue of how to recommend a research paper; but rather, how to recommend additional references for a target research paper. In the context of an e-learning system, additional readings in an area cannot be recommended purely through an analysis of the citation matrix of the target paper, because the system should not only recommend papers according to learners' interests, but also pick up those not-so-interesting-yet pedagogically suitable papers for them (McNee et al, 2002). In some cases, pedagogically valuable papers might not normally be of interest to learners and papers with significant influence on the research community might not be pedagogically suitable for learners. Therefore, we cannot simply present all highly relevant papers to learners; instead, a significantly modified recommending mechanism is needed( Tang and Mccalla, 2004).

3 Proposed Approach We describe our system in four phases(figure 1) : 1)Input 2)Process 3)Output 4)Feedback Processing. There are three type of inputs, Actors that described later include four type of role. Candidate items are contents that recommender systems select N number of them for recommendation. Other one is input information such as user models, friend weights, learning map and so on that explain perfectly in section 3.1. All inputs process in process phase to make recommendation. Recommended items present to user and collect his/her feedbacks in output phase. Finally, by processing feedbacks system can update itself to predict and recommend better. Feedback processing phase provide restoration by reform user modeling, friends weight and other related essential information to increase system accuracy. Our proposed approach summarized in Fig. 2 with more details.

In figure 2 the generic view of our proposed approach is illustrated. According to figure four main phases is recognizable. Each of these phases will explain completely at following subsections.

3.1 Input phase In this phase four roles exist including: user, friends, group member and teacher. Friends are users that directly interact with targeted user. Interests and opinions of friends according to their similarity to targeted user have different weights. These weights are applied in producing recommendation. The other role is group member that indirectly interacts with targeted user and system uses them to give more accurate recommendations. If group member interests and opinions are similar to targeted user, system will recommend targeted user to add this member as his/her friend. By increasing


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FEEDBACK PROCESSING

number of friends and updating their weight a better clustering is made and consequently system gives a more accurate recommendation. Also this method works well when user has few friends. The other role is teachers who have enough knowledge about the discussed topics in learning group and they can be an intelligent agent. System can make a learning group without a teacher. This is a notable attribute of system especially when learning group topic is very update and advanced, so an adequate teacher can’t be found. Most important teacher works in this system listed as follows:

Fig. 1. Concept model of our Proposal

• Learning contents recommendations. • Submission of recommendation when the system recommendation value is

bellow 2 (Recommendation value is a parameter from 0 to 5 and calculates at the time of proposing it.).

• Submission of users’ annotation or summarization after they study learning content.

One of the important elements in lifelong learning system is learner modeling. Because of accuracy and efficiency of two part user modeling approaches (Kardan and Einavypour, 2008) we use a modified version of it. Figure 3 shows an overall view of proposed learner modeling approach. At first system hasn’t any idea about learner, so to accomplish this problem uses questionnaire and inviter learner model. For joining learning group each learner should at least have tow invitation from tow learning group members. Also he/she can alternatively answer the questionnaire includes questions about learner individual information such as: age, geographical location, religion, educations and more, as well as questions about the relation between learner and members who

INPUT PROCESS OUTPUT

Candidate Items

Actors

Input info

Processing unit

Recommendation

Updating unit

Feedback


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Valid Information

invite him/her such as: how much he/she knows inviters, how he/she be familiar with them and more. TLM0 shows learner temporary model at first stage (Burke,2000). After learner interaction with system, system validates TLM0 considering learner feedbacks, how much is the learner model close to real learner? , then TLM0 is updated to TLM1. This process repeats n time, the value of n relates to system efficiency, then TLMn convert to permanent learner model.

Fig. 2. Proposal for combining recommending techniques in LLL

Tem

pora

ry

Use

r M

odel

P

erm

anen

t U

ser

Mod

el

Figure 3: learner modeling

TUM TUM TUMi+TUMValidation

Validation

Validation

PUM

validatio


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The other input phase features are friends and group members learner model repository that is saved distinctively r. The amount of similarity between a learner and his/her friends is saved in weight unit. Last two features of this phase are learning map and pedagogic rules. Pedagogic rules define what and when a learning content should use. For example a difficult technical paper isn’t appropriate for a beginner. We propose ranking and tagging paper based on paper publication time, paper level according to learner (beginner, average, and expert) and teaching ways of teacher. Learning map has meaning relation with pedagogical rules. This map is saved for every learner and helps them to see their learning process. System using this map finds which content has been learned.

3.2 Process phase All processes and recommendation is done at this phase. We propose a mixture approach for making recommendation in lifelong learning systems. In contrast to common approaches that work with limited amount of content, our proposed approach let learner contact universal web and search needed content through web at time of learning process. As mentioned before CF isn’t proper approach for lifelong learning system because the lifelong learning system nature is working with varied and very detailed information. So using CF for lifelong learning system much information with no learner comment or enough comment will be made. To accomplish this weakness we mix it by an efficient approach that doesn’t need learner feedback very. Like (Joachims and Freitag and Mitchell, 1997) reinforcement learning is used for filtering presented documents and information to learner. In this system the WAIR (Web Argent for Information Retrieval) is used.

This architecture includes user interface agent, information filtering agent and information retrieval agent and with using search engines and learner profiles receives documents for learners. The main point of this system is constructing and updating learner profile. The profile at first is made of some key words learner inputs system and general learner characteristic likes language, educations, intelligence and other things is gotten by him/herself or by his/her friend. These key words during learner and system interaction and by receiving learner feedbacks are updated. Updating includes add new words to profile, omit some key words and change learner profile key words weight. Formally learner profile is a vector of weight like the fowling vector:

Content detail such as title,

Publishing date, user’s

annotation, set of comments, summery …

Date of reading

Figure 4: learning map indicate records about user’s activities


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>=< npppp wwww ,2,1, ,...,,

(1)

is equal to weight of word k and

According to the profile WAIR sends a query to search engines that every word existence probability is related to its weight in profile after receiving documents. Rank of each document likes i for profile p calculates according to two vector cosine. For system learning implicit and explicit feedbacks is received. Implicit feedback RE(i) that is received at beginning of system work is the points learners give to documents. Explicit feedbacks RI(i) includes learner study time, and links is followed by learner. Reward for each document is made of the combination all this rewards:

)()1()( iRiRr IEi δδ −+= (2)

Based on this reward learner profile updates as follow:

)( ,)(,

)1(, kii

ikp

ikp xIrww β+=+

(3)

In above formula I(Xi,k) is a threshold function that its output is 0, 1 and -1. After results are gained, contents are revised from the point of LLL rules. If any content contravenes LLL rules, they will be omitted. LLL rules made of learning rules and teaching ways is proposed by teacher according to learning map. Some sample of LLL rules come as follows.

LLL rule validation (user profile, content profile) If (level of content i=A) & (intelligence of user = 40) then reject content. If (language of content i=”English”) & (language of user = “Farsi”) then reject

content If(mastery level of user=A) & (Date of publishing content = 1990) then reject content.

… In addition to recommendations are gained from learner search, by investigating

friend uses and finding similarity between learner and their friends so recommendations produced based on CF. An important point in CF is used in our approach is the way of weighting to friends recommend. As mentioned before learner weights are kept in one place and at time of using CF these weights are used for assigning similarity. Like previous way the results of this approach are checked by LLL rules. Another list belongs to teacher recommendations. The teacher according to his content and learner recognition recommend to learner. These recommendations are checked by LLL rules to minimize human errors. Relations with them recommendations are checked are as follows:

1=pw

Search Items=Ii,Ij,…,Im Professor Proposal= Ii,Ij,… freinds Popular Items= Ia,Ir, Io,Ij,Ic,…,Is

Ufiltering=SI filtering results = LLL rule validation Filtering(Ufiltering,User Profile ) CF results= LLL rule validation Collaborative filtering( friends Popular Items, friends Weight) = CF(FPI, FW) Professor Proposal result = LLL rule validation Professor Proposal

Rec results = (filtering results U CF results U Professor Proposal results= IN,IN-1,IN-2,…,I0

Input

Process

Output


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Search Results

CF Rec Results

Teacher’s Recs

Chat with freinds

3.3 Output phase In this phase if the value of recommendation is bellow 2 the teacher should assign that a learning content is proper or not. But if the value of recommendation is more than 2 validation isn’t necessary. The value 2 is an empirical quantity and has been assigned for system efficiency.

Figure 5: recommendation results

3.4 Feedback Processing phase This phase happens when a learner has studied learning content. System can update itself, improve its recommendations by gathering learner feedback and analyzing it, updating learner model if it is necessary and design new learning map for learner. Feedbacks include information such as: paper level (from A to Z), edition type (weak 0, excellent 100), recommendation precise (from 0 to 100), usefulness percentage (from 0 to 100) and other things are mentioned by learner. Also learner can annotate or summarize the content has been studied. Every annotation saved with its author name and is useful for other learner wants to study those papers. Learner feedbacks make it possible to update weight of his/her friends. As friends have an important role in quality of system recommendation and modeling, by comparing learner model and other members system recommend most similar members to learner as a friend.

4 Conclusion and Future work Current LLL systems have been focusing on the interrelations between users and the system. Hence, the system, if deemed intelligent, must be capable of detecting users'

Recommendation

User can visit when his/her friend read this content by accessing his/her learning map Chat with friend about

Content Catalog

Previous reader of this content (one or more)


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needs, following their footsteps, and finally adapting to their needs. We argue that this is not enough. We have been ignoring the dynamics of the open Web. As such, we believe that two kinds of collaborations should be considered here: one is the collaboration between the system and its users; another is the collaboration between the system and the open Web in response to the changing needs of the users. A system, which can fulfill especially the second type of collaboration, would indeed help its users to keep up-to date to the dynamics of information on the Web. Currently, we focused on developing

REFERENCES

1 Journal Articles: [1] Basu, C, Hirsh, H., Cohen, W. and Nevill-Manning,C. (2001) Technical paper recommendations: a study in combining multiple information sources. Journal of Artificial Intelligence Research, 1, 231-252. [2] Bobadilla, J. Serradilla, F. Hernando, A. MovieLens (2009). Collaborative filtering adapted to

recommender systems of e-learning, Knowledge-Based Systems. 10.1016. [3] Zhang, B., Seo, Y (2001). Personalized web-document filtering using reinforcement learning. Applied

Artificial Intelligence, 15(7):665-685. 2 Conference Proceedings: [1] Bollacker, K.D., Lawrence, S. and Giles, C.L. (1999). A system for automatic personalized tracking of

scientific literature on the web. In Proc. ACM Conference on Digital Libraries (DL 1999), 105-113. [2] Herlocker, J., Konstan, J., Brochers, A., Riedel, J(2000). An Algorithmic Framework for Performing

Collaborative Filtering. Proceedings of Conference on Research and development in Information Retrieval.

[3] Joachims, T., Freitag, D., Mitchell, T. M(1997). WebWatcher: A tour guide for the world wide web. Proceedings of International Joint Conference on Artificial Intelligence.

[4] Kardan, AA., Einavypour, Y( 2008). Eliminating Anomalies in Learner Modeling Using Two-Partial Learner Model. ICEIT'08, IAENG.

[5] Olga C. Santos and Jesus G. Boticario (2008). Recommender Systems for Lifelong Learning inclusive scenarios. ECAI 2008 - Workshop on Recommender Systems, Patras, Greece.

[6] McNee, S.M., Albert, I., Cosley, D., Gopalkrishnan, P., Lam, S.K., Rashid, A.M., Konstan, J.A and Riedl, J. (2002) On the recommending of citations for research papers. In Proceedings of ACM International Conference on Computer Supported Collaborative Work (CSCW’02), 116-125.

[7] TANG,T. Mccalla, G.(2007). Smart Recommendation for an Evolving E-Learning System. Dept. of Computer Science, University of Saskatchewan 57 Campus Drive, Saskatoon, SK S7N 5A9, CANADA.

[8] Woodruff, A., Gossweiler, R., Pitkow, J., Chi, E. and Card, S.K. (2000) Enhancing a digital book with a reading recommender. In Proc. ACM CHI.153-160.

A Proposed Structure for Learning Objects Using Ontology for Effective Content Discovery

Ahmad A. Kardan1, Shima Zahmatkesh1

(1) Advanced E-Learning Technology Laboratory, Department of Computer Engineering

and Information Technology, Amirkabir University of Technology, Tehran, Iran E-mail: [email protected]

Abstract One of the major challenges in e-learning development is search and discovery of an appropriate learning object among the distributed content repositories. Although SCORM presents some approaches for content reusability, but efficient searching process is a significant problem yet. We need an effective searching mechanism for discovery and access to the required learning resources, to utilize them in our courses. But resource discovery within a heterogeneous collection of resources is a challenging problem. Semantic web has been proposed for resolving problems. Some approaches like ontology were proposed to overcome heterogeneity. Ontology represents a set of concepts within a domain, and also the relationships between those concepts. Therefore, by using ontology for metadata of learning objects, we can enrich the information content of the learning objects, and develop a better search methodology. In this work, according to our proposed ontology, we consider the structure of the learning materials in three levels: Learning Object, Content Object, and Content Fragment. Content Fragment is a content unit in a most basic form. Navigational elements enable the sequencing of content fragments in a content object. Therefore, the Learning Objects aggregate Content Objects to cover a learning objective. By focus on the structure of the learning materials, different kinds of learning materials were created. By using ontology, for these learning materials a rich metadata were shaped. By means of this kind of learning materials our ontology could be evaluated for effective searching. Keywords: E-Learning, Ontology, Metadata, Learning Object, Sharable Content Objects (SCO)

1 Introduction Using new learning methods is one of the main challenges. One of the methods having more emphasis on the speed of learning process and its customization is E-Learning. For facilitating the construction of knowledge and skills in the learner, learning activities should be aimed (Allison et al, 2005). One of the E-Learning goals is wide access to learning resources with higher quality and lower cost. Information technology has an important role to achieve E-Learning objectives.

In order to improve access methods to educational information, different standards were created such as LOM and Dublin Core. The SCORM standard was created for


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reusability of learning contents and better management of learning resources. The existing deficiencies of these standards lead to use semantic web and its technologies for effective learning. Semantic web mainly focuses on giving a well-defined meaning to resources, services, and information. It provides tools for knowledge representation and management, annotation of data and resources, discovery of services and resources based on their meaning and function, automatic composition of services, and inference over metadata and ontologies (Allison et al, 2005). For applying semantic web it is necessary to use ontology to describe resources and applications on the web. Therefore, rich metadata could be available by using ontology.

Using ontology, different projects have been developed in E-Learning domain. The CoAKTinG project (Page, 2005) was developed to advance the state of the art in collaborative mediated spaces for distributed e-Science through the novel application of advanced knowledge technologies. The OntoEdue project (Guangzuo et al, 2004) puts its emphasis on adaptability and personalization in learning by means of ontology. The EUME Onto (Amorim et al, 2004) is an educational ontology that contains concepts of learning design, learning contents and learning resources. Weihong proposed an Integrated Semantic E-Learning Platform. This platform is an approach to integrate content provision, learning process, and learner personality (Weihong et al, 2006). The other paper presented a domain ontology which is used for sharing content and services between repositories (Xin-juan et al, 2007).

The rest of this paper is organized as follows: first, we show the overview of SCORM standard, and Semantic Web, to establish necessary fundamental for the rest of the paper. In section 4, we describe ontology and introduce some parts of our ontology in detail. Section 5 shows the process of creating learning objects which could be used with the proposed ontology. In section 6 we sketch out future works. Finally, in the last section the conclusion is provided.

2 SCORM Standard Learning object is a small single unit of information that at least covers a single learning objective. Learning objects are sharable and could be reused in different courses. Each learning object contains a variety of information, but they need a standard interface for communication and combination with other learning objects to compose an e-course. SCORM presents a mechanism for share-ability and reusability of learning objects, known as Sharable Content Objects (SCO's) (Ostyn, 2007). Therefore, SCO's could be used to make different courses, reducing time and cost of content development, and could be delivered by different LMS's (Yang and Ho, 2005).

“The SCORM was created by the Advanced Distributed Learning initiative (ADL), and considers six key requirements: Accessibility, Adaptability, Affordability, Durability, Interoperability, and Reusability” (Mackenzie and Baeini, 2004). The SCORM is actually a set of related documents. There are three main SCORM documents: Content Aggregation Model, Run-Time Environment, and Sequencing and Navigation: The SCORM Content Aggregation Model (CAM) document deals with the assembly, labelling and packaging of Web-based learning contents. The CAM explains the rules and mechanisms by which individual files can be combined into Sharable Content Objects


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(SCOs) and how SCOs can be combined to form Organizations. A Content Package is comprised of two main components: the Manifest file and the physical files. The manifest is an XML file that contains metadata about the package, organization structures that describe the structure of the content, and an inventory of the content resources in the package (Mackenzie and Baeini, 2004).

3 Semantic Web The semantic web is an extension of the World Wide Web in which content can be expressed semantically, and can be read and used by software agents. By getting semantic to the contents, they could be found, shared and integrated more easily. At its core, the semantic web comprises a philosophy, a set of design principles, and a variety of enabling technologies. Semantic web help us to analyze different types of data including the content, links, and also transactions between people and computers.

The semantic web architecture supports content with formal semantics. Thus, the contents on the web can be discovered and used by automated agents. This will enable them to reason about the web content, and produce an intelligent response to unforeseen situations (Stojanovic et al, 2001). Semantic web consist of different layers and use variety of tools and technologies like XML, RDF, RDF Schema, and OWL (Wikipedia, 2008).

Learning contents beside the main content have some semantic annotation and metadata. Thus using semantic web, finding a desired content could be facilitated. Metadata is structured data which describes the characteristics of the other data. it is used for data management and searching content resources. Metadata provides a common set of tags that can be applied to any content resource. Therefore, contents can be describe, indexed, and searched, as a reusable content (Stojanovic et al, 2001). Therefore, contents can be described, indexed, and searched, as a reusable content.

In the E-Learning community different metadata standards are emerging to describe content resources like RDF, Dublin Core, and LOM (Hodgins and Duval, 2002). Also different communities have developed their own metadata. Because of the variation and heterogeneity, different metadata can not interact with each other. “For creating a common understanding between terms in various metadata, vocabularies can be helpful. From the learner point of view, the most important issues for searching learning materials are” (Stojanovic et al, 2001):

Content: What the learning materials are about. Context: In which form learning material is presented. Structure: How a set of learning materials merge and create a learning course. Therefore, by using ontology in each of the above mentioned issues, both instructors

and learners can get efficient results with regard to designing and accessing courses, respectively. Consequently, semantic web can provide suitable platform for searching the desired learning contents. References

4 Ontology Ontology is a data model that represents a set of concepts within a domain and the relationships between those concepts for representing and describing knowledge.


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Ontology suggests a formal description and common understanding of a specific domain, and Ontology generally describes (Wikipedia, 2008):

Individuals: the basic or "ground level" objects Classes: sets, collections, or types of objects Attributes: properties, features, or characteristics, or parameters that objects can have

and share Relations: ways that objects can be related to one another Events: the changing of attributes or relations For coding ontology, different languages have been created and the most important

one is OWL. It is a widespread, expressive language that in terms of the ontology allows the use of external reasoning to compute the consistency of the model, classifying the ontology, query the model and retrieving individuals (Vega-Gorgojo et al, 2006).We use Protégé editor (Protégé website, 2009) to show our ontology (Kardan, 2009). This editor provides a graphical view of classes, and a primary class called "Thing" is the root class of all classes.

“The structure of learning objects was specified in the proposed ontology. In this structure, three elements were identified: Content Fragment, Content Object, and Learning Object. A Content Fragment is a content unit in its most basic form, such as text, image, audio, video, animation, table, chart, and so on. Navigational elements enable the sequencing of content fragments in a content object. Content Objects consist of some Learning Objects which cover a learning objective. These elements appear as classes in the proposed ontology” (Kardan, 2009).

As mentioned in section 2, SCORM presents a mechanism for share-ability and reusability of learning objects, known as Sharable Content Objects (SCO's). For implementation and evaluation of our ontology, Sharable Content Objects (SCO) was used as learning objects to attain reusability.

In Figure 1 subclasses of Content Fragment could be seen. A Content Fragment could be text, image, audio, video, animation, table, chart, and so on.

Figure 1. Different Content Fragment


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A Content Object represents the content of Learning Object. The contents of an e-course could use examples, questions and answers, exercises, descriptions, lectures, simulations, and so on. As being illustrated in Figure 2, subclasses of Content Object introduce different types of learning resources which are presented in learning e-content. The Learning contents could be delivered to learners in different manners such as Description, Explanation, Example, Exam, Exercise, and Question and Answer.

Figure 2. Content Objects

5 Implementation of the Learning Objects For implementing the proposed ontology, a collection of e-learning contents is necessary. Different concepts of e-learning content domain have been introduced in the proposed ontology. These concepts are used for a set of e-learning contents. Rich metadata for the e-learning contents was created by using these concepts. User can use these concepts and an interface to search variety of e-learning contents on the web.

SCORM standard is an acceptable standard in e-learning contents domain. Most of the learning management systems use SCORM standard to manage e-courses. On the other hand, content designers prefer to create e-learning contents according to SCORM standard. According to the aim of our proposed ontology which is searching the existed contents to reuse them in other course, a set of reusable contents was necessary. Reusability can be guarantied by using SCORM standard and creating a set of SCO’s. The usage of this standard has other advantages. The test and evaluation of the proposed ontology become possible in different learning management systems which are SCORM compatible. Under SCORM definition a learning content could be packed as a Sharable


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Content Object (SCO) if it has at least one learning objective. It is mentionable that each SCO includes different files.

To test our proposed ontology, the topic of E-Business and E-Commerce was selected to create an appropriate e-content. In this topic, different issues like E-Commerce Mechanisms, E-Commerce Transactions, Market Research and Online Advertising, and E-Commerce Support Services were introduced.

After selecting a suitable resource for the content, different types of content based on different multimedia capabilities, and according to our ontology were designed and created. The format of the files that being used in the SCO's is not limited by SCORM; so based on unrestricted file's format, a collection of learning contents was produced in Flash and html format.

The structure of learning objects was introduced in our ontology. In this structure, three elements are being identified: Content Fragment, Content Object, and Learning Object.

In this work, a set of Content Objects was created. For the chosen topic we created different types of Content Object like Description, Explanation, Question, Self-assessment, Exercise, Description, Example and Exam. For creating these Content Objects, different kinds of Content Fragments were utilized. Based on our ontology a Content Object is being made of some Content Fragments such as Text, Animation, Table, Video, Image, Audio, and Graph.

We used Flash and html format, because they are capable to support different kinds of Content Fragments. Each of the Flash or html files represent as a Content Object. They include some Content Fragments. The chosen topic is represented in different scenarios. For example in a scenario it is represented in text format and in addition with sound or image. Some of the contents have tree structure for interaction with learner. Video and animation are also used to create parts of the content required for the selected topic. Drag and drop technique also used in questions, exams, and self assessments.

In this work, about 200 files composed as Content Objects were created. They were designed according to the structure of the Learning Objects which are described in our ontology. In next step metadata was created for these files. All of the files and their metadata were put in a content repository. Evaluation of the proposed ontology was done by implementing a semantic search on different repositories

6 Future work In this paper, considering the proposed structure of learning objects, we recommended a process to create a set of learning objects which can use our ontology to creating metadata. In the next step, using ontology concepts, we create metadata for learning resources. Evaluation of the effect of using this metadata will be done at AELT Group, in Amirkabir University of Technology, by putting these resources in different repositories around the campus, and conducting professors to search for desirable learning objects.

7 Conclusion The access to the desired content in a collection of them is one of the important challenges in E-Learning domain. Regarding distributed resources, heterogeneity and


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lack of universal standard are the main problems. To tackle these problems different solutions have been presented such as creating standards for content development, and semantic web for semantic search.

In this study, the structure of the Learning Object is used for creating Content Objects. This structure was introduced in our previous work (Kardan, 2009). Creating a set of Content Objects is necessary to evaluate the proposed ontology. Therefore, in this work different types of Content Objects including variety of Content Fragments were designed and produced. In the next step it will be shown that metadata could be attached to these Content Objects according to the proposed ontology for implementing a semantic search.

8 Acknowledgement Hereby we would like to express our thanks to Iran Telecommunication Research Centre for the dedicated grant to this work under the contraction numbered T/500/20616, and dated on 18.March.2008.

REFERENCES

Allison C., et al, (2005): Services, Semantics, and Standards: Element of Learning Grid Infrastructure.

Applied Artificial Intelligence, 19, 861–879. Amorim R., et al, (2004): An Educational Ontology based on Metadata Standards. Guangzuo C., et al, (2004): OntoEdu: A Case Study of Ontology-based Education Grid System for E-

Learning. Journal of Global Chinese Society FOR Computers in Education. Hodgins W., and Duval E. (2002): Draft Standard for Learning Object Metadata. Technical Report: Learning

Technology Standards Committee of the IEEE. Kardan A. A., Zahmatkesh S.(2009): A Proposed Ontology for Effective Searching of Sharable Content

Objects Emphasizing on Learning Objectives. In 6th International Conference on Information Technology : New Generations, Las Vegas, Nevada, USA.

Mackenzie G. and Baeini M. (2004): A (Mostly) Painless Introduction to SCORM. Ostyn C. (2007): In the Eye of the SCORM, An introduction to SCORM 2004 for Content Developers. Page K. R. (2005): Collaboration in the Semantic Grid: a Basis for e-Learning. Applied Artificial

Intelligence, 19, 881-904. protégé web site (2009): http://protege.stanford.edu/ Stojanovic L., at al, (2001): E-Learning Based on the Semantic Web. In World Conference on the WWW and

Internet, Orlando, Florida, USA. Vega-Gorgojo G., et al, (2006): A Semantic Approach to Discovering Learning Services in Grid-based

Collaborative Systems. Future Generation Computer Systems, 22, 709-719. Weihong H., et al, (2006): An Intelligent Semantic E-Learning Framework Using Context-Aware Semantic

Web Technologies. British Journal of Educational Technology, 37, 351-373. Wikipedia (2008): http://en.wikipedia.org/wiki/Ontology_computer_science Wikipedia (2008): http://en.wikipedia.org/wiki/Semantic_web Xin-juan Z., et al, (2007): Ontology Based Sharing and Services in E-Learning Repository. In International

Conference on Network and Parallel Computing. Yang C. T. and Ho H. C. (2005): An e-Learning Platform Based on Grid Architecture. Journal of information

science and engineering, 21, 911-928.

Interdisciplinary and Specialized Programmers Used in the Practical Part of Teaching

a Technical Course

Irina-Isabella Savin1, Ioana Pristavu2

(1) College teacher, Eng., 1st teaching rank, PhD candidate, “Ioan C. Ştefănescu”

Technical College, Str. Socola nr. 51-53, Iaşi, Romania


(2) International relations officer, „Alex. I. Cuza” University, B-dul Carol I, Nr.11 Iaşi, Romania, E-mail: [email protected]

Abstract This paper deals with a concept of the present pedagogy which combines scientific and technical information with students’ practical applications. An interdisciplinary education means that information taught to students is the result of a mixture of different disciplines: physics, chemistry and textile finishing. Being a computerized didactical-scientific-technical „filter” of these disciplines and their practical applications in the laboratory, this paper becomes a useful, attractive and stimulating teaching instrument both for the students and the teachers. Combining formal and non-formal education, students are able to achieve necessary skills and abilities for their future work in a computerized technical environment.

Keywords: AeL lessons, Spectrophotometer, Dye, Diagrams

1. Introduction Starting from the idea that lessons have to be attractive and bring new information to students, this paper focuses on a practical application for the textile finishing discipline. This course is taught in the 12th form of the technical high schools specialized in textile-leather and it combines practical and theoretical information from other fields – physics, chemistry – with the specialized ones.

AeL lessons are a precious help, as through animation students get a better glimpse of the chemical, physical and technical phenomena they are taught. Interdisciplinary helps students achieve general and specific abilities, as well as practical skills related to working with technical equipment.

AeL lessons in the field of chemistry (for instance natural and synthetic coloring agents, water) (http://advancedelearning.com/materiale/new/chi/) and physics (light dispersion) (http://advancedelearning.com/materiale/new/fiz), combined with specialized ones on the coloring of textile materials (dyeing and printing operations) offer students the chance to learn how to interpret the diagrams which result from the analysis of dyeing agent concentration in different situations, using the Spectrophotometer Kontron.


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As AeL lessons in the fields of chemistry and physics are well-known, this paper deals with the specialized practical application – coloring cellulose textile materials with specific dyeing agents.

When dyeing textile materials, we need to take into account various factors which may have an influence upon the finished material – the Microner index, dyeing agent concentration, work parameters, etc. (Bucurenci and Bucurenci, 1994).

The case study presented here deals with the dyeing operation of materials made of 100% cotton. Different dyeing samples were prepared and tested with the help of the spectrophotometer Kontron.

The paper consists of the following parts: • Introduction • Part I presents a history of the spectrophotometer and some notions on the dyeing

of different cellulose textile materials with various specific dyeing agents; • Part II describes the practical application which uses the Spectrophotometer

Kontron – variations in the concentration of the one dyeing agent (the tub dye) used in the experiment, depending on the wave length, time, number of determinations, initial dyeing concentration, etc.

• Conclusions; • Bibliography. Experimental data interpretation leads to a correct choice for the work parameter

values and to obtaining textile materials which prove to have good and very good technological resistance.

Part I

Modern equipment used in the instrumental measurement of color

In the 50s only 10 spectrophotometers measuring the dyeing concentration were in

use. In the 60s, the most per formant one needed at least 10-15 minutes to read the textile sample reflexion values at 16 points, values which were then used in more complex calculations. During the 70s, the measuring time was reduced to less than a minute and then to only a few seconds.

The prices one had to pay for these devices were very high: • In the 70s, it was the equivalent of 30 Volkswagen cars; • In the 90s, it was the equivalent of 3-4 Hyundai cars.

Colorimetry is nowadays represented by a large variety of spectrophotometers and colorimeters connected to a computer and having an internal memory unit. Newer results show a significant growth of the measuring speed, precision, reproducibility and application flexibility. An important optical change is the extension of the wavelength to the infrared area (which is important for the measurement of the camouflage materials) as well as the ultraviolet area (important for the measurement of the fluorescent bleaching agents).

The features of the spectrophotometer are the following: • Double spot measurements every 10 nm; • Using slots with a good reproducibility rate;


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• A range of the reflex ion values of 0-200%; • The existence of some light source; • Manual or automatic calibration.

The big brands in the field (Data color International, Macbeth, Minolta, Tree Point) modify and upgrade their programmer packages in order to continuously improve the answers that the equipment offers the beneficiaries. An important characteristic of the software used is that Windows now provides us with great graphical operational features. The continuous upgrade of the measurement equipment leads to an improvement of the existing solutions, but as far as the dyeing recipes are concerned, the final decision is always taken by the professional colorist.

Figure 1. Spectrophotometer Figure 2. Spectrophotometer Keyboard and monitor area for the analysis of the bath solutions

1.1 Dyeing with direct dyes Direct dye molecules contain:

• Chromospheres groups which can be di or poliazoic; • Aminic or hydroxylic auxochrome groups; • Soluble sulphonic groups.

Direct dyes are a fine dust with a high water solubility value and they come in various colors and shades. The factors which influence dyeing are: coloring agent and auxiliary substance concentration, temperature, ph of the dye bath, time length of the dyeing process (Mureşan, 2000, Butnaru and Bertea, 1998).

The dyeing procedures are the following: a) The discontinuous procedure – when the dye bath is low alkali nous or neutral;

either dark or light shades can be achieved through this procedure. b) The semi-continuous procedure – for cotton and viscose materials. c) The continuous procedure – which is more difficult to use because of its complex

technology. The dyeing substances are: NaOH, Na silicate, industrial salt, and direct coloring

agent. The dyed material is treated again with the aim of improving the dye resistance.

1.2 Dyeing with tub dyes Tub dyes have been used for a long time now, beginning with the time when they were extracted from plants and cockles.


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After synthesizing indigo in 1897, the first anthrachinonic dye was synthesized in 1901. This type of dyes can be used in order to achieve all shades. They need to be diluted in order to be used for dyeing.

The factors which influence dyeing are: coloring agent and auxiliary substance concentration, temperature, time length of the dyeing process, ph of the dye bath.

Dyeing procedures are: discontinuous, semi-continuous and continuous. The dye resistance is good and very good (Butnaru and Bertea, 1997).

Part II Determining dye solutions concentration in the dye bath

The method is based on determining the concentration depending on the wavelength,

as it is well-known that every color matches a certain wave-length in the UV spectrum. The dye concentration is determined with the help of a measuring curve. The tables

with the concentration values for the one dye can be found below, together with the experimental data – tables and curves of the dye concentration – determined through experiments using the Spectrophotometer Kontron (Butnaru and Bucur, 1996).

Table 1. Determining the concentration of the tub dye in the dye bath before the dyeing operation, on the Spectrophotometer Kontron

Wavel No. Value_S Value_S

350.0 1 0.9348_1 0.9340_2 450.0 2 1.1468_1 1.1474_2 550.0 3 1.1994_1 1.1983_2 650.0 4 1.2028_1 1.2024_2 700.0 5 1.2026_1 1.2020_2 750.0 6 1.1020_1 1.1020_2 850.0 7 1.1200_1 1.1223_2 900.0 8 0.6466_1 0.6471_2

Table 2. Determining the concentration of the tub dye in the dye bath after the dyeing

operation, on the Spectrophotometer Kontron

Wavel No. Value_S Value_S

350.0 1 0.6785_1 0.6815_2 450.0 2 0.4608_1 0.4619_2 550.0 3 0.6570_1 0.6600_2 650.0 4 0.8078_1 0.8099_2 700.0 5 0.0339_1 0.0349_2 750.0 6 0.1549_1 0.1543_2


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Figure 3. Determining the concentrated solution of the tub dye on the Spectrophotometer Kontron

Figure 4. Determining the diluted solution of the tub dye on the Spectrophotometer Kontron


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Conclusions

• based on these diagrams and tables, when dyeing cellulose materials, one can calculate the optimum values of the coloring agents used, depending on various parameters – wave length in order to determine color intensity, time length in order to obtain a uniform dyeing, degree of recovery of the dye from the dyeing bath in order to use it for further dyeing operations;

• cellulose textile materials will be better quality ones as flaws will thus be removed (Bertea, Bertea and Butnaru, 2000);

• students will be better trained in using specialized technical equipment; • students will acquire various skills in different fields – chemistry, physics, textiles –

thanks to the interdisciplinary character of the lessons and the practical applications.

REFERENCES Bertea, A., Bertea, A. and Butnaru, R. (2000): Textile fibers – chemistry and structure, A 92 Publishing

House, Iaşi Bucurenci, E., Bucurenci, I. (1994): Equipment and technology for finishing textile products, vol. II,

Didactical and Pedagogical Publishing House, Bucureşti Butnaru, R. and Bertea, A. (1998): Finishing textile products, Rotaprint Publishing House, Iaşi Butnaru, R. and Bucur, M. S. (1996 ): Physico-mechanical analysis in cellulose textile finishing, Dosoftei

Publishing House, Iaşi Butnaru R. and Bertea A., (1997), Ecological and Toxicological Aspects of the Chemical Textile Finishing,

Dosoftei Publishing House, Iaşi Mureşan, A. (2000): Processes and equipment for finishing textile products, Gh. Asachi Publishing House,

Iaşi PătruŃ, B. and Miloşescu, M. (1999): Informatics, Teora Publishing House, Bucureşti The Romanian Standards Institute (1980): A collection of standard values connected to the textile industry,

Bucureşti http://advancedelearning.com/materiale/new/chi/85_coloranti_naturali_sintetici/M3/index.html http://advancedelearning.com/materiale/new/fiz/71_Prisma_optica_Dispersia_luminii/M6/index.html http://advancedelearning.com/materiale/new/fiz/71_Prisma_optica_Dispersia_luminii/M7/index.html

Research Project on Implementation of Open Distance Learning Method in University Education

Tudor Bragaru1, Ion Craciun1

(1) State University of Moldova

60 Mateevici str., Chisinau, Republic of Moldova E-mail: [email protected], [email protected]

Abstract This paper outlines the findings of the research project in relation to implementation of e-Learning (computer assisted teaching, including distance learning) and its conceptual, terminological, technological, methodological and pedagogical aspects The paper also outlines the results of the experimental testing of the two integrated software platforms designed specifically for supporting e-Learning that are in use at the State University of Moldova (SUM): AeL (Advanced eLearning) and Moodle (Modular Object-Oriented Dynamic Learning Environment).

Keywords: AeL, Moodle, e-Learning, Open Distance Learning (ODL), e-Testing, Information and Communication Technology (ICT)

1. Introduction The increasing importance of Open Distance Learning (ODL) in the modern society driven by “knowledge” is emphasized in a number of electronic and paper sources. ODL is acknowledged as an area of priority in numerous countries developmental strategies. The role of ODL in modern society increases as the requirement to quality of knowledge increases and the importance of teaching quality continues to grow. The requirements to qualification of specialists in various areas are more stringent, which calls upon the improvement in quality of education and is reflected in society’s need for the reform of the educational system.

Digital, electronic and multimedia educational materials become a credible source of bibliography and imaging for various subjects and professors become better acquainted with the specific ways of preparation to educational activities using Information and Communication Technology (ICT). There are more and more educational institutions around the world operating exclusively through the Internet, delivering either a full cycle of subjects for a degree or offering specialized courses for a wider range of users “(Brut, 2006)”.

In the Republic of Moldova, the following project was implemented in order to promote the reform of the educational system:

Project 08.815.08.04A “Development and application of innovative methods in distance learning" runs as part of the larger National Program “Development of the Scientific and Technological support for the growing informational needs of the society of


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Republic of Moldova (RM)". The project commenced in 2008 and is planned to be finalised in 2009. During the project a number of research activities and experimental tests have been performed with the aim of integrating the innovative methods and modern information technology, including ODL, with University education. “(08.815.08.04A project, 2008)”.

At the start of the project the research team included 10 members: 2 university professors, 2 PhD students, 3 competitors, 2 masters in informatics and 1 student. In 2009 the team expansion has been separately financed. This resulted in engaging of 4 additional university professors and 5 future tutors, who will participate in elaboration, implementation and testing of the digital contents of the project.

Objects of research activities related to various aspects of implementation and delivery of ODL, including methodological, technological, pedagogical and infrastructural issues. The starting point of ODL’s implementation is a pilot program offering the Masters Degree at the State University of Moldova (SUM), Faculty of Mathematics and Information Technology during the academic year of 2009-2010.

The following can be considered amongst the most significant results of the project’s research activities:

1. Adoption of local distance education concept “Distance Learning: Concept and Terminology. Initiation Guide", authors Bragaru Tudor, Gheorghe Capatana, Ion Craciun, Chisinau, SUM, 2008;

2. Adoption of local Regulations of ODL for State University of Moldova, Ion Craciun, T.Bragaru, Gh. Capatana;

3. Development of the information resources for distance education, authors T. Bragaru, Vs. Arnaut, I. Craciun;

4. Development of methodological aspects (Bragaru T., Cirhana V., Craciun I. Development of the information resources for distance education , Chisinau, State University of Moldova, 2009; Bragaru T., Cirhana V., Craciun I. Computer assisted testing. Methodology. Chisinau, State University of Moldova, 2009; and other user guides).

5. Research, testing and adoption of hardware and of the software platform necessary for carrying out of the formal distance learning education that consists of 2 components: Moodle (main platform) and AeL SIVECO (second platform).

6. Development and maintenance of the Web page designated to ODL, creation of a virtual community with the interest in the relevant topics, further advertising of ODL and of the innovations in delivering traditional education (http://idd.usm.md).

Successful implementation and continued development of ODL at the State University of Moldova and in Republic of Moldova in general requires a large scale preparation of teaching professionals (including professors, authors of study units’ contents, tutors and managers) through systematic training courses, seminars, conferences, etc.

2. Research Project’s Terminology and Concept Research with respect to terminology promotes a dialogue between different users of the modern types of ODL and serves the purpose of standardisation of the terminology in the


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area, exchange of information and free access to information. The guidance developed within the project’s framework “(Bragaru and Capatana and Craciun, 2008)” can be accessed by general public on http://idd.usm.md.

Electronic education, e-Learning, distance learning are examples of the extension without limitations of the traditional form of education, carried out with the assistance of ICT “(Bragaru and Capatana and Craciun, 2008)”, and as such electronic education method is fundamental to modern learning.

This form of learning has emerged as a necessity of a continuously changing society and currently represents a real challenge for educational system. Electronic education is a generic term covering numerous educational scenarios where there is a significant use of the ICT. Some of the terms that one can come across include: e-Teaching, e-testing, e-Training, e-Education. Semantic representation of the concept of e-Learning also includes terms Online, Virtual, Web based, Internet based learning, computer-assisted learning, Internet-based education, learning through digital television and satellite media, etc. (Figure 1).

Figure 1. Semantic representation of the e-Learning concept

(adapted based on ”(Rosca I. Gh. and Zamfir G., 2002)”) Thus, e-Learning is a wide term meaning a variety of educational situations, which

rely significantly on the utilisation of information technology and communications. Definition wise, the semantic interpretation of e-Learning links with the assisted training, multimedia training, online training (online learning), virtual training, flexible training etc.

In a more narrow sense e-Learning represents one type of distance education that is offered by an institution, which provides study materials in sequential and logical manner that allows utilisation of these materials by students in their individual ways. Carrying out of this form of education is done via the Internet. Internet thus represents the environment for distribution of materials as well as a communication channel between the participants of the educational process. (http://elearning-forum.ro/resurse/a1-elearning.html).

3. e-Learning Environment In essence, e-Learning environment consists of a number of components and dimensions and is defined in a number of ways, such as organisational, technical, technological, operational, pedagogical, with the specific features determined by the supporting digital technology that covers a wide range of applications and educational processes.

From a pedagogical point of view, e-Learning environment offers a modern method of studies, teaching and learning based on digital technology, networking and multimedia resources. This method allows the accelerated exchange of information and knowledge,


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including ways of understanding or interpretation, between the teacher and the student anywhere, at any time as well as on demand. The result is the fast and efficient education process.

From a technological point of view, e-Learning environment represents a technology for maintenance of the processes of teaching, studying and learning which comprises authorisation, distribution, evaluation and administration of the courses’ content and other materials of didactical nature. This maintenance of the teaching process is realised through utilisation of digital, communication and multimedia technologies.

From the contents point of view, e-Learning environment includes the following: • databases and knowledge bases formed by links to all materials placed within

Web-sites (courses, study guides, syntheses, etc), accompanied by explanations and interactive directions as to finding and identifying the subjects of interest. It represents a virtual library, which is easily accessible and makes available to students and others participants of the process the information that theoretically can not be limited by volume of knowledge and can be from any area of activity. Information can be accessed individually or within any established training programs, free of charge or at cost;

• on-line support represented by forums, discussion groups (chat rooms), on-line news bulletins, emails or messenger applications (Microsoft and Yahoo Messenger). These are interactive tools that offer interested parties a possibility of asking questions and receiving quick or immediate answers;

• means of teaching assisted by digital technology From a functional point of view, e-Learning environment includes the following

components: • e-Learning platform, which represents software and hardware support of the

electronic teaching, studying and learning processes; • e-Learning resources, which include all data of interest in e-Learning environment,

and consist of the following: knowledge, represented by all knowledge resources that are available for students

in all areas during the whole educational process; information that defines user identity and roles in relation to any resources in e-

Learning environment. Depending on the role the user might be a student (beneficiary of knowledge), a professor (provider of knowledge addressed to student and creator of teaching strategy), or an administrator (the one who ensures normal functioning of the e-Learning system and is not directly linked with the teaching process)

strategy that define methods of teaching, learning and efficient assessment, tailored to the complexity of the educational objectives (e.g. for business or general interest) and to specific features of each type of education (full time and part time training or open distance learning). Strategies are also tailored to behavioral differences of students based on age and possibilities of direct communication (through classrooms) or indirect communication (through the use of digital technologies of communication) with the professor. Strategies are further tailored to modern forms of education (teaching, learning and assessment) which may include virtual classes, Web-based training, etc.


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An e-Learning platform is a software environment available through the internet and which restricts the access to its internal operations. This is achieved through assigning of usernames and passwords, where every user has access to different functionality features of the system depending on the rights assigned by the administrator.

An e-Learning platform can be better or less functional depending on its component hardware and software (servers, networks, internet connections, operational systems, administration of databases, web applications, etc.). In this context it is a software product designed for ultimate user (student, tutor, didactic stuff or program administrator).

3.1 AeL Platform for University Distance Learning The Well-known system of e-Learning AeL developed by SIVECO Romania “(http://www.advancedelearning.com, http://www.siveco.ro)” that is accessible on the corporate site of SUM at http://siveco.usm.md:81 is used in all schools and lyceums in Romania, in over 60 schools in Republic of Moldova and in some other countries. This system allows the electronic synchronous, asynchronous and open distance teaching and instruction and includes knowledge assessment system. This product can be applied at any level (undergraduate, graduate and post-university degrees) and is suitable for all forms of instruction (full time or part time university studies, distance learning). AeL can quickly and objectively assess students’ knowledge, provide feedback to students on their performance, it offers corrective activities, guides and assists in better absorption of the studied materials.

It should be noted however that while AeL operates sufficiently well within the local networks, it is not so effective for distance learning operating through the Internet, even at the speed of 100 Mbps, sustained by the network. This is possibly due to the weakness in settlings or weaknesses of design, etc. The supplier from who SUM acquired the AeL platform could not satisfactorily resolve this problem during the one year duration of the pilot project. As a result of our experimental test runs we came to an assumption that the problem arises due to the design issues, however this is a separate discussion altogether.

Among the other shortcomings that limit the efficient use of the AeL platform for carrying out higher education e-Learning is the system’s poor documentation and insufficient support by the developer and distributor of the product, who is mainly concerned with different issues and does not have enough interest in the successful implementation of this product for graduate and post-graduate university education processes. Another issue was unsatisfactory test runs of the system in the distance learning mode through the Internet. AeL's success for schools and colleges is rather supported by the teaching content offered within the product, as opposed to the functionality of the platform.

Several universities in Romania and SUM, have not been successful in implementing this system for their formal distance learning programs, abandoning the system after few years of pilot operation. This situation might change in the future.

3.2 Moodle platform for university distance learning. From the performance point of view Moodle “(http://www.docs.moodle.org/)” is one of the most powerful and most commonly used open platforms for e-Learning. This


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platform is being currently implemented at SUM, including being tailored in order to suit the processes of teaching and assessments of students for both distance learning and traditional methods of full-time graduate degree studies. (please refer to http://moodle.usm.md for more details).

Moodle platform is a software of the ‘open-source’ category, which constitutes a considerable advantage. Based on delivery, development, access, etc this system is considered to be substantially different from that of the AeL platform. The teacher creates all processes necessary for studying a subject (study unit contents, practical exercises, lectures, tests, supporting materials for student’s information, etc). Students can then take over the whole educational activity and work through the materials in the independent mode, including going through lectures, practicing the exercises at the agreed timing (activities can be planned for particular calendar days), then the feedback is provided to the student as to how well he/she scored in a particular activity.

This system does not include libraries of lectures or tests, unlike AeL, however, it has a powerful engine for generating the assessment tests with numerous types of questions. The lack of lecture and test libraries is compensated by the fact that in the present market one can find educational materials of the content that’s more diversified and tailored than that available through AeL libraries, the content of which is predominantly oriented towards college study subjects.

The Import-export functionality of the digital educational resources in Moodle is of a higher quality and ensures compatibility with different formats (GIFT, TXT, XML) as well as with isolated systems for e-testing. These features ultimately allow significant time savings for the professors – authors of study units contents or questions for tests. Tests can be built in a very flexible manner. The same test might include different categories of questions with different degrees of difficulty. Access to study units may be restricted by passwords and keys.

After registration and enrollment students gain access to methodological and didactical materials recommended by the responsible course administrator, which can all be downloaded and studied at their own pace at home, or at their work place, or at other places with the access to the Internet, as well as in the specially organised computer rooms at the educational institution. Students have the opportunity to link to or make an appointment for a consultation with a particular tutor, and tutors have the possibility of inviting students for tutorials and individual consultations, or group discussions in the form of forums, chat rooms, etc. Consultations and tutorials can be organised in groups or individually, online or offline in accordance with the adopted decisions, solutions and schedules. After obtaining the materials, students have the opportunity to sign up for the final examinations, individual work, training and practice work based on the approved timetable schedule.

4. Web-site http://idd.usm.md As part of the project the web-site has been created with the main purpose of it being to meet the growing needs of our society in efficient education by simplifying and extending the access to educational distance learning resources.


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The objectives of this web-site are as follows: 1. Simplification and extension of access to university graduate and post graduate

degrees delivered through ODL; 2. Advertising and promotion of ODL in Republic of Moldova; 3. Creating a virtual community for reflecting the best practices and for exchange of

experience with respect to organizing and carrying out of ODL, including benchmark conditions, methodical and teaching recommendations, methodological support for authors creating digital educational resources aimed at supporting the ODL process, supporting managers and students participating in ODL;

Generally the site audience includes people who are older than 17 -18 years who have graduated from high school or lyceum: students, trainees, workers who are looking for self-education or wish to obtain a second degree, etc.

5. Conclusions Presently one can evidence a steady development of educational systems based on ICT. There exist numerous solutions and copyrighted platforms (such as AeL, Prometheus, Hipermethod etc.) as well as the open platforms, of which Moodle is used the most.

The following questions generally require to be addressed when selecting a platform. What is the best way to select the most efficient solution for a specific utilization mode? What should be the principal criteria for selection? What are the risks?

Some of the relevant aspects that have been compared between the two e-Learning platforms tested as part of the the pilot project at the SUM and where Moodle scored better than Ael were as follows: platform is open source, it allows operations export / import for the tests of different formats, allows to plan actions (lectures) which students can access on particular dates, allows project work as a team, allows discussions, meetings and consultations in real time in through ‘chat’ tool.

Experimental test runs have been performed by a group of professors-authors of study units content and tutors for a period of one year for AeL platform and a several months for Moodle platform. As a result of test runs SUM decided to utilize Moodle. The decision was made by reference to the following features of Moodle:

1. Scalability. Allows easy expansion of infrastructure in proportion to increasing subdivisions, participants and educational resources, similar to AeL.

2. Robustness. Stability, availability and security are better ensured in Moodle compared to AeL. In exceptional cases or refusals Moodle, unlike AeL does not require the intervention of the author.

3. Ease of use/operation. Both platforms incorporate new technology and are multifunctional, have a simple and user-friendly interface, which practically does not require additional training for users who are already using Windows or Linux, with support of the Wizard type for the complex functions with contextual help incorporated. But after surveys of teachers and students participating in the test runs of both platforms the majority of the survey respondents preferred Moodle.

4. The time needed to implement. Moodle allows for fast implementation of the computer aided teaching, including distance learning. It allows to for easier recoupment


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of the invested funds, which boils down to the development of educational resources and operating the system. AeL has an additional high cost of acquisition and maintenance, compared to Moodle, which is free.

5. Reliability. Moodle has better reliability and operational speed that is constant with the number of users simultaneously working in the system. Moodle has a better quality support services that are cheaper compared to that of AeL. Dead / idle time occurred while testing AeL diminishing its effective use, this implied additional costs for launching the back up versions of programmed evaluations. No such occurrences happened during test runs of Moodle. That said, the As the number of tests performed on AeL was significantly higher.

6. Security. In addition to limiting unauthorized access and unauthorized copying, and securing against intentional or non-intentional destruction, both systems prevent access to items and tests, or populations of items from which self-testing and other testing exercises may be generated. However, Moodle has an advantage of allowing automatic mixing of order of the responses in multiple choice questions, which makes unauthorized copying or memorizing the answers in order to transfer information outside the test environment more difficult.

7. Administration and configuration. Both platforms allow centralised administration and configuration from the distance without administrators, managers or system engineers needing to move between each personal computer user. Other administration features are similar in both platforms. However, AeL charges additional fees on top of costs of supplier of the platform as well as additional fees for assistance.

8. Access to support. Ease and speed of installation and easy access to support for Moodle platform are internationally recognised. Being widely used platform Moodle develops much faster than AeL with operational costs being much lower. Forum on Moodle allows exchanging the experience and resolving problems quite efficiently. There are a larger number of Moodle users and specialists, which are available for the exchange of experience and developed resources, than that of the AeL platform..

AeL platform was found to be better utilized for computer-assisted teaching in local virtual classes, which are based on local performance networks.

REFERENCES Books: Bragaru T. and Capatana Gh. and Craciun I. (2008): Distance Learning: Concept and Terminology. Initiation

Guide. SUM, Chisinau. Brut M. (2006): Tools for e-Learning. Guide the modern teacher. Polirom (Eds). Rosca I. Gh. and, Zamfir G. (2002): Informatics Training. Bucuresti (Eds).

Scientific Reports:

08.815.08.04A project (2008). Development and application of innovative methods in distance learning. SUM, Chisinau.

Web-resources: AeL, official documentation http://www.advancedelearning.com; http://www.siveco.ro Moodle, official documentation, http://docs.moodle.org/

Knowledge Communication Programs Design

Ioan Maxim1, Tiberiu Socaciu-Lendvai 2

Teacher Training Department „Ştefan cel Mare” University Suceava, Universitatii, 13, ROMANIA

e-mail: [email protected] (2) Economics and Public Administration Faculty

„Ştefan cel Mare” University Suceava, Universitatii, 13, ROMANIA e-mail: [email protected]

Abstract The design of knowledge communication programs presume one strategy of knowledge presentation, succeeded by a scenario for developing interactive learning. Many didactic use products in informatics often neglect one of the two aspects. A conceptual and projective clarification is necessary for doing logical projects for assisted learning programming, programs that satisfy the defining characteristics of educational software: correspondence with the programmatic documents, accuracy and completeness of the content discussed, interactivity, correspondence with the target population, the feed-back and the formative assessment, pointing out achieving the objectives and so on. An attempt to transform into algorithms the learning programs design is late and harmful; success lies precisely in diversity. Moreover, specific procedural particularities of different disciplines, the diversity of learning methods and procedures implemented in the educational software, non-uniformity of contents, specificity of target population or its samples, impose some very important projection rules in the design of learning programs practice.

Keywords: Assisted learning, Logic project, Educational software, Learning scenario

1. Introduction Constant communication deficit between the segments involved in the learning programs design, psycho-pedagogy and informatics segments, is being concretized in learning informatics products for educational use of questionable value and utility. Undeclared dissensions between the two areas work together with conservatism of the educational system, sluggish and obsolete, which has facilitated and benefited from the lack of constructive dialogue between the two segments involved in logical and effective design of learning programs. The system reform requires a sinuous way, long and costly, which supposes the removal step by step of invoked obstructionist elements by the three parts; informatics and psycho-pedagogy segment, and educational system, which should validate the efficiency of informatics product for training. Certification of the final product of the education system is a condition for quality and efficiency for the informatics product in educational use. Therefore, the design of


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learning programs can not be disengaged any time from the evolution, from the changes which regard permanently the national education system and it must be every time subject of laws which govern the system.

2. Results and argumentations The computerized educational system, as designed by the Promoting Informatics Technology Group, in spring 2001, doesn’t fit and does not meet the requirements of assisted learning Romanian education system (Siveco, 2009). Declared as being the system for the educational reform, based on the education reform objectives proclaimed by e-Europe strategy developed by the European Community and integral part of the initiative European e-Learning, the SEI program although using numerous human and material resources, has failed. Designing learning programs should be based on defining characteristics of educational software (Maxim, 2008): - conformity with the curriculum; - accuracy and completeness of onset contents; - interactivity; - compliance with the characteristics of target population; - feedback and the formative evaluation; - marking the objectives achievement and so on. The content diversity and peculiarities of procedural features, specific for different disciplines, arsenal of methods and procedures implemented in the training programs, specificity of target population, exclude any attempt to algorithm the design of training programs. At the same time, the unity is in the diversity and the rules absence or methodological settlements would maintain the system in the craft area, in the moment inspiration area, situation categorically excluded from learning theory and practice. For this reason, the settlement of the design rules, which lead to quality informatics product, interactive, attractive, bearing appropriate scientific content, producing skills and competences proclaim through the specific objectives for each discipline, is a necessity. A learning program is for students, book and teacher at the same time and must include educational valences of the book, informative and formative task of this, as and the procedural part included in the methodological and didactic task of the teacher and to impose the relationship with the student, to achieve operational objectives. Starting from requirement that the manual should achieve the consistence with the curriculum and have the complexity degree in agreement with the particularity of the target population, the educational software should fulfil the same requirements: - to submit same elements of scientific content, but by means that are specific for it; - to achieve the same level of difficulty as a book; - to ensure equally, scientific accuracy of the transmitted content. Unlike the book, the educational software has one virtually unlimited space that can back up and complement elements of scientific content by images, audio and video recordings, to present the processes and phenomena described by the text of the manual, on the dynamic processing of theses.


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This way of transmitting informatics by text supported and complemented by audio and video records, represents an important advantage for the learning programs, but at the same time an element that must be judiciously controlled. Students are not used to "learn watching", and therefore, the illustrated scientific content must be supplemented with comments or appropriate subtitles, which will highlight the essential elements of transmitted content, will emphasize the students into the essential and will protect from harmful elements of the image or video recording. Scientific content can be presented in the three forms: - image or video recording; - audio recording; - custom text, activated by elements associated with the two previous modes of representation, explanatory tools, links to pages or windows for thoroughgoing study or extension, starter, processing of feed-back in learning situations. The presentation and representation manner of scientific content must be in conformity with the particularity of the target population: - in preschool and primary cycle content is transmitted primarily by image, less codified forms of representation of informatics, stick up by audio records; - learning tasks is transmitted by audio records and they must be short, clear, concise, without ambiguities or possibilities of interpretation; - learning tasks should be illustrated by demonstrative elements; - the difficulty degree to grow progressively, to avoid bottlenecks, situation of difficulty to be asseverate by help elements, which enable the student to solve the problem by fragmentation and a return to the original problem by defragmentation (Maxim and Moroşanu, 2008). A strong point of a learning program is interactivity. Even if the program is primarily for communication of new knowledge and through learning scenarios most situations where the student may be in difficulty are forecast and obviously there are set and applied some learning methods and processes which help the student to overcome these moments, no scenario can intuit and implement in a program all these situations. For this reason it is desirable to identify some dialogue techniques that allow students to question the software, in a manner familiar to them, in cases of student’s doubt of communication. It is widely known the passivity and un availability of the student for dialogue in communication in knowledge situations, but it can be reasoned by the volume of new information and the absence of cognitive structuring or reorganization of information, which occurs only after one prior assessment, a renewal of initial synthesis resulted by strengthening retention and by operating of the content. Therefore feed-back must be done after the presentation of a relatively low volume of knowledge, usually at the end of a paragraph or a sequence of paragraphs that address a common, dominant element of scientific content. Identifying sequences of content, after which is the feedback done and the learning situations that start the feedback, are important elements in designing the learning scenario. The feedback is for the student the most important occasion to highlight and clarify communication errors, understand and maintain the transmitted scientific content; and is the first step towards the activation of the contented elements. Moreover, it is an opportunity for the student to accommodate with exercise techniques.


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The transit through the last communication knowledge sequences and getting to the afferent feedback moment marks the beginning of the exercise sequence, for a systematic summary and the contents activation moment. A side effect of this sequence is to obtain a measure of the degree of achieving operational objectives and training skills derived and which can be expressed by the mark. This way the possibility to have a measure of the efficiency of its work and to build up a plan for improvement is offered to the students (and teachers), even if only by going over of the learning program, where the acquired outcome is not satisfactory. Although there is a very rich literature in this domain, which contains definitions of these key concepts, none manifested a tendency to unify those different meanings. This inconvenient has not been an obstacle to rapid progress, theoretically and in particular, in its application. The accumulated knowledge and the newly introduced paradigms require, from time to time, reassessment of key terms by the resumption of the effort to redefine and clarify the concepts. The comprehensive bibliography makes possible the formulation of a concrete response to the question: „What is an learning program?”. The notion of educational software allows the definition of the concept of computer-assisted learning and today is increasingly felt the need for assimilation of results from artificial intelligence domain, result which will gradually lead to intelligent systems training. Intelligence of such training systems is linked to their ability to teach and to adapt to the requirements, capabilities and to the peculiarity of the student, although it is possible that soon we can talk about training programs which infer with the own persuasions and with student’s emotions and which are able to express, in turn, emotions and feelings alike humans. The concept of intelligent agent its felt more often usefulness in the design of teaching programs (Maxim, 2008). With no unitary concept regarding the definition of the agents, research advance so rapidly that it can be said that an unitary point of view and an unifying concept is already shaping, so we appreciate that the domain is heading towards an inevitable international standardization. In training programs designing, the agent is often treated as the "attribution and effect", alternately, according to the learning situation for teacher and student. However, the concept is substituted to a kernel of informatics product, which manages besides the elements of scientific content or learning situations, attitudes, behaviors, responsiveness, experience, feelings of students, action expressed during the process of learning subordinated by educational software. The agent defined in this case, as „an entity that guides the process of instruction directing it to achieve operational objectives”, indicates that it meets one task of training, causing a change in attitude and behavior for student. In terms of targets, educational agent exceeds the register act, considered a defining characteristic of the agent’s concept („pursuing an action, changes something in the environment” or „Agents act: that is why they are called agents”) (Maxim, 2008), involved in shaping the student‘s personality, acting on the attitudinal and emotional register, intrinsic of training.


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Educational agents implemented in learning programs are based on their models of action upon learning procedures and methods; this makes them affect the "environment" and themselves at the same time. If an efficient educational process requires a proper approach, achieved through a systematic manner of activity and a correct decision regarding the selection and application of training methods, the methods represent specific organization forms of the relationship between agents and between agent and the environment. The “educational environment” includes a suite of elements that concerns also the knowledge, training, and at same time, the agent-student personality shaping. The learning procedure is the way of expressing the method, is the practical way of achieving it and is the fact that imposes an operating model to the agent-teacher and conditions the operating model of the agent-student. Relationship method-procedure is dynamic, so one method can become a procedure in the other methods and vice versa. Rationality presupposes student’s initiation of an action in the intention of maximizing their performance in relation with the evaluating function (Shardlow, 1990). The rational autonomous action, as defined, is too large for a criterion, which extends too much this object’s category. An acceptable "specific difference" is made by the definition of the Jennings (Jennings, Sycara and Wooldridge, 1998) for which “an agent is a computing system situated in a certain environment, which is capable of flexible autonomous action to achieve its designed objectives”. It is remarked that three key concepts are used to define an agent: positioning in relation to the environment, autonomy and flexibility. Positioning, in this context, means that the agent receives input from its environment (scientific contents) and it is capable of actions that change the environment (expand contents by student's action) in a manner specific for the environmental knowledge (science) addressed. The environment is a stage characteristic, positioning is a temporal property and autonomy and flexibility are dimension actions (Jennings, Sycara and Wooldridge, 1998). These defining features make the difference between the agents based system and the expert systems, which don’t interact directly with the environment, but receive information and knowledge through the knowledge engineer, which is a human "agent". The expert system does not act directly on the environment, but through the human factor. The tend to approach the learning programs to expert systems is more conspicuous, expert systems where the human intervention is essential in knowledge environment changing, investigated by the student. It’s the case of socio-human sciences, languages and literature, philosophy and so on, sciences for which the use of subjective items is a current practice in achieving the process of feedback and formative assessment. The trend is accentuated by the difficulty of subjective items algorithm implementation in the design of learning programs (Maxim and Moroşanu, 2008). Autonomy is understood as the absence of human intervention, but does not exclude the intervention of other agents, because learning occurs in a social environment, perceived as a competitive environment and therefore, the rationality of an agent’s actions is conditioned or is situated in the context of the environment and action of other agents.


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An agent can completely control its own actions and its internal status, but the influence of other agents on his action is achieved by prior changes that they produce on the environment. Sometimes autonomy is understood in a strict sense, an ability that the agent has to learn from his experience (Russell and Norvig, 1995). Educational agent is by definition responsive - perceives and responds to the timely and appropriately to changes that occur therein, which allows learning programs to make sequential feedback, is proactive – his actions are not simple reactions to the environment, but the expression of the ability to exercise behavior orientated towards a specific purpose, expressed through the action that approaches it to the goal, of achieving operational objectives that it has established, having in this meaning, its own initiative, and social – the agent is able to interact with other agents to solve its own problems and help others in their work, which gives educational software the interaction attribute. Luck, M. and others define the agents very synthetically, but comprehensively: "Agents can be defined as computational entities problems solver, autonomous, able to execute operations in dynamic and open environments" Luck, Mcbumey and Preist, 2001). If the first part of this definition is compatible with other definitions discussed above, the second part shows that the interest has moved from the individual systems, stationary, seen more as tools able to help the man in his activities, towards the situation in which the power of these computing systems is used to operate in distributed environments, unpredictable, open and dynamic.

3. Conclusions Such a system is an educational software, that must interact, must overpass the organizational predictability limits through the lesson’s project, they must operate efficiently, in terms of problem-situations that change quickly and dramatically, to attain operational objectives common to different types of educational agents integrated in the program of instruction.

REFERENCES Jennings, N.R., Sycara, K., Wooldridge, M., (1998), A Roadmap of Agent Research and Development,

AAMAS, 1, 7-38. Luck, M., Mcbumey, P., Preist, C., (2001), Agent Technology: Enabling Next Generation Computing. A

Roadmap for Agent Based Computing, Agent Link II, AAMAS Maxim, I., Moroşanu, C., (2008), Didactica specialităŃii Informatică, Editura UniversităŃii „Al. I. Cuza”, Iaşi,

2008, pp. 47-49 Maxim, I., (2008), Instruire asistată de calculator, - Working Paper – Teacher Training Department, „Ştefan

cel Mare” University Suceava, www.eed.usv.ro/~maximioan/ Russell, S.J., Norvig, P., (1995), Artificial intelligence: a modern Approach, Prentice-Hall Inc., Upper Saddle

River, NJ. Shardlow, W.J., (1990), Action and agency in cognitive science, Working paper. http://www.siveco.ro/press_release_details.jsp?ID=211

Section

TECHNOLOGIES

Technologies (TECH): • Innovative Web-based Teaching and Learning Technologies


• Web, Virtual Reality/AR and mixed technologies

• Web-based Education (WBE), Web-based Training (WBT)


• Educational Technology, Web-Lecturing Technology




Java in Scientific Computation An educational approach

Ernest Scheiber

Transilvania University of Braşov, ROMANIA


Abstract The aim of this paper is to emphasize some specific aspects when numerical methods are implemented in Java like involved programming problems, available resources and the possibility to extend the application usage in a distribute environment, like Internet. Keywords: Scientific computation, Java programming.

1. Introduction The fifteen years old development programming language Java is used in many projects, frameworks and products for high performance computing and parallel distribute computing. The Java technology is improving continuously. Java was designed to meet the real world requirements of creating interactive, networked programs. It’s interesting to consult the TIOBE Programming Community index of the popularity of programming languages (IS1). The index is updated monthly.

Among the present tendencies there are: • Software as a Service (SaaS) – an application is offered to a client as a collection

of services; • Platform as a Service (PaaS) – The services are available through some software

and hardware resources, offering scalability. This is known as Cloud computing and it is a new form of evaluation and of usage of software.

Taking into account these facts, the purpose of this paper is to give a snapshot of the most relevant tools, frameworks, programming technologies involved in scientific computing: mathematical resources, java numerical packages, math parsers, graphical interfaces, web applications, file upload, web services, from the Java perspective.

Mathematical aspects of the numerical methods are presented in Kincaid (1991), Press (2007), Stancu (2001) but here we are interested in their Java implementation (Landau, 2005, Ritkey, 2000).

Implementing a numerical method, to benefit of the object oriented paradigm it is preferred to define an interface and implementing classes. We point out two ways to transfer the input and output data between the user / client and the computing method:

• The input data are formal parameters of a method (as in the Fortran style). When the data is a user defined function it raised a problem – in Java a method can not


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be a formal parameter. Usually the function is implemented as a method of a class, and an instance of that class is set as parameter.

• Using wrapper classes, Java beans. This seems to be a better solution. The case when the function is defined by a string introduced dynamically by the client

will be presented in the math parser section.

2. Useful Programming Tools The following Java programming tools are very useful in the development of applications:

• apache-log4j – allows to register messages with the evolution of computation; • junit – allows to perform automated testing; • apache-ant – a build tool, independent of platform, it automates the operating

tasks. We must mention the OSGi (Open Source Gateway initiative, 1999) component

model, too. The OSGi model requires constructing components denoted bundle for deployment, programmed on the base of a specific API (Application Programming Interface). Many of such bundles may be installed, even as services into such frameworks. There are well known three OSGi frameworks:

• equinox - used by Eclipse; • apache-felix; • Knopflerfish – it offers a graphical interface to perform the specific OSGi

operations. The common operations relative to a bundle are installing, start, stop and uninstalling.

3. Java and other Mathematical Resources An evidence of the available numerical software and some comparisons are given at (IS2) and respectively, (IS3). The functions of the main products may by call from Java. Thus Mathematica, Maple, Matlab and Scilab have components that allow a Java program to interact with them.

Using Java Native Interface (JNI), it is possible to call a C function defined in GNU Scientific Library (GSL).

The rJava software contains a component denoted jri that allows calling an R function. R is a language and environment for statistical computing and graphics, a GNU product.

There is a Python community of scientific computing (Langtangen, 2008). A reference Python package for scientific computation is scipy. Using the Jepp package it is possible to use from Java the resources of scipy. We remember the sagemath project having the target to gather and to assure the maintenance of open and free of charge mathematical software. The link is Python. Under the MS Windows operating system, sagemath is given as an appliance for VMware Player. The starting point of this project is the fact that while the costs to maintain the mathematical publications are negligible, the costs to maintain the mathematical software are considerable.


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A consequence of these facts is that Java is a working environment that connects all the above mentioned products.

4. Java Numerical Packages There are several Java packages with classes that solve numerical problems. An overview of such packages may be found at (IS4). Here we mention only two such packages:

• apache-commons-math - a library of lightweight, self-contained mathematics and statistics components addressing the most common problems not available in the Java programming language. It contains solvers for systems of linear equations, nonlinear algebraic equation, ordinary differential equations, interpolation, numeric integration formulas, fast Fourier transform, etc.

• Jama – implements the common numerical linear algebra methods. 5. Math Parsers A math parser tool allows interpreting a string as a computing expression. Such Java tools are:

• Java Expression Parser (JEP) – Until the version 2.4.1 this tool was free of charge. The usual notation of the functions is used. The recognized function family may be extended dynamically.

• MathEclipse Parser – The package may be used as a Google Web Toolkit (GWT) module, too. It uses the Mathematica notation of the functions.

6. Graphical Interfaces The existence of a graphical interface helps the usage of an application. There are

several ways to program a graphical interface, using: • The java.swing classes from JDK (Java Development Kit – Sun Microsystems); • The SWT – Standard Widget Toolkit package, developed by I.B.M.; • The JavaFX declarative language, developed in recent years, by Sun

Microsystems. An Integrated Development Environment (IDE) simplifies the programming work.

Such free of charge IDE are: • Netbeans supported by Sun Microsystems. • Eclipse supported by I.B.M.

7. Graphical Representations PtPlot and jfreechart are tools whose classes may be easily used to obtain a 2D graphical image. To represent a function f it is enough to provide the set of coordinates

iii xfx ))(,( . VisAD, a more sophisticated package, allows 2D, 3D representations and

animations. These products are open source and free.


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8. Web Applications We emphasize two models of distribute applications

• Client-server – The server executes the requests of the clients. Between the client and the server, with the communications based on the http protocol we distinguish :

o Web application or site – the client is a human. The request is launch through a browser (Mozilla Firefox, Google Chrome, Microsoft Internet Explorer, Opera, Apple Safari, etc).

o Web service – the client is a program. • Dispatcher-worker (master-slave) – The dispatcher program distributes the

computation tasks to the workers and coordinates their activities. Limiting to the Web applications we enumerate the following technologies: • Servlet – this is the most basic Java program from the server side (Boian, 2004). • Java Web Start - based on the Java Network Launching Protocol (JNLP) allows a

desktop application to be used remotely. • Java Server Pages (JSP) – combines html and Java codes.

For all the above technologies, the server is installed in a servlet container Web server (apache-tomcat, jetty, Sun Java System Application Server – used by Glassfish, JBoss, etc.).

A servlet may be included into an OSGi bundle and used through the modulefusion middleware, that contains the jetty Web server.

If the Web application has a more complex structure then there are a lot of frameworks that simplifies the management of the components of the application, as well as the programming: Struts, Java Server Faces, Wicket, Google Web Toolkit (GWT), etc. GWT uses the Java programming language, but the framework translates the classes into JavaScript.

9. File Upload Sometimes the client has to supply a large amount of data to the server (like the elements of a matrix). The upload problem means to send a file of data to the server. At the server side the apache-fileupload tool facilitates the programming task to receive the sent file. At the client side, the file selection and the sending are easily solved by html forms, apache commons-httpclient package or GWT.

10. Web Services There are known two kinds of Web services:

• Based on the Remote Procedure Call (RPC). The service is described by a wsdl (Web Service Description Language) file. The JSR (Java Specification Request) 109 defines two way to implement RPC service:

o Based on a servlet; o As an Enterprise Java Bean (EJB) session.

• RESTfull service (REpresentational State Transfer) – the service is identified by an URL.


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Metro is a framework allows developing a RPC service, both the server side as the client side. Sun Microsystems and Microsoft jointly test Metro against Windows Communication Foundation (WCF) in .NET to ensure that Sun web service clients (consumers) and web services (producers) do in fact interoperate with WCF web services applications and vice versa. This ensures the interoperability between the Java and the .NET platforms.

The Jersey project is the reference implementation of JSR 311 (The Java API for RESTful Web Services). There are two ways to program a client: using the java.net.HttpURLConnection class from the JDK distribution or the Jersey-Client classes.

The above distribute applications can be installed into the cloud. There are well known the following Cloud Computing platforms:

• Amazon’s Elastic Compute Cloud (EC2) - reference product but commercial; • Google App Engine (GAE); • Microsoft Azure.

We have used GAE. For now GAE has two versions – for Java and Python - and each contain a local simulator. The product is also free.

11. A Case Study Let us implement the tangent method to solve an algebraic equation. This will belong to a larger library called mathlib

mathlib

| |-->client

| | |--> ecalg

| | | |--> impl

| | | | | TangentMethod.java // The implementing class

| | | | ITangentMethod.java // The interface

| | | | DataIn.java

| | | | DataOut.java

The interface declares the method public DataOut tangentMethod(DataIn

din). DataIn and DataOut are wrapper classes of the input and output data. The left side of the equation is defined in DataIn through public abstract double

fct(double x) while its derivative is computed numerically using the Richardson extrapolation. To be used as a GWT module it was intercalated the client folder.

The implementation may be own or it may call an external resource. To test, it is defined a derivate class SimpleEcAlgDataIn extends DataIn,

fixing the fct method. A test code is import org.junit.*; import static org.junit.Assert.*;

import mathlib.client.ecalg.*;

import mathlib.client.ecalg.impl.*;

public class AppEcAlg

// the known result of the equation


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public double result=-0.7666647;

@Test

public void test()

DataIn din=new SimpleEcAlgDataIn();

ITangentMethod obj=new TangentMethod();

DataOut dout=obj.tangentMethod(din);

assertEquals(result,dout.getX(),din.getEps());

public static void main(String[] args)

org.junit.runner.JUnitCore.main("AppEcAlg");

For an OSGi bundle, the corresponding Activator class is import mathlib.client.ecalg.*;

import mathlib.client.ecalg.impl.*;

import org.osgi.framework.*;

public class Activator implements BundleActivator

public void start(BundleContext context)

DataIn din=new SimpleEcAlgDataIn();


DataOut dout=obj.metodaTangentei(din);

// print the results

public void stop(BundleContext context)

To simplify the tangentMethod usage a graphical interface may be attached, but in this case it is necessary to derive an appropriate class of DataIn

package mathlib.client.ecalg;

import org.nfunk.jep.*;

public class JepDataIn extends DataIn

private JEP parser=null;

private String var;

public JepDataIn(String var,String expr)

this.var=var;

parser=new JEP();

parser.addStandardFunctions();

parser.addStandardConstants();

parser.addVariable(var,0);

parser.parseExpression(expr);

public double fct(double x)

parser.addVariable(var,x);

return parser.getValue();


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A servlet, RPC or RESTful type service may be built to call the tangentMethod. The Java code for metro RPC service is

package ecalg.server;

import javax.jws.WebMethod;

import javax.jws.WebParam;

import javax.jws.WebService;

import mathlib.client.ecalg.*;

import mathlib.client.ecalg.impl.MetodaTangenteiWeb;

@WebService()

public class TangentMethodWS

@WebMethod(operationName = "solve")

public DataOut solve(@WebParam(name = "x") String x,

@WebParam(name = "svar") String svar,

@WebParam(name = "expr") String expr,

@WebParam(name = "eps") String eps,

@WebParam(name = "nmi") String nmi)

JepDataIn din=new JepDataIn(svar,expr);

din.setX((new Double(x)).doubleValue());

din.setEps(Double.parseDouble(eps));

din.setNmi(Integer.parseInt(nmi));


DataOut dout=obj.tangentMethod(din);

return dout;

Trying to find the negative solution of the equation 22 xx = , starting with 5.0−=x we obtain


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REFERENCES Books Anisiu V. (2006): Calcul simbolic cu Maple. Ed. Presa Universitară Clujeană. Cluj-Napoca. Boian F.M., Boian R. F. (2004): Tehnologii fundamentale Java pentru aplicaŃii Web. Ed. Albastră, Cluj-

Napoca. Kincaid D., Cheney W. (1991): Numerical Analysis.Mathematics of scientific computing. Brooks/Cole,

Pacific Grove, California. Landau H. R. (2005): A First Course in Scientific Computing. Symbolic, Graphic, and Numeric Modeling

Using Maple, Java, Mathematica, and Fortran90. Princeton Univ. Press, Princeton. Langtangen H. P. (2008): Python Scripting for Computational Science. Springer, Berlin. Petcu D. (2000): Matematică asistată de calculator. Ed. Eubeea, Timişoara. Press W. H., Teukolski S. A., Vettering W. T., Flannery B. P. (2007): Numerical Recipies 3rd Edition: The

Art of Scientific Computation. Cambridge University Press, Cambridge. Stancu D. D., Coman G. (Ed) (2001): Analiză numerică şi teoria aproximării. Vol. I, II, III, Ed. Presa

Universitară Clujeană, Cluj-Napoca. Tocci C., Adams S. (1996): Applied Maple for Engineers and Scientist. Artech House, Boston, London. Internet Sources Ritkey K. (2000): Java as a Scientific Programming Language (Part1). www.developer.com/tech/article.php/631151. Ritkey K. (2000): Scientific Computing in Java (Part2). www.developer.com/java/other/article.php/631281. (IS1) http://www.tiobe.com/index.php/content/paperinfo/tpci/index.html (IS2) http://en.wikipedia.org/wiki/List_of_numerical_analysis_software (IS3) http://en.wikipedia.org/wiki/Comparison_of_numerical_analysis_software (IS4) http://math.nist.gov/javanumerics

New ways of transforming Drupal from CMS to LCMS

Liviu Beldiman1, Dorin Canepa1

(1) AltFactor, Galati

23, Portului Street, 800025, ROMANIA E-mail: [email protected]

Abstract There is a constant global effort to improve the e-learning experience. This includes several aspects, like: new ways of elaborating the educational materials, improving the new applied pedagogies, but also new paths of assuring and delivering the educational process. The present paper is describing a new e-learning tool developed by AltFactor that plays the role of a Learning Management System. Together with Drupal, the well - known Content Management System, the result is a complex LCSM that can be used as an integrated e-learning solution. The solution has been successfully tested on a group of 40 students, that have studied a two - module Project Management course. Keywords: LCMS, SCORM, e-learning

1. Introduction Even if the paradigm of e-learning has remained unchanged to the same levels since ancient times, the way the information that should ensure the educational process is passed from one teacher to his pupils is changing every day.

The mechanism of learning is, of course, the same, but the race to deliver wide – impact, high – quality, cost – effective training has raised the tools offered by ICT to new levels that have imposed themselves in the activity of trainers and content developers.

Nowadays, there are at least four main types of actors in the field of e-learning: e-trainers, e-pupils, content developers and content management system developers, each of them playing a very clear role.

AltFactor has earned the reputation of content developer, proving a solid experience in elaborating educational materials for students of different ages: from 6 to 65 years old. The present paper is revealing the efforts AltFactor has done recently in designing a complete e-learning solution: developing a LCMS.

2. A Content Management System A content management system, usually known as CMS, is an application used to control and manage any workflow needed to collaboratively create, edit, review, index, search, publish any type of Web content or digital resources. A CMS can be successfully used to implement a large range of applications, from simple websites to complex corporate


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applications. It is used all over the world to power government portals, corporate intranets and extranets, ecommerce sites, nonprofit outreach, schools, church, and community sites.

AltFactor’s solution is based on Drupal, a free and open source CMS written in PHP that is used for many types of web applications, ranging from small personal blogs to large corporate and political sites and even front end for some other web application like CRMs (Client Relations Management), ERPs (Enterprise Resource Planning) or LMSs (Learning Management System) systems.

One of its main advantages is the modularity that is accomplished by the simplicity of developing or installing third party or in-house custom - built plug-ins (modules). The standard release (Drupal core) contains basic features common to most CMSs. These include the ability to register and maintain individual user accounts, administration menus, RSS-feeds, customizable layout, flexible account privileges, logging, a blogging system, an Internet forum, and options to create a classic brochureware website or an interactive community website.

Because of its modularity, Drupal is also referred to as being a CMF (Content Management Framework). Although Drupal offers a sophisticated programming interface for developers, no programming skills are required for basic website installation and administration.

Drupal can run on any computing platform that supports both a web server capable of running PHP version 4.3.5+ (including Apache, IIS, Lighttpd, and nginx) and a database (such as MySQL or PostgreSQL) to store content and settings.

2.1 LMS vs LCMS The primary objective of a learning management system (LMS) is to manage learners, keeping track of their progress and performance across all types of training activities. By contrast, a learning content management system (LCMS) manages content or learning objects that are served up to the right learner at the right time.

AltFactor’s platform is a LCMS as, in addition to managing the administrative functions of online learning (the LMS functions), it provides tools to deliver and manage instructor-led synchronous and asynchronous online training based on reusable learning object methodology.

Simply explained, the primary educational problems an LCMS solves are • centralized management of an organization's learning content for efficient

searching and retrieval; • productivity gains around rapid and condensed development timelines; • productivity gains around assembly, maintenance and publishing / branding /

delivery of learning content.

3. AltFactor’s LCMS AltFactor’s educational platform is based on the Drupal CMS (Figure 1). The starting point of view was very simple: to be as friendly and lightweight as possible for both user categories: teachers and students.

The platform is structured in order to ensure a smooth educational process. A teacher can upload his own courses, monitor the students progress – activity on the platform and


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grades obtained on the on-line tests, upload bibliographical materials for off-line study, post messages in the News section or on the Calendar section, send personal messages to his students and, of course, moderate discussions in the Forum.

A student on the platform can study the courses he is assigned to, view his grades and his progress, send personal messages and post messages in the Forum.

Other roles are course secretary – for monitoring the educational process, course administrator and platform administrator – key roles for managing the educational and the technical aspects of a LCMS.

Only an administrator can create a new course and upload its content to the platform. After courser creation at least one teacher must be assigned to that particular course. Of course, it is possible to have more than one teacher assigned to one course.

The next step is to assign the students to the course and to a specific trainer. In this moment an e-mail is automatically sent to the student with details concerning the course. If the student ignore this e-mail, or after a period of inactivity on the platform, other e-mails are sent to the student in order to remind him about his duties.

A teacher, a secretary or an administrator can observe some general statistics and personal statistics. In the general statistics section reports about a course can be monitored, like: number of users, SCOs finished, SCOs started, total time spent on the course.

In the personal statistics section, reports about students can be monitored, like: what SCOs are finished or not, how many times a SCO has been accessed, the SCORM status of the SCO, the total time spent inside each SCO and total time spent studying the course.

Figure 1. AltFactor’s LCMS Home Page

3.1 The Educational Component What we usually name the educational component is in fact the SCORM 2004 player which plays the content packed in SCORM 2004 zip packages. This component is built using Action Scrip 3.0 technology, using Adobe Flex SDK and javascript that links the part written in Flash (the SCORM tree) with the Drupal, written in php technology. The


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data is sent both ways in order to record and show the user progress. The Drupal is able to store data received from the flash to its own database and then send it back when it is needed (e.g. the student is able to continue the course at the exact SCO when he pushed the Suspend button and left the training session).

The whole application is encapsulated in a module that can be easily installed – it is only one click away. At this moment the module is designed only for Drupal version 5, but it can easily be rewritten for Drupal version 6 if anyone should need it or from technical reasons. In order to define the whole educational process, this module has to be installed with another one that defines the notions of class, tutor and student, assessment reporting & tracking.

The access to the educational content is granted upon the rights granted by the administrators to certain courses. The user has to enter his unique username and password only one time, when he is logging on the LCMS. Every user has a unique id, so the platform is able to report to Drupal different statistics about one user, regarding his progress: time spent on the platform, time spent on a certain educational material, SCOs finished, grades or other reports that one tutor may need.

The navigation between the course’s SCOs is ensured by using the SCORM tree or the previous and continue buttons – if the SCORM package does not hide them, using the hideLMSUI function. The SCORM is not responsible for the navigation inside the SCO, only the programmer being in charge to resolve this small scale navigation. Of course, one solution is to use only one SCO screen.

In order to briefly sum up the functions of the player, we have to mention that the application is designed to:

• import course packed SCORM 2004; • upload SCORM packages on the server; • unzip SCORM packages; • verify the manifest.xml file; • save the SCORM objectives values in the Drupal database; • save the lom (the key words) in the Drupal database.

By choosing Courses from the menu, the user will choose from a list with the courses he is assigned to, the one he wants to study (Figure 2):

Figure 2. List of courses available on the LCMS


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After choosing the course, the user will be able to access the player on another browser page, where he will be able to study the educational materials available for the selected course.

If the course has been previously accessed, but not finished, besides the Start button a Continue button appears so that the student can continue the study from the exact point where he suspended his training session.

According to SCORM 2004 standard, the player interface is divided into two parts (Figure 3): the navigational tree on the left and the educational content on the right. The graphical layout of the player can be easily changed according to the beneficiary visual identity, while the content interface and graphical layout can be very easy designed and implemented so they fit the beneficiary needs. For example, for the applications elaborated in flash, the .swf file that contains the educational application is accompanied by another .swf file, that defines the graphical user interface. This later file can be easily modified.

Figure 3. The SCORM 2004 player

4. Conclusions This long - distance educational solution is used by AltFactor together with one partner (an authorized long - life learning provider from the local market) in order to provide on-line courses for Project Management. Even if the economic crisis has a great impact on economy and on people’s will to spend money for studying, the clear advantages of e-learning seem to determine many students to choose this form of instruction that provides them the much needed diplomas.


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Also the funds provided by the European Union through different kinds of structural financial programs are helping e-learning to develop by providing opportunities to purchase the necessary hardware infrastructure, to connect to high speed Internet lines, and then to develop an integrated e-learning solution, with an electronic curricula that covers the society present and future needs.

For the future, two main actions are planned: to improve the features of our LCMS in order to provide better services for our partners and clients and to develop more on-line courses with high impact on the national market in order to improve the educational offer.

REFERENCES

Conference Proceedings: Beldiman L., Ifrim V. (2007): Coordonate de design pentru conŃinut în instruirea asistată de calculator. In The

South-East European Space In The Context of Globalisation, Bucharest, pp. 397-404, ISBN: 987-973-663- 535-9

Beldiman L., Comănescu A. (2007): Centru de instruire în sistem e-learning pentru personalul angajat. In A V-a ConferinŃă NaŃională de ÎnvăŃământ Virtual, ConstanŃa, pp. 65-70, ISSN: 1842-4708

Internet Sources:

http://cursuri.trainingimm.ro http://drupal.org http://opensource.adobe.com/wiki/display/flexsdk/Flex+SDK

Management of Knowledge –Base Systems in Desktop and Mobile Learning Environments

Veronica Ştefan1, Ion Roceanu2, Cătălin Radu2,

Ioana Stănescu3, Antoniu Ştefan3

(1) Valahia University of Târgovişte, E-mail: [email protected]

(2) “Carol I” National Defence University in Bucharest

(3) Advanced Technology Systems - ATS, Târgovişte

Abstract The authors present a comparative approach between the user interfaces of knowledge databases developed for desktop and mobile access, underlying the main similarities and differences, with the purpose of sustaining sound practices and increase transfer and accessibility to the mobile arena. Collaboration is a key element in providing improved performance and quality of activities both in educational and business settings. As result of the work for MOBNET-Learning research project, this article explores the dimensions of building collaborative systems based on mobile technologies as a tool for sustaining interactive environments that comprises wireless communication technologies and mobile terminal devices for the real time access to knowledge database.

Keywords: Knowledge creation and dissemination, Mobile Knowledge Management Systems, Mobile user interface design

1 Introduction Knowledge management (KM) emerged from the world of academia and became a burning issue for business and technology leaders in the last decade. Although a factor of improvement, knowledge management has not been largely embraced by organisations. This paper explores the importance of creating a dynamic management system, not just a storage capacity for accumulated knowledge, although at times useful. KM enables taking informed action in previously unencountered/ unknown circumstances. MOBNET-Learning is a research project developed by “Carol I” National Defence University in Bucharest in partnership with Advanced Technology Systems, the Research Institute for Artificial Intelligence of the Romanian Academy and other 2 private companies. MOBNET-Learning Project explores the potential of knowledge in the mobile learning environment. In this paper the authors examine the shift to mobile knowledge. In recent years there has been a major transformation in how formal and informal communication is disseminated by electronic means and the mobile learning environment is already based on standards (O’Connel and Smith, 2007).

MOBNET-Learning Project comprises a learning management system and a knowledge management system (Roceanu et al, 2009).


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Figure 1. The Web site of MOBNET-Learning Project

2 The potential of Mobile Environment for Knowledge Organisations Knowledge management has slowly matured mainly within global organisations, sometimes as executive information portals, content management or intellectual capital. Successful KM practices came to include portals, e-learning, e-analyses and content management (Guy, 2009). In the current economic climate, organisations are realizing that leveraging the already accumulated corporate intellectual property is by far the lowest-cost way available to increase their efficiency and competitive stature, in the case of companies. In a knowledge-based society and economy, knowledge management is the critical element in the strategy of organisations that will allow them to accelerate the rate at which it handles new challenges and opportunities, and they do so by leveraging the most precious of resources, collective know-how, talent and experience – intellectual capital.

Organizations are no longer valued solely for what they have done – but the potential of what they might be able to do. The promise and interest in knowledge management is not in knowing, but in being able to act creatively based on what you know and you are able to access. Innovation results from knowledge that it why it is important to consider the infrastructure behind knowledge management. The raw goods of intellectual property – experience and know-how – must be channelled and made available. This is a very real problem for many organisations.

Consider the issue that NASA faces. Virtually the people involved with the Apollo projects are not active anymore. With them went the know-how on how to land a man on the moon. While the planned approaches were captured, the dynamically acquired knowledge base that emerged through facing the challenges that each Apollo mission


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presented were not captured anywhere (Frappaolo, 2006). Knowledge management systems answer to the need to capture and monitor ever-developing bodies of intellectual capital, and to promote its leverage by communities of practice. The advent of Internet as a worldwide common interface is making this vision possible, but it also raises the bar on the scope of success and failure. Knowledge has become the key economic resource and the dominant and perhaps the only source of competitive advantage in a developing knowledge society (Toma et al, 2009). At the same time, the practices in accessing knowledge and information have changed, particularly in the use of search engines, digitized resources and mobile environments. The authors consider that the simple growth and proliferation of outputs does not lead straightforwardly to a richer and more diverse information and knowledge environment. This paper defines the settings for the implementation of the knowledge and the considerations for achieving a comprehensible knowledge infrastructure.

3 The Development of the Mobile Knowledge Management System Information and communication technologies provide tools to optimize the use and to increase the value of captured knowledge. Contextual learning requires specific, timely knowledge and, at the same time, generates valuable input data. Most of the times this contextual knowledge cannot be accessed or is lost due to the lack of adequate access/collection systems available in the mobile environment (Stănescu and Ştefan, 2008). One of the goals of the MOBNET-Learning Project is the development of a knowledge acquisition and retrieval system that operates as a mobile learning assistant, allowing users to access mobile knowledge when and where they need it, filling the present gap in the access chain. Learners will use the mobile knowledge management system in order to be able to fulfil their tasks quickly and more efficiently, as the system filters information by various criteria, facilitating access to specific knowledge.

3.1 Mobile Knowledge Management Systems Architecture The system uses a common database for both the knowledge management system and the learning management system. This improves the results of the search and allows an easy administration of knowledge and learning objects and a unified access from the users’ standpoint.

The knowledge is accessed via a mobile Graphical User Interface built according to best practices issued by the World Wide Web Consortium (W3C). The mobile website is developed based on the Microsoft .NET Framework using ASP.NET and C#. For the backend, the developers have used Microsoft SQL Server 2008 as the database engine.

Figure 2. Mobile Knowledge Management System for MOBNET-Learning Project


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3.2 Mobile Knowledge Management Systems Main Functionalities The Mobile Knowledge Management System (m-KMS) provides access to information via a Web-based Graphical User Interface available in desktop and mobile environments. Access rights were considered as follows: - A private section: in order to be able to benefit of the full potential of the KMS,

users need to create an account; thus, the uploaded content and the related added comments can be user-related and reader rated as competency in concerned; users and content can be rated; this increase the trust level for the accessed knowledge.

- A public section: the application manages a public section that comprises general information of public interest (news, articles, etc.) and access to certain bodies of knowledge, declared as public by the issuing party; the information can be accessed directly, without being logged into the system.

Management of knowledge includes management of users, management of data classified by domain, author, date, relevance, management of knowledge acquisition.

The m-KMS provides advanced searching options: by keyword, full text search, by topic and by similar articles, to target the preferences of a larger group of mobile users. To improve the user experience, the systems allows refining of search results by applying search criteria progressively, against the current result set.

While reading an article, users are provided with links for terms on which the system can provide further information. This feature is valuable especially for mobile users which are constrained with regards to the input methods that their device provides. At the end of an article, users are also provided with links to other related articles and information on where to obtain further data. Over time, users are likely to refer to the same articles multiple times. This is particularly valid for articles that include mathematic formulae and large tables that are impractical or hard to memorize. To speed up access for these articles, users are provided with a complete history of previously visited articles as well as with the possibility of creating multiple article favourite lists based on topics of interest.

The m-KMS also allows learners to capture new information by providing different forms of input such as text, sketches, recording of messages or photos. To use the potential of this data collection process, the system allows the user attach feedback to existing articles and also to create new articles. The user also has the option to automatically attach relevant information such as localisation, or a history of the most recently accessed articles.

3.3 Mobile Knowledge Management Systems Technologies These are a few of the key features of the mobile knowledge management system that is developed by the MOBNET-Learning Project. The system aims to build adaptive learning resources reconfigurable based on the device attributes and users’ preferences and to provide mobile learners with knowledge in the Romanian language, becoming a start-up project in this domain.

The m-KMS is developed using Java Enterprise Edition (Java EE). Unlike native applications that access the operating systems and the hardware resources directly, Java applications are executed by a virtual machine (JVM - Java Virtual Machine). Thus, they


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are isolated from native access and they can access only Java libraries or the functions of the virtual machine. The virtual machine contains the Java Runtime Environment that represents all the standard functions and libraries provided by Java.

Java desktop applications (Java SE) are executed directly and function similar to any desktop application, while Java EE Application require an application Server (JBoss) than acts as a Web server.

4 Building Mobile Graphical User Interface The research within the MOBNET-Learning Project focuses in the area of mobile learning environments. Regardless of the settings they operate, users constantly want new features on their mobile phone, such as texting, voice memos, browsing, cameras, music and television, because they would like these things in their pocket and the phone is already there. MOBNET-Learning Project aims to improve the experience of the mobile learner by identifying a flexible blend of devices, technologies and skills required for a better performance.

4.1 Capabilities and Restrictions of Mobile Devices Mobile devices represent a key performance factor for accessing mobile knowledge. In the last years, the mobile market provides a wide range of devices from mobile phones, smart phones, XDAs, PDAs, Media Players, notebooks and laptops. The MOBNET Project aims to provide access to specific content and develop optimised knowledge delivery for devices that present significant restrictions in terms of screen size, keyboard access and processing power (Shearer, 2007; Ştefan and Stănescu, 2009).

In order to obtain an enriched user experience when accessing mobile knowledge, the users need to understand the capabilities and the technology that their mobile device provides. The large range of mobile devices available on the market today implies that it is basically impossible for developers to target each and every one of them (Lindholm and Keinonen, 2003). This requires future mobile users to consider certain features when purchasing a mobile device. When users intend to access web content on their mobile device, they will benefit most if they choose a device with a web browser based on the same libraries as a desktop browser.

For example, iPhone OS uses Mobile Safari, which is based on the same WebKit libraries as Safari and Google Chrome. The same applies to the Series 60 3rd Edition web browser, which is also based on WebKit.

Mobile devices have such a precious screen estate, and developers need to follow the best practices recommended by the W3C and avoid adding extra user interface elements. Given the same URL, one can easily observe the difference between:

1. Mobile browser configured in mobile view mode; 2. Mobile browser configured in desktop view mode;

Figure 3. Development platform for m-KMS


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3. Mobile browser configured in one column mobile view mode with full screen.

Figure 4. Comparison between different view modes ATS For example we present this figure from a demo knowledge-based decision support

system that Advanced Technology Systems has recently developed. The best experience can be obtained by removing the application’s title bars and

adapting the content to just one column to allow users to scroll in just one direction.

4.2 Particularities of Mobile Content Delivery The particularities of mobile devices require solid customization of delivery in comparison to the desktop computers in order to encourage users to become mobile. This is even more to be considered in the learning environment from the perspective of setting course to good practice and implementations of mobile developments.

This section comprises a set of best practices (Rabin and McCathieNevile, 2008; Lumsden, 2008; Shneiderman et al, 2007), that base the design and development of the m-KMS:

-“Content provided by accessing a Uniform Resource Identifier (URI) should yield a thematically coherent experience when accessed from different devices”.

The content should remain the same, regardless of the means used to access it. At most, parts of the content may be missing, if they cannot be made compatible with the client devices.

-“Device capabilities should be exploited to provide an enhanced user experience”. Different devices provide different functions, and these should be exploited to a maximum in order to provide the best possible experience for the mobile user. Adapting the system and/or the content to support specific functions of a device or group of devices allows the user to obtain a better experience.

-“Tests on actual device”s. Because of the vast number of differences between mobile devices, it is best to test the website of as many different phone models as possible.


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Sometimes the browser implementation can differ greatly for the same phone model, depending of the firmware version installed.

-“Keep the URIs of site entry points short”. The web site should be designed with quick URIs that can take the user to a specific page based on content ID. For example, the user can access the address http://news.mobi/40652 and be automatically taken to the article with ID 40652.

-“Provide minimal navigation at the top of the page”. The navigation menu should be designed in such a way to occupy little space but at the same time provide links to the most important pages. It is probably best if content is structured hierarchically to provide the content hierarchy leading to the current page.

-Provide a balance structure between having a large number of navigation links on a page and the need to navigate multiple links to reach content. Mobile web pages should include as much content as possible without requiring the user to switch between multiple pages to find the rest of the information.

-“Provide consistent navigation mechanisms”. Use the same navigation mechanism across a service to allow users to identify them easier.

-“Assign access keys to links in navigational menus and frequently accessed functionality”. This would improve the mobile experience and will allow users to enjoy it with the help of a single key acting as a single click.

-“Limit scrolling to one direction”. This allows the user to experience all the content of a web page without having to switch in all directions.

-“Avoid large or high resolution images”. If used, images should be resized at the server. Mobile devices have limited capacities and waiting for a web page to load it is not a welcomed experience.

-“Do not use frames”. As many mobile devices do not support frames, the web site becomes inaccessible and the target group is severely and uselessly restricted.

-“Provide informative error messages and a means of navigating away from an error message back to useful information”. It is always helpful to know that something went wrong, then to simply get stuck without an obvious reason.

-“Avoid free text entry where possible, and provide pre-selected default values where possible”. When referring to online mobile tests or evaluations, free text can be replaces with access keys that point to the correct answer. Also, in designing for small devices, speech input is a viable alternative for devices too small for extra buttons.

When designing for multiple and dynamic contexts the developer needs to consider the environmental conditions where the learner activates, to provide enriched user experience.

5 Conclusions MOBNET-Learning Project promotes the values and the opportunities that the mobile technologies can bring to the learning environment and the knowledge communities. The Project represents an innovative practice-driven approach for the Romanian research area and aims to become a significant contribution to the implementation of mobile knowledge management. MOBNET Project develops mobile content and systems that teachers,


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trainers and students can use to complement or as an alternative to course activities whether they occur or not in traditional classroom environments. This paper examines the implications of the transition of knowledge to the mobile environment in terms of graphical user interface and mobile devices restrictions. A demo version of the m-KMS shall be available online at the completion of the project and users shall be able to provide feedback on their mobile experience.

REFERENCES

Frappaolo, C. (2006): Knowledge Management, Capstone, Mankato. Guy, R. (2009). The Evolution of Mobile Teaching and Learning, Informing Science, Santa Rosa. Lindholm, C.; Keinonen, T. (2003): Mobile Usability: How Nokia Changed the Face of the Mobile Phone,

McGraw-Hill Professional, New York. Lumsden, J. (2008). Handbook of Research on User Interface Design and Evaluation for Mobile Technology,

Information Science Reference. Hope, P.; Walther, B. (2008): Web Security Testing Cookbook: Systematic Techniques to Find Problems

Fast, O’Reilly Media, Sebastopol. MacGregor, R. S.; Aresi, A.; Siegert, A. (1996): WWW Security: How to Build a Secure World Wide Web

Connection, Prentice Hall, New Jersey. O’Connel, M.; Smith, J. (2007): A Guide to working with m-Learning Standards, Department of Education,

Science and Training, Australian Government, Sydney. Rabin, J.; McCathieNevile, C. (2008): „Mobile Web Best Practices 1.0”, http://www.w3.org/TR/mobile-bp/,

retrieval date: October, 1th 2008. Roceanu, I.; Stefan, V.; Popescu, V.; Popescu, M.; Gramatovici, L.; Lazo, F. (2009): “Knowledge anywhere,

anytime based on the wireless devices”, The 5th Scientific Conference eLearning and Software for Education, Bucharest, April 2009

Shearer F. (2007): Power Management in Mobile Device, Newnes, Oxford. Shneiderman, B.; Plaisant, C. (2004): Designing the User Interface – Strategies for Effective Human-

Computer Interaction, Addison Wesley, Harlow. Shneiderman, B.; Plaisant, C. & Cohen, M. (2009): Designing the User Interface: Strategies for Effective

Human-Computer Interaction, Addison Wesley, Harlow. Smith S. (2007: “Mobile Learning”, http://newsletter.alt.ac.uk/e_article000729140.cfm Stănescu, I.; Ştefan, A. (2008:. “Analyses on the Current State of Development of Web Services on Mobile

Device”, unpublished research, Code2Mob Project, ATS Ştefan, V.; Stănescu, I. (2009): “Capabilities and Restrictions of Mobile Devices”, unpublished research,

MOBNET Project, Advanced Technology Systems - ATS Toma, S.; Gabureanu, S.; Fat, S. (2009): “Teaching in the Kowledge Society: The Impact of the INTEL TECH

Program in Romania”, Agata Publishing H., Bucharest.

e-Tutor - An Approach for Integrated e-Learning Solution

Pradipta Biswas1 and S. K. Ghosh2

(1) Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, England

[email protected] (2) School of Information Technology, Indian Institute of Technology, Kharagpur-

721302, India [email protected]

Abstract With substantial growth in multimedia technology and increasing availability of computer systems, there is thrust towards computer-based training, which uses interactive text, audio, visuals and animation, in a self-paced mode. End-users’ (i.e., students’) satisfaction levels have seen a marked improvement with the use of these modern methods of education technology. The present paper proposes a framework for integrated e-learning environment. Our system will have advanced e-learning features like provision for integrating multiple simulators for different subjects, integrated student performance evaluation system etc. The novelty of our system lies in the creation of an integrated framework that will cover all the aspects of teaching activities starting from classroom lecture, laboratory work and final evaluation. An operational prototype of the system is used in a limited way in a premier engineering institute and the result is quite encouraging to use the system of evaluation for a longer duration.

Keywords: e-Learning, Computer based Teaching Tool, Education Technology, Simulator, Data Warehouse

1 Introduction There is an increasing use of computer as a teaching tool, especially due to availability of a plethora of interactive computer based teaching packages that can supplement classroom lectures. However, for some subjects, laboratory work is an integral part of classroom lectures – the subject cannot be assimilated without the laboratory work. Realizing the importance of the hand on experiments as part of a course, recent researches have focused on integrating simulator or software tool with traditional one-dimensional computer based teaching tool. Statutor software [1] is an attempt that is designed to simplify the learning and teaching of statistical concepts, especially those related to sampling distributions based on sampling from a population. Another such initiative is Pegasus [2]. This software helps students to visualize laboratory work with a 3-phase induction motor. Besides the education technology departments of Universities, some commercial products are also available to facilitate learning of basic principles. DENFORD Machines & Systems Company has developed CNC Desk-Top Tutor for understanding the basic principles and developing practical skills in Computer Numerical Control (CNC) [3]. Network for Inclusive Distance Education [4] has developed some


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interesting interactive learning product like Digital Frog International, Snowbird software etc. They have taken a novel approach to spread the learning in an interactive way to disabled students also. One such software is “A Digital Field Trip to the Rainforest” which offers self-voicing for users who have visual disabilities. In [5] some Interactive Learning Modules are discussed for Electrical Engineering students which provide interactive and animated simulations, problem sessions and also online guidance. The concepts of Virtual Reality are used to design a collaborative environment for easy understanding of molecular biology, DNA structure etc. for secondary standard students [6]. In [7] some technical details of providing interactivity (about use of Flash Animation or JAVA Applets) and some conceptual details of building a learning tool has been given. In [8] a web based virtual laboratory system is being proposed that pioneers an approach of using VRML and XML in the building of simulation and animation. An intelligent multimedia tutoring system has been proposed in [9] for Cardiac Diseases.

Most of the existing e-learning systems are targeted towards very specific and specialized areas (e.g. 3-Phase induction motor or Computer Numerical Control etc). The term ‘Virtual Laboratory’ has been used at [8]. The high level aim of our project is same as [8] but our approach is a more generic one. The present work aims at developing a framework that consists of simulators for more than one subject (the subjects may vary from Communication Engineering to basic subjects, like Physics, Chemistry etc) and on-line teaching and evaluation modules. The simulators are so designed that they will help students to understand the basic principles of a subject through multimedia aids. Most of the multimedia tools used in e-learning or web learning packages are high end animations (JAVA Applet or Flash files) rather than a simulator in true sense. Our simulators provide more freedom to the user in terms of designing an experiment. The novelty of our approach lies in its integration and interaction features - a single package enables users to upload and read lecture slides, to simulate practical demonstrations for different subjects and to take evaluation using an interactive evaluation system.

The paper is organized as follows. In section 2 an operational overview of our system is presented. Following the operational overview the system is designed in section 3. Section 4 states the present status of the system. We pointed out the novelty of the system in section 5. Finally we concluded in section 6.

2 Operational Overview Our system operates in three phases to construct and properly use a student model. These phases are

1. Initialization Phase 2. Running Phase 3. Assessment Phase

These system phases conform to the regular course calendar. The initialization phase takes place before start of a course. The running phase runs with the course. After the end of the course, the students’ and teachers’ performances are evaluated in the assessment phase. The whole operation can be visualized through the activity diagram shown in Figure 1.


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The initialization phase mainly concerns with database fill up with curriculum details and demographic information. A course is broken up into a number of subjects. Each subject is further classified into chapters or topics and a topic is broken up into some concepts. As for example a secondary level science course can be divided into subjects like physics, chemistry, biological sciences and mathematics. Physics can be disintegrated into topics like optics, magnetism, mechanics etc. The topic ‘mechanics’ includes concepts like free body diagram, inclined plane, momentum etc. The ontology of a course is defined as shown in Fig. 2. When this ontology will be defined for several subjects, we can define surmise relationships among the concepts and develop a knowledge space for a student easily [10]. As shown in Fig. 2 each topic, concept and question is given a difficulty index. Questions are associated with an expected answer time also. These difficulty indices are used for assessment of the student. Initially when the system is installed for the first time, the difficulty indices is assigned a value based on an assessment made by experienced teachers’.

Fig. 1 Main Activity Diagram of the system


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In the running phase, the teacher can periodically evaluate the class performance by designing online examinations or quiz sessions. These examinations or quiz can be designed using the existing question-answers within the database or by inserting new questions and answers. Even the course instructor can add new topics or concepts also during this running phase. Short-term assessment can also be carried out by manually analyzing the points scored by the students during an examination. After the end of the course, the final assessment can be carried out. The final assessment will not only consider the immediate performance of a student in a single course, but also takes care of historical data available about the students, teachers and subjects.

3 Design of the system The system is designed according to its operational life cycle. The front end of the system will consist of three modules

Upload Module: Using this module a teacher can upload the lecture slides/video within the system.

This module will also help the instructor to upload a set of question and sample answers to the system. This question answers will be used in the evaluation process.

Use Simulator: Simulator module of this project can be used to simulate different laboratory experiments in different subjects.

Evaluate: The evaluate module can be used to evaluate students (replacing traditional classroom examination). A student can also use this function for self-evaluation.

The backend will consist of an online database and a data warehouse. The details of the backend and the point calculation technique using it are discussed in a separate paper [11].

4 Present Status of the System Currently an operational prototype of the system is implemented on a multimedia-enabled based Pentium-IV system (with standard configuration and Windows operating system). The successful implementation of the system largely depends on the proper planning of the course in terms of lecture modules, experiment sets and evaluation plan for the particular domain. Present implementation includes development of a virtual classroom module, online examination module and two simulators for communication engineering and system programming. In the following sections a brief outline of the system will be presented. 4.1 Virtual Classroom Module The virtual classroom module aims to simulate basic classroom activities within a computer screen. In the virtual classroom of our system, there will be provision to present

Fig. 2 Ontology of the

course


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a video lecture and (or) a slideshow synchronously. The upload module can be used to upload lecture slide or video lecture. There will be a writing pad in the screen where students can take notes and can store for future reference. 4.2 Simulator Modules The system is designed in a way that third party simulators can also be easily integrated with the system. Currently the system is integrated with two simulators-one for communication engineering and the other for systems programming. Both of these two simulators aimed to visualize complex operations to students. The next two sections will present an overview of the simulators with examples of their usage. 4.2.1 Simulator for Communication Engineering The simulator for Communication Engineering can be used to simulate basic signal processing operations like addition, subtraction, integration etc. It can also simulate modulation techniques like Amplitude Modulation, Frequency Modulation, Delta Modulation, QPSK, GMSK etc. Each of these signal operations can be demonstrated with all intermediate steps for easy assimilation of students. As an example of its usage, a modulation operation viz. Pulse Width Modulation (PWM) is demonstrated in the next section Demonstration of Pulse-Width Modulation The process starts by drawing a Baseband signal. Fig. 3 shows a Sine wave and its frequency response. In Fig. 4 the PWM Waveform (in blue color) is shown. Fig. 5 gives the frequency response of the PWM waveform (in gray color). Then the PWM waveform is demodulated. The Baseband signal, the demodulated signal (in yellow color) and their correlation are shown in Fig. 6. Fig. 7 shows the modulating, modulated and demodulated waveforms simultaneously. Finally the frequency responses are drawn again in Fig. 8. It has been shown the frequency response of the modulating and demodulated waves overlap, as expected.

Fig 4. Baseband signal and PWM

Waveform Fig 3. Baseband signal and its frequency

Response used in the demonstration of PWM


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Fig 6. Baseband Signal, Demodulated

Signal and their Correlation

Fig 8. Baseband Signal, PWM Waveform, Demodulated Wave and their Frequency

Responses 4.2.2. Simulator for Systems Programming The simulator for system programming is developed to illustrate students the sequence of actions occurred inside a computer for executing a program. Most of the practical courses on system programming generally start with 8085-microprocessor programming. The simulator presents a step-by-step analysis of an 8085 assembly language program execution. It consists of four modules viz. Editor, Assembler, Loader and Debugger. Screenshots of each module are shown from fig. 9 to fig. 12.

Fig. 10. Screenshot of Assembler

Fig 5. PWM Waveform and its Frequency Response

Fig 7. Baseband Signal, PWM Waveform and Demodulated Wave

Fig. 9. Screenshot of Editor


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Fig. 12. Screenshot of Debugger

The editor instructs the user to write an assembly language program or importing a

previously written program. The assembler takes a starting memory address and run a two-pass assembler program. The user can see Symbol Table or the Error Table from the assembler. The loader simply loads the object code. Optionally, the user can also relocate the object code using the Loader. Finally the debugger executes the object code. The user can also step over through the object code. After execution, the debugger allows the user to see any memory location, register or system flags. In the next section, the system is explained with an 8085 Multiplication program.

The 8085multiplication program is shown in Fig. 13. The assembler produces the object code shown in Fig. 14. Fig. 15 shows the relocation operation by the Loader after relocating the program from address E000 to 9000. The red circles in Fig. 15 show the code modifications due to relocation. Finally the Debugger executes the program. The register values and Flag Values at each step of execution are shown in Fig. 16.

Fig. 13. Source Code of a Multiplication Program

Fig. 11. Screenshot of Loader


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Fig. 14 Object Code of the Multiplication Program

Fig. 15 Object Code after Relocation from E000 to 9000 address

Fig. 16 Register Content and Flag contents at each step of execution and

Memory Content after execution


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4.3 Online Examination Module The online examination module takes a set of questions and answers as input. Optionally the question set can be divided into 2 two 8 sections. The questions in each question set are presented sequentially (Fig. 17). There is a mechanism to store response time and given answer of each question. At any stage of examination, a student is free to see his status (Fig. 18). In the status window, all of the questions of the present section with the given answers and number of unanswered questions will be shown.

Fig 17. Screenshot of Online Examination Module

Fig. 18. Screenshot of the status window of Online Examination Module

5 Novelty of the System Integrated Approach: Our system is not merely an e-learning package for a particular subject, rather it can be served as a virtual college where course instructors can upload lectures, monitor the progress of students and evaluate them. Besides going through the lecture slides, students can also run simulations of laboratory works. The system will be


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particularly useful for students of under-developed areas where it is not always possible to construct a high-end laboratory with skilled instructors.

Modular Design: We developed the system in a modular fashion such as any module

of the system can be used independently from the others. So during deployment, any module of the system can be replaced by a more customized one or new modules (e.g. simulators for different subjects) can be easily integrated into the system.

Intelligent Evaluation: The evaluation module of the system [11] is particularly

important. It consists of a database as well as a data warehouse for storing information about teaching and learning at a very detailed level. The data warehouse can be used to calculate performance metrics for any possible groups of students, teachers and subjects. As for example, we can calculate metrics very efficiently indicating performance of mid-worker student in Optics, performance improvement of students during first half of a course etc. In a decision-making scenario, these metrics may help in providing enough insight into the assimilation capability of students and teaching capability of teachers. Once measured properly for adequate length of time, these metrics can also be customized to provide other useful utilities like developing a student model, measuring utility of a course modification, quantifying institutional performance etc.

6 Conclusions The present paper aims at merging “e-teaching” with “e-laboratory” – thus making “e-learning” more effective. The teaching tool will be an interactive audiovisual system, which will break up the course in a series of lectures, computerized practice sessions and assignments. The integrated simulator can be used to visualize the operational environment without a practical laboratory set up. The framework is accompanied by a personalized student evaluation module that can provide many other useful information like utility of a course modification, institutional performance etc. An operational prototype of the system is used in a limited way in a premier engineering institute and we hope the system will be particularly useful for students of under-developed areas where it is not always possible to construct a high-end laboratory with skilled instructors.

REFERENCES

Wolfe Robert A. (1991), “Statutor Version1.23 A computer-based teaching tool for statistical concepts”.Available:

http://archives.math.utk.edu/software/msdos/statistics/ statutor/statu123.readme, Accessed on: 29th March 2006

Avouris N.M. et. al.(2000), “Development and evaluation of a computer-based laboratory teaching tool” Available:www.ee.upatras.gr/hci/papers/j21_avouris-tselios-tatakis-00.pdf, Accessed on: 29th March 2006

Morozov E(1996), “Implementation of computer based teaching Systems for professional training in Computer aided engineering” In Proceedings of the ICDED’96

Interactive Learning Tools; Network for Inclusive Distance Education(2006); Available:http://nide.snow. utoronto.ca/Interactiveindex.html, , Accessed on: 31st March 2006


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Millard, D.L.(2000), “Interactive Learning Module for Electrical Engineering Education”, In Proceedings of the Electronic Components and Technology Conference, 2000. 2000 Proceedings. 50th , 21-24 May 2000 Pages:1042 – 1047

Halvorsrud R. et. al. (2004),” Designing a Collaborative Virtual Environment for Introducing Pupils to Complex Subject Matter” In Proceedings of the third Nordic conference on Human-computer interaction October 2004

Woolf B. P.(1996), Intelligent Multimedia Tutoring System; Communication of the ACM, April 1996 Vol. 39, No. 4

Shin D., Yoon E., Lee K., Lee E.(2002), A Web based interactive virtual laboratory system for unit opeartions and process systems engineering education: issues, design and implementation, Computers & Chemical Engineering, Volume 26, Issue 2, 15 February 2002, Pages 319-330

Chen C., Lee,H. Chen Y.(2005), Personalized e-learning system using Item Response Theory, Computers & Education, Volume 44, Issue 3, April 2005, Pages 237-255

Dietrich A. et. al., (2006) Current Trends in eLearning based on Knowledge Space Theory and Cognitive Psychology Available at: www.research-it.at/ ~ac18008a182527705af0348c10147878d887feb,, Accessed on: 15th July 2006

Biswas P., Ghosh S.K. , An Universal Assessment Methodology for Evaluating Students' and Teachers' Performance in an Academic Institute, Proceedings of International Conference on Cognitive Systems (ICCS ’05), Available at : http://www.niitcrcs.com/iccs/papers/2005_73.pdf , Accessed on 24th July 2007.

A Multilingual Virtual Environment for Shoe Design Training

M. Sahin1, A. Mihai2, S. Yaldiz1, M. Pastina2

(1) Technical Science College of Selcuk University (Turkey)

(2) Gh Asachi Technical University (Romania) [email protected]

Abstract The objective of this paper is to present a virtual environment developed for shoe design training in English, Romanian, Turkish and Greek. http://www. vtcforshoedesign.com is a virtual training tool as a product of LdV projects under LLP program. The virtual training centre is a good example of the development of innovative practices in the field of vocational education and training, which is One of Leonardo da Vinci General Objectives. The virtual training tool aims to improve the Quality of VET systems and practices by contributing to “Learning to learn”, which is one of Lisbon Key Competences. The paper displays how the developed content has been transferred to the virtual environment with visual aids. The paper focuses on the multilingual aspect of the modules within the virtual environment. Key words: Virtual Environment, Shoe Design, Virtual Training

1. Introduction Virtual reality can be defined as a technology allowing a user to interact with a computer-based environment which may consist of a simulation of the real world or an imaginary world. Many of such virtual environments are based on audio and visual experiences reflected on computer screens. These environments can have additional properties with simulations. These simulated environments can be very similar to the real world. Myron Krueger used "artificial reality" as term in the 1970s, but the origin of the term "virtual reality" can be traced back to the French playwright, poet, actor and director Antonin Artaud. Artaud described theatre as "la réalite virtuelle", a virtual reality "in which characters, objects, and images take on the phantasmagorical force of alchemy's visionary internal dramas" [1]. The earliest use cited by the Oxford English Dictionary is in a 1987 article entitled "Virtual reality" [2]. Michael Heim [3] identifies seven different concepts of Virtual Reality: simulation, interaction, artificiality, immersion, tele-presence, full-body immersion, and network communication. To Heim, virtual reality already exists and he deigns to communicate to us via the dead tree medium of books. So strap on your virtual eye phones and open the covers and prepare yourself for a roller coaster ride through the labyrinths of hypertext and cyberspace. Heim also identifies the main points that distinguish our external reality from virtual reality? His answer is 1) natality (we are born), 2) mortality (we die), and 3) temporality (we remember past happenings). These limits, he says, "impose existential parameters on reality, providing us with a sense of


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rootedness in the earth (a finite planet with fragile ecosystems)." I would agree with him, except I consider the earth to have a robust ecosystem, to be a robust planet, not a fragile one. 2. The Aim of the Paper This paper aims to introduce VTC-SHOE, Virtual Training Centre for Shoe Design, as a model of multilingual virtual training environment used in vocational education and training. The Virtual Training Centre for Shoe Design is a virtual environment for training for all those with an interest in shoe design field of vocational education and training. Experts in the field can share and exchange knowledge and experience with associates within and outside the European Union through this centre. The project’s scientific and pedagogic objectives are in tune with the main priority in Lifelong Learning Programme. Through the various research and development projects, partners have developed training materials for shoe design. These materials have been transformed into the native languages of the partners. This indicates that the innovative e-content, developed within the VTC-Shoe project can easily be translated to various languages too. This virtual training centre formed in this field and its application constitutes the first and good example for virtual learning in national vocational training systems. It helps to improve and upgrade competences and skills of staff and exchange experiences over the virtual training centre. It also increases the work opportunity by helping young generation to use Information Technologies. Virtual Reality is an efficient tool in education and training as education people tend to comprehend images faster than the text lines. Learners can actively participate in the learning process and are attracted by the visual information rather than boring texts. Simulations help them to have the training that would otherwise be too costly. This kind of training is preferred mostly in aviation to train pilots that would be too expensive and dangerous. When we use this training tool in the class rooms, it is certain that it will increase student participation and Classroom activities will use VR tools for hands-on learning, group projects and discussions, field trips, and concept visualization [4].

3. Importance of Virtual Training in Vocational Education and Training During the 60's and 70's, teaching and learning tools were nothing but a piece of chalk and a blackboard eraser, teachers and students who met each other face to face inside the classroom during class. In the 80's, videotape programs were used as teaching aids. In the 90's, one-way teaching by computer arrived. And finally today's advanced computer and information network technology has revolutionized our teaching and learning methods. In accord with the development, learning environment has also changed. Students can listen to their teacher or trainers in distant classrooms through PCs and get a simultaneous view of their teachers and texts as well. They can ask questions and record the "class" for repeated viewing. Training organizations can conduct professional training directly via the computer network. These learning environments are not so different from a teacher-guided class with discussions and tests as well [5, 6].


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In the report “Studies in the Context of the E-learning Initiative: Virtual Models of European Universities”, a key concern was how virtual mobility is being supported in European universities through ICT integration and e-learning [7]. The study found that the majority of universities face major challenges in promoting ICT integration. ICT strategy is very important and those universities that have an ICT strategy are significantly ahead in integration of ICT in administration and organisation and networking. Integration of ICT and e-learning is politically important in the EU in terms of internationalisation and globalisation of education, student demand and interest in increasing the quality of education through ICT. At the national level, integration of ICT should become a key priority with national and regional institutions making a commitment to ITC and the development of networks. There must be increased national flexibility with a commitment to support common standards of quality and assessment and to develop national and international metadata standards.

4. VTC-Shoe as a Training Tool The virtual training centre (http://www.vtcforshoedesign.com) is a portal which has the following sections:

VTC-Shoe is the title of the product, which is the main training tool developed. The product is financed by the Executive Agency (EACEA) in Brussels under LdV Development of Innovation program. The product has been produced in English and then transformed into the native language of each partner. Each flag in this part represents the language version of the tool. The tool is accessible only through membership by getting a user name and password. The buttons of the content are for Address Database, which is the list of the addresses of the footwear related companies in each country. Lessons have been formed according to the common curriculum developed before the start of lessons. This section consists of four parts as well as the Introduction to VTC, Approach and Methodology used in the development of the content.


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Part I covers the lessons related with foot focusing on the knowledge on foot anatomy and biomechanics applied to footwear design and pattern making. Part II is about footwear. It covers the lessons about materials used for footwear products, footwear structure, functions and classification criteria, lasts for footwear industry, footwear technology and technological allowances for pattern making. Part III consists of the lessons related with measurements and tools used in footwear design. The main topics are foot anthropometrics, measurement systems and tools for pattern making. Part IV covers the lessons related with design and pattern making:

The button Tests includes the tests developed for the assessment of each lesson based on an interactive approach. Animations and Videos are the section that includes movies and animations classified according to the lessons:


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Design Collection includes the designs made by the trainers and trainees. Press News is the section to serve the dissemination activities of the product through printed or visual media. The trainee can be in contact with the trainer or the product developer by using the contact form and can have access to useful links. 5. Pattern Making Loafers: Sample Lesson The sample lesson chosen from Part IV of the training centre is lesson 8: Pattern Making for Loafers. The following slides are presented just to demonstrate the multilingual aspect of the product rather than the content details.

Figure 1: English version of Unit Descriptor, Topics and Content


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Figure 2: Romanian version of Unit Descriptor, Topics and Content

Figure 3: Turkish version of Unit Descriptor, Topics and Content

Figure 4: Greek version of Unit Descriptor, Topics and Content


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Figure 5: English version for Step 1: Mark the ball points (3D Modeling of the Loafers)

Figure 6: Romanian version for Step 2: Draw the girth’s reference line

(3D Modeling of the Loafers)


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Figure 7: Turkish version for Step 3: Mark the height of the quarter (3D Modeling of the Loafers)

Figure 8: Greek version for Step 4: Draw the auxiliary line for back part of the quarter (3D Modeling of the Loafers)

6. Conclusion VTC-SHOE is a multi-lingual virtual environment in which the shoe design training is served in English, Romanian, Turkish and Greek according to the curriculum developed for this purpose up to intermediate level. As a training tool, the curriculum is in accord with the approach, methodology and techniques required for virtual training. As it is accessible by anyone who has membership or permission, anyone who is interested in


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shoe design training can benefit from this training tool. The audio and other visual aids contribute to its attractiveness for a trainee or trainer in this field. In addition, the animations, quizzes and design collection can further contribute this tool to become more attractive and effective in training.

Since this training tool is in English, Romanian, Turkish and Greek version, it can help its scope and effect as a training tool internationally. In this way, it can be transferred to similar fields such as furniture, textile, air conditioning etc. The approach, methodology and techniques used in this training centre can be used as a model in developing and improving other training programmes in particular in the area of new information technology applications in related sectors.

The VTC-SHOE will establish networks of people who are engaged in footwear business and training. Thus, it will support the entrepreneurial community, including small and medium businesses, through collaboration and community support. The mission of the VTC-SHOE should be to support economic development by facilitating footwear design training that empowers socially and economically diverse people to strengthen and sustain growth opportunities in existing businesses or in the planning and marketing of a start-up business.

REFERENCES

[1] Erik Davis, Techgnosis: myth, magic and mysticism in the information age, 1998 [2] Garb, Yaakov (Winter 1987), "Virtual reality", Whole Earth Review (57): 118ff. [3] Michael Heim The Metaphysics of Virtual Reality, Published by Oxford University Press, 1993. [4] Bricken, M., "Virtual Reality Learning Environments: Potentials and Challenges." Human Interface

Technology Laboratory, University of Washington, Seattle, WA: 1991. [5] Şahin M., Bilalis N., Yaldız S., Antoniadis A., Ünsaçar F., Maravelakis E., (2007): Revisiting CNC

Training–A Virtual Training Centre for CNC. EPVET 2007: International Conference on E-Portfolio Process in Vocational Education, Present and Future, 2-3 May 2007, Bucharest, Romania

[6] Şahin M., Yaldiz S., Ünsaçar F., Yaldiz B., Bilalis N., Maravelakis E., Antoniadis A. (2007), Virtual Training Centre for CNC: A Sample Virtual Training Environment, ICVL 2007: The 2nd International Conference on Virtual Learning, 26-28 October, 2007, Constanta, Romania

[7] Ramboll, PLS, (2004): Studies in the Context of the E-Learning Initiative: Virtual Models of European Universities (Lot1). Draft Final Report to the European Commission, DG Education and Culture. Available At Http://Elearningeuropa.Info

Educational software for the simulation of virtual dynamical systems

Puşcaşu Gheorghe – [email protected]

Codreş Alexandru – [email protected] Codreş Bogdan – [email protected]

Stancu Alexandru – [email protected] Universitatea Dunărea de Jos, GalaŃi

Abstract In this paper some aspects regarding the implementation of the control algorithms for virtual processes are presented. Virtual reality represents an easy approach to study the behaviour of the process. Using virtual reality one can achieve knowledge about the influence of the input and the output signals on the dynamical systems. Along the implementation of the virtual system it is necessary to do a solid modelling of all essential aspects of the real process. However, the virtual system is included into a control loop. Also, the actuator of the control loop is a virtual system and it can be servomotor, DC motor or step by step motor. The behaviour of the virtual actuator is based on the mathematical models or the static characteristic. To achieve compatibility between virtual systems and real systems it is required a card acquisition for the signal’s adaptation. This educational software has two advantages. Firstly, when using the card acquisition, the virtual approach is very similar to the real one. In the virtual approach the control of the virtual system is made with electrical signals. Secondly, it is possible to analyze the system when reaching its limits. Keywords: Educational software, virtual process, virtual reality, modelling

1. Introduction Virtual reality is an artificial environment that is created with software and presented to the user in such a way that the user suspends belief and accepts it as a real environment. The simplest form of virtual reality is a 3D image that can be explored interactively at a personal computer, usually by manipulating hardware interfaces (Kovach, 1997; Peterson, 2001).

A VR application is made of different components (Burdea and Coiffet, 2003; Vince, 2004) which can be described as:

a) The scene and the objects. The scene corresponds to the world in which the objects are located. VR contains lights, viewpoints and cameras. The objects have a visual representation with colour and material properties.

b) Behaviours. The objects may have behaviours (Willans, 2001). For instance, they can move, rotate, change size and so on.

c) Interaction. The user must be able to interact with the virtual world and its objects. For instance, a user can pick up some objects or he can drag an object. This may be


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achieved by means of a regular mouse and keyboard or through special hardware such as a 3D mouse or data gloves (Vince, 2004).

d) Communication. Nowadays, more and more VR applications are also collaborative environments in which remote users can interact with each other. To achieve this, network communications is important.

e) Sound. VR applications also involve sound. Some research has been done over the last 20 years in order to simulate sound in VR application. In this paper, the modelling of the sound will not be addressed.

The developing of the different components of a VR application is not an easy task and during the last twenty years, a number of software tools have been created to ease the developer's task. These tools can be classified into authoring tools and software programming libraries. Virtual reality can be used for the simulation of a real environment in training and education and for the development of an imaginary environment in a game or interactive story.

The most important applications of the virtual systems are those used for training flight pilots, drivers and ship commanders (Wolffelaar and Winsum, 1995). Besides the basic training, the simulators can be used for training in risky situations that cannot be exercised in real life. This paper contains educational virtual processes used for system analysis and synthesis of the command. The connection between the virtual process and the control computer is done using a hardware interface. In this way system analysis and system control are identical with the real system from the user’s point of view.

2. The components of a virtual system used in the analysis of dynamic systems

The virtual systems (Willans and Harrison, 2001) used in this educational software allow the analysis of the dynamic systems using the same input/output sizes of a real system. In this way the control software for the virtual system is 100% compatible with the control software for the real system. Besides other advantages, the virtual process allows the user to train in limit conditions without affecting or damaging the system.

The structure of a virtual process used in the educational software is shown in figure no. 1.

Figure 1 The structure of a virtual process


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Software and hardware components of the process are shown below: The virtual process corresponding to a real system allows observation of the system

components behaviour during analysis. Besides standard components the system also contains limiters and transducers. Also, the virtual system allows observation from different angles and distances. In this way it is possible to watch and observe different system components during the analysis. The system shown above consists of a suspension which contains a spring and a hydraulic shock absorber.

The mathematical model of the process is used as an interface between analysis procedures and the virtual system. The model must catch all important aspects of system dynamics. On the other hand, the mathematical model of the process is subjected to restrictions, taking into consideration that the sizes of the process must belong to well-defined intervals. Numerical integration of the mathematical model is done using Runge-Kutta methods. This method was chosen because it allows nonlinear dynamic system integration using variable integration step.

Virtual actuators are used to illustrate the fact that in order to act on the process you need to convert and amplify the control signal using dedicated components. In many cases the actuators consist of a dynamic system with an associated mathematical model. In the case that the process is much slower than the actuator, the actuator is approximated with a linear transfer characteristic.

The adaptation interface is a hardware component with the following characteristics: • It converts the control signals received from the process computer, from electrical

values to numerical values used as inputs in the mathematical model; • It converts the mathematical model numerical outputs to electrical signals.

This interface creates a perfect compatibility between a real system and a virtual system from the user’s point of view. The control signals used for the virtual actuators are similar to those used with real actuators. In this way, in order to analyse and control the virtual system any hardware configuration can be used: PC with data acquisition card, microcontroller, PLC etc.

3. Mathematical modelling of the dynamical components of a virtual process For a better understanding of the process, an accurate modelling of all dynamical components of a virtual process and actuators is necessary (Conninx et all, 2006). In this paper, a mathematical model of a car’s suspension and also of the actuators is presented.

Suspension Modelling Oscillation analysis of car’s suspension in vertical plan represents one of the most

complicated problems of the car’s dynamics. The complexity derives from the coupling elements and nonlinearities of the car’s suspension. In virtual reality the simulation of road humps is made with the help of an actuator (DC motor or servomotor).

The model used to study the suspension’s behaviour on different road humps is presented in figure no.2. Car’s suspension is made with one elastic and one hydraulic damper defined by k and C constants. The car with constant weight m, during the movement on the road, encounters a hump of height u which causes a displacing y of the car’s body on vertical.


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In this case, the equation of the vertical motion uses D'Alembert principle:

0)()( =−+−+ uyCuykym &&&& (1) or

ukuCyCykym ⋅+⋅=⋅+⋅+ &&&& . (2) where :

m – the body weight; k – the elastic damper constant; C – the hydraulic damper constant; Because equation (2) contains 2-nd order

derivative, in order to integrate it must be brought it to a input-state-output form. After a series of transformations the following set of equations is obtained:

⋅+⋅−=

⋅++⋅−=

um

kx

m

kx

um

Cxx

m

Cx

12

211

&

&

(3)

1xy = , Where x1, x2 represent the state variables, u – the command, y – the output, and m,k, C

- the same meaning as in equations (1) and (2).

Actuator modelling The actuator amplifies the power of the control signal. In many situations actuators are

dynamical systems. The most known actuator is the DC motor. If the process is described by time constants greater than the DC motor ones than these are approximated with the help of input-output static characteristic.

In this paper the following types of actuators are used: • the DC motor; • the real servomotor; • the ideal servomotor.

The DC motor has the mathematical model [13] described by the following set of differential equations:

⋅−⋅−⋅=

⋅−⋅−⋅−=

mJJ

Fi

J

K

uLL

Ki

L

Ri

a 1

1

2

1

ωω

ω

&

&

(4) where:

ω – the rotor speed [rad/s]; i – the intensity of rotor current [A];

Figure 2 Suspension model


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m –the load torque; R – the rotor resistance [ohmi]; L – the rotor impedance [mH]; Fa – the friction coefficient [N*m/rad/s]; J – the moment of inertia [Kg*m2] K1, K2 – the DC motor’s constructive constants [N*m*s] The real servomotor is a device that has a linear transfer characteristic but with a finite

rise time. This means that the output follows the input, but with a delay. If the input varies, the output will have a linear evolution until it reaches the size of the input (figure no.3).

Figure3 Figure 4

The ideal servomotor is the particular case of the real one, where the rise time is

infinite. In this case the output is equal to the input applied to the actuator: ue(t)=ui(t). This ideal servomotor is used because the transfer function of the process can be identified directly from data set obtained from the virtual system.

4. Case study. Frequency analysis of the virtual system – car suspension In this application the amplitude-frequency and phase-frequency characteristics will be determined. These characteristics will be obtained experimentally using deterministic and periodical signals.

Before starting the experiment it is necessary to obtain some a priori information about:

• the domain in which the input signal frequency must vary; • number of values in frequency domain for which the transfer locus will be

determined;

• the cutting frequency ω t ( 0|)( == tA ωωω );

• the frequency for which 0180)( −=ωϕ . The car suspension (the virtual process), figure no 5, will be used in this paragraph in

order to determine its frequency characteristics.


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Figure 5 The car suspension: the virtual process

where: 1. actuator – can be DC motor, real or ideal servomotor. 2. damping spring – damping out of oscillation 3. viscous damper 4. motion transmission from the actuator 5. guide element 6. elevating stops 7. mass

Data processing The methods of automat data processing resulted from conducting the experiment will

determine the real and the imaginary part of the transfer locus. Using the nonparametric representation of the system (transfer locus) the amplitude A(ω)= |G(jω)| and the phase ϕ(ω)=arg(G(j)) can be determined.

The function of partial polar correlation [4] defined for [0 T] will be used as the method for determining the transfer locus.

∫ +⋅⋅=T

yu dttuytT

R0

)()1

)( ττ (5)

where u(t) and y(t) are the virtual system (car suspension) input and output respectively. If the input signal u(t) is a sinusoidal one, the partial polar correlation function will

be: [ ] dttAtAT

R e

T

iyu )sin()(sin1

)(0

ϕωτωτ +⋅+⋅= ∫ (6)

The real and the imaginary parts will be computed for the following values of the τ : For τ =0 the equation (6) will be


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)(Re2

)0(2

ωjGA

R iyu ⋅= , (7)

And for τ =T/4 the equation (6) will be

)(Im2

)4/(2

ωjGA

TR iyu ⋅= . (8)

Figure 6 The hodograph and the amplitude-frequency characteristic

System identification In the following, the steps used for computing the real (equation 7) and imaginary

(equation 8) parts of the hodograph will be presented: • generating the sinusoidal input signal with the frequency chosen from the

frequency vector • computing the output corresponding to the sinusoidal input signal • using equation (7) the correlation function will be computed in order to obtain

the real part and using equation (9) the correlation function will be computed in order to obtain the imaginary part.

The hodograph and the amplitude-frequency characteristic obtained using the educational software for dynamical systems analysis will be presented in figure 6.


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5. Conclusions In this paper a virtual process connected with an embedded computer through an acquisition card was presented. The virtual reality offers many advantages for system analysing and for the control low synthesis. In order to approximate the real process, the models for the car suspension and for the DC motor were also obtained. In the end of the paper a case study is presented. This case study consists in frequency analysis of the car suspension system.

REFERENCES Burdea, G.C., Coiffet, P. (2003): Virtual Reality Technology, Wiley-IEEE Press ISBN: 0471360899. Coninx, K., De Troyer, O., Raymaekers, C, Kleinermann, F. (2006): VR-DeMo: a Tool-supported Approach

Facilitating Flexible Development of Virtual Environments using Conceptual Modelling, Proc. of Virtual Concept 2006 Cancun, Mexico, Springer-Verlag, ISBN 2-287-48363-2.

Kovach, P. J. (1997): The Awesome Power of Direct3D/DirectX, Softbound. Peterson M. T. (2001): 3D Studio MAX FUNDAMENTE, Ed. Teora. Puscasu Gh., Stancu Al. (2001): "TEHNICI DE IDENTIFICARE A SISTEMELOR. Teorie si aplicatii",

Bucuresti, MATRIX ROM; 260 pag. ISBN 973-685-159-1 Vince, J. (2004): Introduction to Virtual Reality. Springer, ISBN 1852337397. Voicu M. (1986): Tehnici de analiză a stabilităŃii sistemelor automate, Editura Tehnică, Bucureşti. Willans J. and Harrison M. (2001): A toolset supported approach for designing and testing virtual

environment interaction techniques. International Journal of Human-Computer Studies, 55(2): 145-165. Willans, J. (2001): Integrating behavioural design into the virtual environment development process. PhD

thesis. University of York, York, UK. Wolffelaar PC, Winsum V. (1995): Traffic simulation and driving simulation – an integrated approach, In

Proceedings of the Driving Simulation Conference (DSC’95), Toulouse, France.

Development Interactive Courses of Education in Microbiology Based on E-Learning System Applying

in Technical College of Yambol

Dineva S.1, Nedeva V. 1

(1) Technical College of Yambol, Gr.Ignatiev str. 38, Yambol, Bulgaria

[email protected], [email protected]

Abstract The purpose of the article is to represent the results of the development interactive courses of education in Microbiology based on virtual learning environment. The virtual learning environment has been created using Moodle software platform and has been implemented in many different disciplines in Technical College of Yambol. The advantages of this way of education is the unlimited access of the training materials in convenient of the learner time, as well as the interactive method of acquiring the knowledge’s in form of test or by creation of multimedia presentations. The performance of virtual study environment allows improving the efficiency of the learning.

Keywords: e-learning, Moodle, course organization, lessons, quiz, new feature in Moodle

1. Introduction The rapid development of information and communication technologies (ICT), especially the recent explosive growth of Internet capacities, offers tremendous educational opportunities. The future growth and development of e-learning technologies is, perhaps, the most important of these trends in the realm of education. In fact, e-learning in particular is slowly being accepted as one of the criteria of a progressive, innovative, and leading higher educational institution. The Internet has created a new paradigm of learning which can allow teachers and students to teach and learn collaboratively via web-designed courses (Al-Fadhli, 2009).

The development of information technologies has contributed to growth in online training as an important education method (Fazlollahtabar and Yousefpoor, 2009). New developments in information and communication technologies (ICT) to support learning have brought about increasing interest by both academic and non-academic institutions in e-learning. These developments in ICT are principally multimedia and the Internet with its World Wide Web. Interest in ICT supported learning is also fuelled by the associated (expected) cost reduction and easy expansion of education to the increasing and flexible market that is difficult to reach by traditional delivery (Abel Usoro & Bridget Abiagam, 2009).


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2. Material and Methods Moodle is a Course Management System (CMS), also known as a Learning Management System (LMS) or a Virtual Learning Environment (VLE). It is a free web application that educators can use to create effective online learning sites. Moodle is a course management system designed to help educators who want to create quality online courses. The software is used all over the world by universities, schools, companies and independent teachers. Moodle is open source and completely free to use (http://moodle.com/?moodlead=moodle.general).

Moodle is the leading open-source virtual learning environment with over 50,000 installations world-wide. Moodle is a free and open source e-learning platform designed to assist educators in creating online courses and resources (http://www.synergy-learning.com/?moodlead=synergyie.courseware). The word MOODLE is an acronym for Modular Object-Oriented Dynamic Learning Environment. It is handy for an online course that has students all over the world. Moodle has many capabilities including forums, journals (private between student and teacher), quizzes, resources, and a section for displaying assignments. Currently there are 6429 sites from 137 countries, which have registered by using Moodle. Currently there are language packs for over 60 languages (Williams, 2005).

3. Results and Discussion The architecture of Moodle is compatible with the hardware and software of Technical College – Yambol (Nedeva, 2005). The incorporation of LMS will be done during the building and use in Intranet network. We created Microbiology courses, according to the international requirements for e-learning – SCORM and IMS, and the recommendation of the administrator of Moodle (Figure 1).

Figure 1. The screen shot of the Microbiology resources – topic units

There are three different formats for the class (course) – Weekly, Topic, and Social. The weekly format organizes the class into weeks, with assignments, discussion boards,


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tests, etc, all residing in a week-by-week block. The Social format is built around a forum (bulletin board), which is good for announcements and discussions. The Topic format organizes everything by topics (or units); regardless of how long they take. Our courses are in topic format. They are used for e-learning by our students, who use the resources of their home PCs by logging into http://tk.uni-sz.bg/e (Nedeva, 2005). The online training environment enables learners to undertake ‘any time, any place’ customized training. Moreover, information technology allows both trainers and learners to be decoupled in terms of time, place, and space (Fazlollahtabar and Yousefpoor, 2009).

The Lessons module is exactly that – lessons you develop and post online for your students to navigate. Questions at the end of each page in a lesson can be multiple choice, true/false, short answer, numerical, matching, and essay. As an example, to create a question page you would decide on the type of question, give the page a title, add page contents (for example, ask the question), provide the answer(s), include feedback to be displayed depending on the student's answer, and also supply a "jump," to where the student should go next depending on the answer given (Branzburg, 2005).

The lessons of Microbiology are separated by topics (Figure 1.). After every new topic the quiz took place. Each quiz includes materials of one or several themes. Questions are stored in categories for easy access, and these categories are "published" that make them accessible. Quizzes are automatically graded, and can be re-graded if questions are modified. Quizzes can have a limited time window outside of which they are not available. Quizzes can be attempted multiple times, and can show feedback and also the correct answers, if they are in adaptive mood. Quiz questions and quiz answers are shuffled (randomized) and that option reduces cheating. Questions allow HTML and images to be included. Full activity reports for each student are available with graphs and details about each module. A database of questions has been created and can be used and re-use in different quizzes (Figure 2.).

Figure 2. The screen shot of the Microbiology resources – available quizzes, created after each topic


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Quizzes can be attempted multiple times, if desired, or restricted. Multiple-choice questions supporting single or multiple answers include: Short Answer questions (words or phrases); True-False questions; Matching questions; Random questions; Numerical questions (with allowable ranges); Embedded-answer questions (cloze style) with answers within passages of text; embedded descriptive text and graphics (Figure 3.).

Figure 3. The screen shot of the Microbiology resources – question from the quiz, adaptive mood with the correct answer, after submission of student choice.

Moodle has revolutionized the learning process, by offering an advanced and user-friendly solution for encouraging the collaborative work of students and teachers. It comes with a toolbox full of online teaching techniques that facilitate and enhance the proven teaching principles and traditional classroom activities. The philosophy behind Moodle states that through an accent on collaborative learning, students get better motivated to engage themselves in the training process (http://www.ntchosting.com/ elearning-web-hosting.htm).

Moodle allow reader and student to have full view of complete report activity of the student for each of the items. The reader can use many new techniques and web-resources (images, links, videos and etc.) to make the unit lessons more attractive to the students and enough visual, demonstrative, to give illustrative examples, where is considered necessary (Figure 4).

The student’s attending the course of Microbiology also have the possibilities to make their own presentations that are published in the e-learning virtual environment and in that way to take feedback from the reader and their collegians.

The new features that we implement in this course are described bellow (Marcais, 2009).

One of the major changes is that Moodle now uses a set of Roles throughout its system. Roles are mostly managed and maintained by your system administrator, but as a teacher, you do need to know the basic concept of the roles. A role is basically a collection of permissions defined for the whole site that you can assign to specific users in specific contexts.


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Figure 4. The screen shot of the Microbiology course – student view For example, you may have a Role called "Teacher" that is set up to allow teachers to

do certain things (and not others). Once this role exists, you can assign it to someone in a course to make them a "Teacher" for that course. You could also assign the role to a user in the course category to make them a "Teacher" for all the courses under that category, or assign the role to a user just in a single forum, giving that user those capabilities just in that forum. Roles can only be added to activities by editing the activity after it has been created.

One of the nice new enhancements to Moodle, is that you can now see exactly what your students see when they log into your course! To do this, look at the top right corner of your course. Using the choices from the drop-down menu, you can switch temporarily to another role.

The roles available are the same as the roles that you are allowed to assign to people. Your Moodle administrator can make additional roles as needs arise on your Moodle system. Any of the permissions given to users in the Moodle system can be added or removed from these custom roles. For example, in our system… we have created a role called “Student – No Time Limit on Quizzes” or “student_notimelimit” for short. This role is identical in every way to a normal student role… EXCEPT… it has been set to ignore any time limits placed on quizzes. This means that if you have any students with

learning disabilities who need extended time on their quizzes, you can simply set their role in your class as a “student_notimelimit” rather than as a “student”. Then, every time they take one of your quizzes… they won’t be timed, even if you have a time limit set for the other students. The possibilities for custom roles are extensive, and certainly add a huge level of flexibility to the Moodle system.


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The Backup section now allows you to choose not only the type of activity you want to backup but you can also choose between individual activities as well. All you have to do is choose the individual activity you want, decide if you want to include the user data, and then you can back up your course as usual. The great thing about this enhancement is that now you know exactly what is being archived! Likewise, when you restore a course, you will have the option of exactly which activities you wish to restore to your course.

When you use the Import Course Data link, you will also have the option to import items on an activity-by-activity basis. This makes it much less confusing when you’re trying to transfer information between two classes.

This page allows you to remove user data from your course, while retaining any activities and other settings you may have implemented in your course. Types of user data you can remove include: Students, teachers, course events, logs, and/or groups. You can also reset the course start date. Also, you have the option to remove posts and/or subscriptions from any forums created in your course. USE CAUTION when using this feature, because once you click the “reset course” button, your user data from the course is gone for good!

The link in the Administration block that was previously named “logs” has changed its name to “Reports”. There are now additional features available in this section. The reports page is divided into four boxes, or sections.

The top section entitled “Choose which logs you want to see:” is almost identical to the previous version. However, you can now also narrow your results from the “all actions” dropdown menu by type of action (view, add, update, delete all changes). You can also choose how your results will be displayed (Display on page, download in text format, download in ODS format, or download in Excel format).

The second section has a link for “Activity Report”. When you click on this link, you’ll see a summation of all the activity in your course. The third section lets you run a participation report. Here, you can choose an Activity Module, a period of time to “Look back”, which users to show, and which actions to show.

The final section has a link for “Statistics” (if this is replaced by the phrase “Statistics is not currently enabled” this means that your administrator hasn’t activated this feature). When you click on the “Statistics” link, you will see graphs and tables which show how many hits there have been on various parts of your site during various time frames.

In Moodle 1.8, the concept of Groupings is introduced: a way of organizing various groups in a hierarchical structure. While this approach may prove to be more powerful, using groups is no longer as intuitive. For example, a teacher teaches four sections of the same class. The teacher could have 4 groupings (i.e. one for each section). Within those sections the teacher could assign various students to various groups within the groupings. Another great advancement is that students may now belong to multiple groups.

To add students to a group, the teacher must follow these steps: Create a grouping; Create a group in the grouping; Assign users to the group.

After you’ve created your groups, you’ll be able to edit them by using the various buttons.

One of the huge enhancements to Moodle is that it now supports blogs. Blogs allow students, teachers and administrators to have a public web log. This online journal has various settings to control who can read them. Every user can create their own blog by


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going to their profile page (by clicking on their name, anytime it appears on a Moodle page as a hyperlink). Once you are at your profile, notice that there is a tab called “Blogs” at the top.

If you made your blog entry only visible to yourself… no one else will be able to see it. If you made it visible just to anyone on the site… people will only be able to view your blog if they’re already in the Moodle system. However, most people want to find a way to share their blog with people outside of their Moodle system. To do this, your entries must be set to be available to “Anyone in the world”. world”. Once that is done, you can generate RSS feeds for your blogs. There are basically three types of blogs you can view in Moodle... a user blog, a course blog and a site blog.

The Database activity allows the teacher and/or students to build, display and search a bank of record entries about any conceivable topic. The format and structure of these entries can be almost unlimited, including images, files, URLs, numbers and text amongst other things. You may be familiar with similar technology from building Microsoft Access or Filemaker databases. One useful way to use activity in a classroom would be to use it as a student portfolio area, where students could share their work.

4. Conclusion Moodle is a Course management system (CMS) - a software package designed to help educators easily create quality online courses. Such e-learning systems are sometimes also called Learning Management Systems (LMS) or Virtual Learning Environments (VLE). It has been designed with pedagogy in mind and fully supports different learning styles (face-to-face, blended and e-learning). It has a comprehensive feature set covering all types of content ranging from basic documents, RSS feeds and videos via different types of assessments (formative and summative) to forums, questionnaires and blogs. Moodle fully supports student management, course and curriculum management (http://www.synergy-learning.com/moodle/).

Creation the virtual learning environment in the College has positive influence on the prosperity of the students, due to the more interesting and useful materials that are offered. E-learning encourages the collaborative work of students and teachers and overcomes the shortcomings of the traditional forms of learning. The online teaching techniques facilitate and enhance the proven teaching principles and traditional classroom activities. Students are more satisfy from the evaluation of their knowledge’s, because the factor of subjectivism is missing. It has been registered that students get better motivated to engage themselves in the training process.

REFERENCES Abel Usoro & Bridget Abiagam University Of The West Of Scotland, Paisley, United Kingdom, Providing

Operational Definitions to Quality Constructs for E-learning in Higher Education, е-Learning Volume 6 Number 2 2009 ISSN 1741-8887 http://www.wwwords.co.uk/elea/content/pdfs/6/issue6_2.asp#1

Al-Fadhli, Salah Kuwait University, Kuwait Instructor Perceptions of E-learning in an Arab Country: Kuwait University as a case study, е-Learning Volume 6 Number 2 2009 ISSN 1741-8887, http://www.wwwords.co.uk/elea/content/pdfs/6/issue6_2.asp#1


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Branzburg, Jeffrey, (Aug 15, 2005), How To: Use the Moodle Course Management System, http://www.techlearning.com/story/showArticle.jhtml?articleID=168600961.

Fazlollahtabar Hamed, Yousefpoor Narges, Cost Optimization in E-learning-Based Education Systems: implementation and learning sequence, Mazandaran University Of Science & Technology, Babol, Iran, е-Learning Volume 6 Number 2 2009 ISSN 1741-8887, http://www.wwwords.co.uk/elea/content/pdfs/6/issue6_2.asp#1

http://moodle.com/?moodlead=moodle.general http://www.synergy-learning.com/?moodlead=synergyie.courseware http://www.synergy-learning.com/moodle/ http://www.ntchosting.com/elearning-web-hosting.htm Marcais, Tom Moodle – Upgrading from version 1.5.3 to 1.8 Important Changes for Teachers,

https://moodle.sbc.edu/mod/resource/view.php?id=8088 Nedeva V., The Possibilities of e-learning, Based on Moodle Software Platform, Trakia Journal of Sciences,

Vol. 3, No.7, pp 12-19, 2005. Nedeva V., P. Prodanov, Zl. Ducheva, D. Nedev, Moodle Lesson Activity In Measuring The Hardness Of

Materials, Trakia Journal of Sciences, Vol. 4, No. 4, pp 20-27, 2006, pp.20-27 Nedeva V., E-learning – a condition to increase the quality of education, International Scientific Conference

The Educational Policies Of European Union, Yambol, 18.05.2006, стр.94-102 Williams, Bryan, (Sep 1, 2005) Moodle 1.4.3 For Teachers &

Trainers,http://moodle.org/file.php/29/English_Manuals/Moodle_1.4.3_For_Teachers_and_Trainers.pdf

Advantages of the Web-Based Training for the Increasing Quality of Preparation and Self-Preparation of Students from the

Specialty “Food Technology”

Margarita Pehlivanova1, Zlatoeli Ducheva1, Snejana Dineva1

(1) Technical College of Yambol, Gr.Ignatiev str. 38, Yambol, Bulgaria

[email protected], [email protected] [email protected]

Abstract

The report represents the results of implementation e-learning based lessons and quizzes in the education of students in Technical College of Yambol, Bulgaria. The e-learning is a way to use networking technologies that allow to access the training materials at any possible time, permit interacting with the training environment in convenient for the user time, that lead to improving self motivation and the effectiveness of acquiring knowledge’s. The area of e-learning study in Technical College of Yambol included courses in Informatics, Programming languages, Information technology, Common and General Chemistry, Biochemistry, Microbiology, Ecology. The results of our investigation show that the performance of e-learning system is the reason for improving the effectiveness of the education, as well as improving the motivation among students and teachers have been registered.

Keywords: e-learning, effectiveness of the education, motivation

1. Introduction The education and possibility of acquiring different competences must be available, not only in the range of the compulsory education, but also after the beginning of an active social life, if possible, without taking too much time from the professional, social and personal activities. These educational tendencies, in particular for University education, are imposed, because of the need of active involvement of the educational institutions in the development of the European educational and scientific space; the demographic characteristics of the students; the expanding globalization and stronger competition in the area of educational services, especially with the introducing of the electronic and distant learning. The implementation of Bologna strategy the EU's efforts should be directed to unification in 2010 to educational programs in all EU member states (short training courses, BA, MA, MD ect.). That means to develop and coordinate flexible, modernized curricula in all areas, which to correspond to the requirements of the labour market, and quality assurance systems (Furtunova, 2009). This demands the integration of classic and modern educational models and establishment of new ones that can give opportunity not only of acquiring knowledge and skills in a modern environment, but also to develop intellect and social skills to the students, alter the accent of the education,


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applying interactive methods, modification the roles of teachers and students. Simultaneously it is necessary the education to be hold during a convenient for the student’s time, place, way and rate.

In the management of the university education changes, regarding the integration of information and communication technologies (IT), is necessary the Boards of the educational facilities to make their choice on the market section of education services, they want to place theirs offers on and for the options for suitable and modern pedagogical technologies. For the realization of the educational policy of the university is of big importance the understanding, the adoption and exploitation of the ideas of the pedagogical stuff. Still, the modern educational technologies are only partially implemented, most of the time from particular lecturers or disciplines, not like a consistent policy and specific measures for realization (Pehlivanova and Ducheva, 2008).

2. Materials and Methods The concept of the E-learning in Technical College –Yambol, is based on the idea of using elements of electronic leaning (e-learning) and the relevant technologies. We accept the idea, that e-learning is a type of learning, which preparation, implementation and management requires using modern information and communication technologies, including Internet.

Figure 1. The Topic format of organizing, compulsory subject Microbiology, the lessons and test are organized by topics (or units), regardless of how long they will take


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It is an attribute of the global information society - born by the necessity of the modern student for more flexible and open education and becomes possible thanks to the progress of the education, information and communication technologies. The goal of the project activities is not only to enrich the traditional systems and approaches for learning, but also to develop and integrate new pedagogical technologies in an interactive environment.

During the theoretical validation of the development and integration of e-learning system in the college, we accept that the web – based learning concept is inseverable part of the Information Society concept, which technologic platform is based on digital multimedia and global communications. Education, during which www is used as a virtual environment, for introduction of the subjects and realization of the learning process.

Based on traditions and cultural mission, in the Technical College -Yambol, are placed the foundations of the e-learning. We could say that, the model, on which the learning is based, has five main components (external environment and conditions; policy; integration; practice; experience and effects) is suitable for our work. In the College activity, e-learning is base on MOODLE. As a result of our work the foundations of a technical and informational data for future distant learning took placed: virtual library with materials - lectures and exercises on some of the subjects; tests; glossaries with the terminology for the different subjects.

Figure 2. Sample list of questions in quiz module, compulsory subject Ecology, developed in the Virtual Learning Environment eDuTK


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The e-learning materials are base for raising the quality of learning; it forms a permanent interest in the students towards the studied subjects. The study materials in the self-training modules are developed and approbated (Figure 1). Tests and glossaries are also created in the college system of e-learning for the following subjects: General and Inorganic Chemistry, Biochemistry, Microbiology and Ecology.

There are three different formats for the class (course) – Weekly, Topic, and Social (Nedeva, 2005). The weekly format organizes the class into weeks, with assignments, discussion boards, tests, etc, all residing in a week-by-week block. The Social format is built around a forum (bulletin board), which is good for announcements and discussions. The Topic format organizes everything by topics (or units), regardless of how long they take (Figure 1.). Our courses are in topic format. They are used for e-learning by our students, who use the resources of their home PCs by logging into http://tk.uni-sz.bg/e-learning/.

Figure 3. The Glossary, compulsory subject Ecology, developed in the Virtual Learning Environment eDuTK

Quiz module allows the teacher to design and set quiz tests (Figure 2). Each question

has a category. When you create a new question, it is stored in the category you select. To create a new question, you must select the type of question you want from the pull-down menu. You have the option of adding, which includes: Multiple choice questions; True/False questions; A short answer question; A numerical question; Matching question; Description question; Random set; Random short answer; A special embedded question (Cloze). These questions are kept in a categorized database, and can be re-used within courses and even between courses. Quiz module includes grading facilities (Nedeva, 2005).

The Glossary offers the opportunity to create and maintain a list of definitions and terms that are specific to the content of the given area of study. The Glossary can be


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separately for each lesson or thematic to the all area of the study subject. The students can be searched or browsed in many different formats (Figure.3). It is possible to automatically create links to these entries throughout the course.

Our considerations to choose the MOODLE are based on: • First, this is Modular Object-Oriented Dynamic e- Learning Environment. • Second, it includes large community of programmers and users; • Licensed under GPL; • Translated into 60 languages (incl. – Bulgarian). Its build up by 9 modules, which could be extended and enlarged; compatible with

large number of browsers; it has integrated HTML editor; secure and safe; gives options for interface setting. Our opinion is that the main advantage, from pedagogical point of view, is that it is based on implementing the theory of the social construction, the discussing problems and individual adaptation in the process of learning.

3. Research and Results

The main ideas of the theory of e-learning in the College are based on the following principles:

• Student’s knowledge is built up more actively by interaction and communication with the surrounding environment and became significant, when it is used in a wide social context;

• The acquiring of new knowledge must be effective and students to be not only subject of training but able to interact and take experience;

• During the process of e-learning in the given environment, the students are affiliating in a small group, with its own characteristics and culture, with common values and in the process of join activity they become part of that group (Pehlivanova and Ducheva, 2008).

• There are conditions created for effective communication, feed back, individualization and creativity.

The feed back of e-learning is taken and developed into two main aspects: • Feed back “student – lecturer” as an ability of the student to contact his teacher for

different issues, which came out in the process of learning. • Feed back “education effectiveness” - ability of the student to evaluate the level of

results, the gaps in the introduction of the study material, the effectiveness of the learning.

According to the analysis of the data, this type of feed back gives a chance to the lecturer to correct the gaps and to adapt the content, according to the specifics of the targeted group, the current state of the scientific field and the labour market requirements. In order to evaluate the qualities and the effectiveness of incorporated e-learning, the inquiry research with the participation of 61 students has been made (Figure 4). The students were from the specialties “Automatics, informational and controlling technique” (37 students) and “Food technology” (24 students); from the 1st and 2nd year during 2006 year (Pehlivanova and Ducheva, 2008).


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They were divided into three age groups: first group – 19 years old (23 people); second group 20-21 years old (26 people) and third group – 22-26 years old (12 people). From the participants of the inquiry 53 of 61 were first year students and 8 students

from the second year of study; 35 with male sex and 26 female. In order to improve e-learning and carry out monitoring, in 2009 has been conducted a new survey questionnaire with 64 students (51 women and 13 - men) from the specialty «Food Technology», the first, second and third course: “General and Inorganic Chemistry”, “Biochemistry”, “Microbiology” and “Ecology”.

The data from the survey for the qualities of the e-learning shows, that 67% of the inquired students prefer combined learning. This means that they accept the e-learning not as a new model, but as an opportunity for improving and to overcome of the shortcomings of the traditional forms of learning. The fact that 24,5% of the students, most of them from the third age group, with more social experience and partly occupied, prefer the e-learning, confirms the standpoint about the meaning of the new educational technologies for increasing the equal social possibilities for education and qualification during the entire life.

The aim of the investigation was: 1. to evaluate how the electronic courses influence on the effectiveness of student’s

self-preparation and are they improve the quality of obtained knowledge’s; 2. to estimate whether educational content meets the requirements for accessibility,

usefulness, applicability of the proposed information and whether it is appropriate and understandable for the students;

3. to discover the connections between student’s skills in the field of information technologies and e-training in the specific subjects;

4. to analyze the opinion of students about the importance of e-learning form of education and their preferences to the way of acquiring new knowledge’s as well as their self-motivation for learning through electronic tests.

5. the level of student’s motivation is done by indirect indicators like interest, usefulness and necessity of e-learning and their perception for difficulty.

15%

75%

5% 6,25%

78,13%

15,63%

33,33%

66,67%

00%

10%

20%

30%

40%

50%

60%

70%

80%

first second third

neutral

very much

absolutly yes

Figure 4.The effectiveness of the developed electronic material for improving

the quality of self-preparation


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5%

0%0%

35%

0

8,33%

30%

18,75%

8,33%

15%

37,50%

16,67%15%

25%25%

0%

5%

10%

15%

20%

25%

30%

35%

40%

absolutly

no

not neutral very

much

absolutly

yes

f irst

second

third

Figure 5. Preferences of the students for e-learning.

The diagram from the investigation shows that during these years students change

their opinions and preferences about the e-learning (Figure 5). Most of the investigated students (60, 94%) have very good skills with computer technologies that support their prosperity in other educational courses and self-preparation in a virtual environment. Only 9% haven’t the necessary skills to work with computers.

About half of students evaluated the electronic form of training as a very interesting and useful (Figure 6). This fact is confirmed by the results for the practical relevance of content and form of training. This is an indirect indicator that speaks to increased motivation for learning. Only 37% of students find that teaching content is easy for assimilation.

The development of content in different disciplines is characterized by modules, multiple and varied use, interactivity, flexibility about learning strategies and take into account of student’s individual skills, time and place of usage and opportunity for development.

0 0 1,56%0

17,79%

7,81%

48,44%50%

15,63%

26,66%

0

0,1

0,2

0,3

0,4

0,5

absolutly

no

neutral absolutly

yes

interesting

practical

Figure 6. Assessment of interest and usefulness of е-learning


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The advantages of assessing the preparation of students by electronic tests are that: • they are automated; • individualized; • with repeated use; • easy processing of results; • opportunity for self-evaluation; • data retention and production of portfolio performance of students. According to the database 17 % of the students under investigation access as very well

the possibilities to use the electronic tests; 34 % - responded as absolute. That means that half of the inquired students appreciated the advantages, objectiveness and impartiality of evaluating their knowledge’s by electronic tests.

4. Conclusion The analysis of the results and the database of our investigation enable us to make the following conclusions:

• there are increase interest and preferences of the students from specialty “Food Technology” to the introduction e-learning in the main compulsory disciplines;

• practicalness, usefulness and interesting way of presentation the content are the main reasons for the increasing the motivation and the interest of the students;

• increasing the preferences to the educational materials, published on the web-page, has been mentioned, as well as the rising the level of self-preparation of the students;

• students reported that electronic tests overcome a large part of the effects of subjectivism in the evaluation of their knowledge’s;

• the development of educational information in accordance to the pedagogical criteria and indicators for quality, facilitating the adoption by students and increased their activity.

REFERENCES Branzburg, Jeffrey, (Aug 15, 2005), How To: Use the Moodle Course Management System,

http://www.techlearning.com/story/sho wArticle.jhtml?articleID=168600961. Furtunova, 2009 – За модернезиране на висшето образование, Trakia Journal of Sciences, Vol. 7, Suppl. 2,

pp i -ix, 2009. Margarita Pehlivanova, Zlatoeli Ducheva Quality of e-learning in Technical Colleage - Yambol , Bulgaria,

Technikal College – Yambol, Fourh International Bulgarian - Greek Scientific Conference, COMPUTER SCIENCE’2008, 1-6.

Nedeva V. The Possibilities Of E-Learning, Based On Moodle Software Platform, Trakia Journal of Sciences, Vol. 3, No. 7, 2005, 12-19.

Dynamics in the meaning negotiation: can online participation and reification be correlated in informal settings?


PhD student in e-Learning & Knowledge Management

University of Macerata (Italy) E-mail: [email protected]

Abstract According to Wenger’s theory of Communities of Practice, the learning process is a fruit of complex dynamics that involves participation and reification processes, which are dual and essential for the meaning negotiation. So, given that both the processes are complementary and each cannot exclude the other, through the use of ICT toolset within a virtual learning environment, it is possible to explore the dynamics of the respective processes in order to trace and individuate eventual correlation between them. Owing to the intangible nature of informal learning, a part of reification and participation phenomena will be untraceable, because they can happen also outside the e-learning platform, but, inviting e-learners to use a common forum within the VLE, it is possible to have a great part of traceable data about meaning negotiation. This paper deals with a sample of teachers invited to create individually some multimedia artifacts in a free context, using Moodle™ environment as common communicative preferred system. Through the use of an Sociomatrix Finder software, it was possible to extrapolate the sociometric matrix of the teachers’ social reticle in order to esteem the individual participation level; besides, an independent judge assessed all artifacts giving a vote to each reification. Comparing participative and reificative data it is possible to verify the existence of a correlations. The experience was repeated with some of teachers’ students at the same conditions. Keywords: informal learning, SNA, participation, reification

1. Learning as social practice and the role of educator in creating the conditions to grant its existence and development This paper assumes the Wenger’s Community of Practice theory (1998) as reference according to which learning is conceived as a social activity that stands in practice of social exchanges and in particular in the fusion between participative and reificative processes among people. That fusion takes the name of meaning negotiation. Owing to the complex nature of learning and the empirical evidences of the importance of informal learning within individual and social learning processes, it is necessary for educators to stimulate learners in participating and producing something tangible that could be representative of meaning negotiation’s dynamics.


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The nature of informal learning processes, which is spontaneous, natural and free (Cross, 2007) and the non-traditional places in which it happens (usually outside schools, universities and other institutional places: see Lave, & Wenger, 1991), it is very difficult for an educator to engage his/her students in informal activities, for many reasons: first, can happen inside school’s boundaries, the major part of it is probable activated by contacts outside school; second, assigning a precise task to learners means to impose a precise operative strategy which is in total contradiction with the informal nature of the processes that the educator wants to activate; third, if the educator wants to leave free his students, he has the necessity to evaluate their activities, but, monitoring them, he in practice would contradict the informal nature of the context in which informal learning should happen (Piave, 2008).

2. Relationship between Participation and Reification processes Wenger highlights how participative process represents a sort of reciprocal acknowledgement among learners (but it can imply also a level of common engagement among people, within the community of practice): it means that a mere measure of participation level can be insignificant for educators who want to evaluate informal learning. In practice, everyone can be involved at an high level without producing nothing or can be involved a little but producing many contributions to overall activity. Participation itself is not a measure of informal learning. In the same way, reification process, taken alone, is not a measure of informal learning, because it represents only a part of the whole production of an individual/community, but it does not communicate us anything about the way in which people were being led to that point of production, and makes difficult to individuate the individual contribution to the communitarian whole.

When participation and reification determine a meaning negotiation, they produce informal learning: they are a duality and are complementary. Owing to the evanescent nature of meaning negotiation, it is impossible to have a precise measure of informal learning, but it could be possible to have an esteem, taking in count of the complementary nature of both the processes and the possible correlation among them. The concept of complementarity is not considered here in mathematical terms, but as an ideal approach, in which in every single production of informal learning, there has to be both the participation and the reification, even if a part of them could result invisible for the observer. It implies that participation and reification can be correlated positively when informal learning happens: in other terms, it is probably that when the participation level is high and the reification level is also high, there could be a great informal learning production; besides, it implies also the contrary. More difficult is to investigate the correlation when a process is more present than the other and a possible process of estimation could be wrong. But, in general we could assume that a low level of reification (with an high level of participation) can be representative of a scarce (or invisible) production of informal learning. When, instead, the reificative evidences are strong while the participative level is scarce, it is difficult to make an esteem, because people can produce something significant and tangible both in the cases of scarce presence and of high involvement.


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This paper deals with the possibility of verifying a correlation between participation and reification levels in informal settings which corresponds to a proof of effective learning activity. In order to do this, the ICT toolset was implemented within a VLE (that is MoodleTM), in which people were called to collaborate in producing a personal artefact about a theme of own interest, giving help to own colleagues in difficulty. The individual task was very simple, without a precise structure and granted the possibility to have a specific proof of reification not only through the common forum’s posts but also through the evaluation of personal production.

3. The sample and the results The sample consists of 27 teachers, chosen from a population of 127, who showed enough competence in the use of some web 2 applications1. The sample was divided into two groups: A group, which represented the traditional group of peers involved in a structured task under the monitoring activity of a tutor; B group which – instead - operated in informal context, without the supervision of a tutor and without precise instruction about the tools and the process of production. Both the groups were engaged in individual task consistent in the production of a multimedia artefact about a specific discipline. The activities made by both the groups were recorded online by VLE toolset and then analyzed under two different viewpoints:

- in the social network analysis (SNA) perspective, in order to obtain precise data about participation’s levels;

- by an independent judge in order to obtain a vote about personal final production (with a number between 0 and 10), according to a fixed evaluation rubric (Arter & McTighe, 2001; Mertler, 2001)

Given that our hypothesis is about the informal context, B group represents our reference in this study. B group was observed in four distinct periods and the table below synthesizes the results with help of SNA’s parameters (table 1).

The sociometric matrix was calculated by Sociomatrix Finder software, on the basis of precise conventions applied to the tree-structure of VLE’s internal forum.

Sociometric status represents the sum of in-degree and out-degree parameters and expresses the role that each member had within the group (Knoke & Yang, 2008). We adopted that convention according to which it is necessary firstly to verify the presence of a roles’ distribution in order to understand the nature of the observed group. The tutor’s data are ignored because he was not influent on the whole process (the fact is demonstrated by the presence of a scarce variance of sociometric status for all the other members, who are allocated substantially on the same level).

1 This paper regards a part of a bigger experience which involved several Italian teachers in various aspect of formal/informal learning relationship [see more in Piave (2009). Social Network Analysis for e-assessment: reliability of formal and informal social reticles, in Proceedings of ICVL – International Conference on Virtual Learning, Jassy (Romania)], regarding a Master Course titled “La professionalità del docente e del dirigente scolastico”. Please make reference to that work for more clarifications about parameters and mathematic conditions applied here and in the following paragraphs.


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High level of SS for the tutor are justified because in both the groups the tutor opened a thread to present the activity and, according to the convention of Sociomatrix Finder software we used, the first who opens a thread in the forum, is considered as a member who sends a message to all the group.

INFORMAL CONTEXT’S GROUP OF TEACHERS

SOCIOMETRIC STATUS DATA OBSERVED IN FOUR PERIODS

(n=13, without the influence of the tutor)

I II III IV Other data

Node SS(i) SS(i) SS(i) SS(i) SS(i) average Reification

R(i)

Bea 1,46154 0,76923 0 0 0,5576923 10

Nifio 0,38462 0,76923 0,5385 0 0,423076943 9

papillon 0 0,07692 0 0 0,01923077 6

archimede 2,30769 2,15385 1,7692 0 1,557692325 6

morgana 0,15385 1,07692 0 0 0,307692315 5

mortisia 0,23077 0,30769 0 0 0,134615388 0

delfina 0,30769 0,07692 0 0 0,09615385 3

Ribe 1,46154 2,07692 0,1538 0 0,923076915 7

Alice 1 0,61538 0 0 0,40384616 4

Kaka 0,38462 2 0,6923 0 0,769230775 7

Prof 0,07692 0,07692 1,3077 0 0,365384615 3

Milka 0,30769 0,46154 0 0 0,192307695 10

Bros 0 1 1 0 0,5 5

TUTOR 3 3 1,9231 0 1,980769225 //

existing leadership

No No No No

Table 1 In practice, the roles’ distribution is granted by the following mathematic condition:

0,319283 < 1,175824

Otherwise the group is formed by peers without roles’ distinctions. Collected data (see table 1) demonstrated the informal nature of the B group: so it is a

group of peers. Even including the sociometric status of the tutor, data confim the informal nature of the group and consequently the insignificant role of the tutor during the whole activity, according to the informal structure of the task. There is not properly a leader (although the tutor has constantly the highest level of participation in the group). B


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group operated in an intensive way, reaching substantially the same level of participation, with scarce differentiation.

Making reference to the votes attributed by judge about the personal artifacts made by teachers, we can observe more differentiation.

Calculating Pearson’s coefficient between average of SS(i) and R(i) for each member, we obtain:

0,247630411 Data show that SS(i) and R(i) are correlated positively. This measure can be

considered reasonable because of the scarce variance of SS(i) values, so that the average of SS(i) levels seems to be significant and representative of the effective “weight” that each member had during the production in the group. A roles’ distribution would avoid this kind of choice.

4. Searching for further proof of correlation In order to have a further proof of correlation, we repeated a similar experience with some students of the previous teachers. The proposed activity was similar: in fact, it consisted in making a personal multimedia artefact as answer to the previous artefact made by teachers. In this case, each teacher chose five students and engaged them in the activity( with the exception of Flox’s group which has only three members). It were formed seven groups of students. There were 32 subjects in total, only a part of the whole sample which will include all teachers’ students involved in this research.

Students belonging to informal groups, without the control of a tutor and in absence of precise instructions about their task, confirmed sufficiently the data observed in the previous stage of the experience. In particular, all students’ groups confirmed that nature of informal group, having no significant roles’ distribution.

In this stage of the experience, we called teachers to evaluate the general learning activity as result of their students’esperience through an interrogation in classroom. Then we also asked independent judge to evaluate only the individual production. So here R(i) represents the vote given by the judge to the reification process (according to the same evaluation rubric used in the previous stage), while J(i) represent the measure, made by teachers, of the whole students’ learning experience.

We found that (see table 2), with the exception of a one case, in all groups there is a correlation between R(i) and J(i): in other terms, a good reification process leads to a good level of learning, evaluable by teachers. Besides:

– in some cases the correlation between SS(i) and R(i) was inverse (Mortisia and Nigipa), but in the major part of them was direct (all the other groups);

– in some cases the correlation between SS(i) and J(i) was inverse or absent (Mortisia, Papillon, Kikka), while in the major part of them was direct;

Calculating the average among correlation results, we obtained that R(i) e J(i) are in

general correlated and that R(i) e SS(i) are in general correlated. The same correlation exists in general also between SS(i) and J(i).


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So, it is possible to affirm that a great level of participation (represented by SS) implies in general a good level of reification (represented by R) and, consequently, it leads to a better evaluation of the whole learning activity.

It is obvious that more data are necessary to obtain more significant conclusions.

INFORMAL CONTEXT’S GROUPS OF STUDENTS ANOTHER PROOF OF EXISTING CORRELATION (N=32)

Group of SS(i) average

SS(i) variance

correlation between

SS(i) and R(i)

correlation between SS(i) and external judgement

J(i)

correlation between R(i) and

external judgement J(i)

Mortisia 3,8 6,3875 -0,868158887 -0,078081003 0,441261304

Papillon 19,6 31,45625 0,650977182 -0,133909115 0,134839972

Linam 6,5 10,6875 0,166794364 0,886310304 0,01805657

Kikka 7 3,59375 0,153684188 0 0,24469154

Nigipa 2,6 0,3625 -0,890765201 0,355930691 -0,662122192

Stef 5,7 2,54375 0,461103483 0,36802481 0,431331093

Flox 8,666667 2,333333 0,928571429 0,5 0,785714286

No Existing leadership, because SS(i) variance not is = or higher than double SS(i) average

average of p results between SS(i) and R(i)

0,086029508

average of p results between SS(i) and J(i)

0,271182241

average of p results between R(i) and J(i)

0,199110367

Table 2

5. Discussion of findings After the data presented in the previous paragraph, it is necessary to put some questions for a further analysis about the observed processes:

a) why R(i) and SS(i) are not always correlated, and when they are correlated the nature of correlation is weak (p=0,08)?

b) what are the possible reasons of the inverse correlation (p=-0,86 and p=-0,89) happened in some cases between R(i) and SS(i)?


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c) Although R(i) and J(i) represented different kinds of judgement (the former about the multimedia and completeness of the artifact and latter the general evaluation about the interrogation of the author’s artifact), they are correlated. Why?

d) When R(i) and J(i) are not correlated and why?

5.1 About correlation between reification and sociometric status About a) e b) questions, it is the Wenger’s theory itself which can offer a possible explanation: given that participation and reification are dual processes and each of them cannot be representative of the whole meaning negotiation activity, it implies that reification includes a part of participation activity and vice versa; so, in presence of significant meaning negotiation activity, the correlation between SS(i) and R(i) is probable, but it is not a certainty, because even if SS(i) is high or vice versa, the other process can also be not productive owing to the quality of collaboration and the exchanges within the group/community. When SS(i) or R(i) taken alone are high, it is not equivalent to affirm the existence and the effectiveness of underlying meaning negotiation activity. In some cases SS(i) and R(i) can be inversely correlated for the same reason: an high level of participation does not imply, taken alone, that the learner will produce good reification. It is also true the inverse observation: a good reification can not imply an high level of participation automatically.

The weakness of the positive correlation, which is recorded in the major part of the cases, is justified by the evanescent nature of the dual processes: we cannot observe all the processes within the community, because part of them are intangible and can even happen outside the VLE itself among learners; so it is possible to affirm that, in general, the role in social reticle and the reification are correlated, with some exceptions.

About correlation between reification and the external general evaluation About the c) and d) questions it is necessary to specify the nature of both the parameters. R(i) is the subjective judgement about several aspects of the multimedia artifacts made by teachers/students, according to a specific evaluation rubric that was known for all the authors before the beginning of the activity. J(i) instead represents a sort of complete and general evaluation of the results deriving from the activity: so, it includes the evaluation about informal production and exchanges among learners, but it is calibrated on the visible and complex results that each leaner can show through an interrogation about the chosen theme. R(i) and J(i) are not the same thing, but J(i), in a certain sense, includes R(i). So, it is obvious that R(i) and J(i) can be correlated in probabilistic terms.

In some cases this correlation does not happen: in other terms, what happens between R(i) and J(i) is a direct consequence of the relationship between SS(i) and R(i). Although an high level of participation can imply an higher level of R(i), it can also be wrong when something within the meaning negotiation process goes wrong; so, even between R(i) and J(i) is highly probable a correlation, but it can happen that the reification (which is not alone a proof of the negotiation effectiveness) is not representative of a good learning.

6. Conclusion The paper presented a brief analysis of the behaviour of two different informal groups, working in a free way without the supervision of a tutor, in order to investigate the possible correlation between participation and reification processes.


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The informal contexts and the analysis of both the processes involved in meaning negotiation confirmed that, in general, participation and reification are correlated positively. Besides, in general, the more a learner participates online, better he will produces appreciated reifications and, in probabilistic terms, in presence of high levels of participation (and therefore of reification) his/her total learning (that is formal and informal learning, at the end of the experience) will be of better quality than in other conditions of participation or reification. The Wenger’s theory of community of practice seem to be confirmed by this empirical study, but it is necessary to make more researches about this theme, with an higher number of subjects and monitoring the finality of learning through the introduction of an e-portfolio, in order to have more data correlated with the development of reification processes in the time.

The paper opens possible scenarios for further researches in formal settings and in the knowledge of meaning negotiation dynamics’ related to various kind of assigned tasks (for example collective or individual task) and time spent in the productions (for example: will the informal group’ structure remain the same for a longer period of observation or not?).

7. Acknowledgments The author thanks Prof. Giuseppe Refrigeri, Full Professor of Didactics in University of Cassino (Italy) for his disposability in putting him in condition to operate within the Master Course “La Professionalità del docente e del dirigente” from which illustrated data were collected. The author also thanks all teachers of Master Course (and their students), as members of the samples, who gave their availability for this study.

REFERENCES All trademarks belong to their legitimate owners. Arter, J. & McTighe, J. (2001). Scoring rubrics in the classroom: Using performance criteria for assessing and

improving student performance. Thousand Oaks, CA: Corwin Press/Sage Publications. Cross J. (2007). Informal learning, San Francisco: CA, Pfeiffer Knoke D., Yang S. (2008), Social Network Analysis, Thousand Oaks: CA, Sage Publications Lave J., Wenger E. (1991). Situated Learning. Legitimate peripheral participation, Press Syndicate of the

University of Cambridge Mertler, C.A. (2001). Designing Scoring Rubrics for Your Classroom Practical Assessment Research and

Evaluation 2(2). Retrieved from http://PAREonline.net/getvn.asp?v=7&n=25. Piave (2009). Social Network Analysis for e-assessment: reliability of formal and informal social reticles, in

Proceedings of ICVL – International Conference on Virtual Learning, Jassy (Romania) Piave N.A. (2008). Educare all'apprendimento informale online: la scuola 2.0 fra paradosso e opportunità, in

iGel - Il giornale dell'e-Learning, II, n.5, Ancona, Wbt srl, on line at http://www.wbt.it/index.php?pagina=669 (verified on 09.08.09)

Piave N.A. (2007), (ed.). La classe virtuale, Manduria (TA), Barbieri Wenger E. (1998). Communities of Practice. Learning, Meaning, Identità. Cambridge University Press Sociomatrix Finder is a software in the property of Nicolò A. Piave, released under Creative Commons License.

Section

SOFTWARE SOLUTIONS

Software Solutions (SOFT): • New software environments for education & training

• Software and management for education

• Virtual Reality Applications in Web-based Education

• Computer Graphics, Web, VR/AR and mixed-based applications for

education & training, business, medicine, industry and other

sciences




• Software Computing in Virtual Reality and Artificial Intelligence

• Avatars and Intelligent Agents

Open learning resources as an opportunity for the teachers of the Net Generation

Fulantelli Giovanni, Gentile Manuel, Taibi Davide, Allegra Mario

Italian National Research Council,

Institute for Educational Technology Via Ugo La Malfa 153, Palermo, ITALY

giovanni.fulantelli, manuel.gentile, davide.taibi, [email protected]

Abstract In this paper we illustrate a solution to reduce the gap between teachers and the Net Generation. In the framework of an European funded project called Tenegen, based on a former project called Sloop, we encourage teachers to produce, share, comment, tag and modify Open Learning Objects, as their students are used to do on the Net with different types of information. In such a way, teachers are involved in network social activities, use Web 2.0 tools, and their learning objects are the examples of application of collective intelligence. To sum up, teachers emulate their students’ learning behavior. Keywords: Open Learning Objects, Open Educational Resource, Net Generation, Connectivism, Web 2.0

1 Introduction During the last 5 years, the number of repositories of digital educational contents has rapidly increased, as a consequence of the diffusion of e-learning methodologies and solutions in schools. Despite this, the number of teachers using, producing and sharing digital contents is still low. The adoption of the Learning Object (LO) paradigm as the main model for the content in most of the Learning Management Systems set up in schools has not facilitated the use of digital contents by teachers. Actually, the technical standards behind the LO model (e.g. SCORM) represents one of the main obstacles to the adoption of the LO model by teachers, together with the initial lack of software packages that could simplify the creation of SCORM compliant LOs. Consequently, for many years the production of educational materials for e-learning has been demanded to the digital content providers and developers, usually cooperating with traditional editors, thus compromising one of the principles of e-learning 2.0: the possibility for a community of teachers to produce and share their own materials.

In order to support teachers in the production and sharing of their educational material, in 2005 we started a European funded project called SLOOP: Sharing Learning Object in an Open Perspective (Masseroni and Ravotto 2005). Two of the main results of the project were an extension of the Learning Object model, called OpenLO, and the concept of a new category of software tools called Learning Object Management Systems


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(LOMS), which extends the typical functionalities of a Learning Object Repository, providing users with tools to collaboratively produce learning resources. In Sloop, we developed a first example of LOMS, called FreeLOms; by hiding technical aspects and guaranteeing compatibility with standards in a transparent way, FreeLOms allows teachers to concentrate on the content to be developed.

During the 2 years of the project, some important concepts emerged in the Educational Technologies field: a different use and interpretation of the Web, called the Web 2.0 paradigm (O’Reilly, 2005); the existence of a new generation of students, referred to as Digital Natives (Prensky, 2001) and Generation Y (McCrindle,2006), or generally defined as Net Generation; the need and opportunity of Open Educational Resource (OER) models (Atkins et al., 2007; OECD, 2007; OLCOS, 2007). Some of these concepts had been defined some years earlier, but during the last 3-4 years they have become argument of discussion in the schools.

The Sloop project coped with most of these concepts: the OpenLO model as an application of the more general OER paradigm; the social ties amongst teachers as fundamental elements to elaborate educational materials in a cooperative way; the produced LOs as the result of collective intelligence. The involvement of the Net Generation, even if not part of the project activities, was one of the future activities that emerged during the project: “A future development - SLOOP 2.0 and freeLOms 2.0 – could directly involve young people, the digital natives [....] a student instead of tagging only photos and videos and downloading music would tag didactic resources adding her/his personal tag to those of the teacher; that a student would access resources not because of the teacher’s instructions but because other students has tagged them as useful.” (Ravotto, Fulantelli, 2007).

In 2008 we have had the opportunity to cooperate to a new European funded project called Tenegen: Connect the TEachers to reach and teach the NEt GENeration, explicitly aimed at reducing the gap between teachers and the Net Generation. The OpenLO concept is being transferred to the Tenegen project with the objective to encourage teachers to participate in the production of a shared resource, which will be commented, tagged and modified by other users of the Net. In other words, teachers will behave as the Net Generation usually does. Specifically to the Tenegen project, the shared resources will be Open Learning Objects, and FreeLOms will be part of the platform that will support the social network learning activities.

2 The Sloop project and its main results The 2-year Sloop project, run from September 2005 till September 2007, involved 10 partners from 5 countries (Italy, Ireland, Romania, Slovenia, Spain), and was promoted and coordinated by ITSOS Marie Curie, Italy. Following the successful stories of the free software/opensource movement, the main objective of the project was the development of free educational resources accessible from everyone and open to external contributions.

The Learning Object model was adopted as the paradigm for the digital contents to be produced by teachers. Even though there were several reasons to follow the wiki-way solution, specific considerations convinced us to adopt a more formal model:


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– the standards behind the Learning Object model guarantee accessibility, reusability and interoperability that are central concepts in the SLOOP project.

– an approach based on LOs does not limit the digital formats used to develop content, this is different to Wiki where there are some limitations; a solution which does not preclude the possibility to transform any digital content into didactic material fits better with the fundamental ideas of the SLOOP project, i.e. the sharing of digital content which exists already on thousands of computers all over the world. For example, a power-point presentation need a re-engineering work to be adapted to the wiki environment, while the same presentation can easily fit into the LO model and maintain its main characteristics.

– the methods used to search for didactic resources based on the wiki model, up until recently, are usually based on free text search. This places considerable limitations on the identification of didactic resources made up of more wiki pages with hypertextual links. The LO model overcomes this problem by an ad hoc standard which allows all the resources to be described in a formal way, such as the IEEE LOM (IEEE, 2002);

– finally compliance with the SCORM standard (ADL 2004), which is widespread in the LO world, is mandatory in Italy for organisations supplying distance learning courses at a university level.

Nevertheless, we also took into account the main criticisms that had put in doubt the pedagogical value of LOs: the difficulty to practically guarantee re-usability and the technical difficulties connected to standards in the production of LOs. In order to overcome these limitations, we have defined the Open Learning Object model (OpenLO): Starting from Wiley’s definition of learning object (Wiley 2000) we define open learning object as “any open digital resource that can be reused to support learning”. In this definition the term open indicates open content, namely content developed in open format (e.g. Open Document) or content in closed format whose source files are also available (e.g. Adobe Flash). In addition it refers to open licenses (e.g. Creative Commons) thus allowing users to freely modify and reuse learning objects. (Fulantelli et al., 2007)

Our vision of reusability is not simply based on combining LOs but goes beyond this towards a pedagogical concept of reusability in which a LO can evolve to meet specific educational requirements. The OpenLO model allows users to edit LOs created by different authors, and customize the LOs according to their own pedagogical needs; in addition, communities of educational professionals can work on the same LO and contribute to its collaborative evolution at content level. Finally, the replication of this process of adaptation of LOs at content level over time is a mechanism that can provide pedagogical sustainability of the LOs.

In the implementation of the OpenLO model, and in the definition of educational methodologies based on this model, it is relevant to focus on three main aspects: 1) changing the life cycle of Learning Objects and consequently the methodologies for producing these resources; 2) assigning a dynamic role to metadata, which should evolve in parallel with the life of the learning object. 3) moving from current Learning Object Repositories (LOR) to innovative Learning Object Management Systems (LOMS). To the aim of this paper, we focus on the third aspect. In-depth discussions on the other aspects can be found in (Fulantelli et al., 2008).


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According to the report on Free and Open Source Software (FOSS) for Open Educational Resources (VV.AA., 2006), the traditional tools to manage the elaboration of LOs can be divided into: authoring tools, tools to implement learning technology standards, learning object repositories, learning management systems, collaborative environments for sharing LOs. A teacher wishing to develop a LO needs to have all the skills required for using different tools to handle the LOs in the different phases. This represents a major obstacle for teachers in adopting the LO paradigm. In addition, these tools are not suitable for managing the evolution of LOs and controlling the dynamics introduced by the new OpenLO model.

For this reason it is essential to design a new kind of environment which can manage LOs throughout their entire lifecycle. This kind of platform, that we call Learning Object Management System (Gentile et al., 2006), allows teachers and experts to create a network where they can participate collaboratively in the processes of design, development, sharing, reusing and evaluation of open learning resources through a typical Web 2.0 approach. In our vision, a LOMS is a Rich Internet Application; at the same time a LOMS can be seen as a set of services accessible through the Web from different applications. The goal is to make it easy to use the services provided by a LOMS, and not to impose specific software, but rather to propose a philosophy that makes the creation, management and reuse of digital educational resources efficient and effective.

In the framework of the Sloop project, we have developed a specific LOMS, called FreeLOms. In order to manage learning objects created in a variety of digital formats and provide users with tools to support collaborative activities, FreeLOms has been designed by means of an abstract model of the contents which is able to manage different formats of learning materials, thus facilitating sharing, retrieving and reusing of LOs. FreeLOms includes functionalities for:

− uploading digital educational resources into a repository (LOs in SCORM terminology: Assets, SCOs or Content Aggregations);

− editing LO IEEE Metadata (IEEE 2002); editing of metadata can occur at any stage of the LO lifecycle, and not only when it is uploaded into the platform;

− searching LOs shared by the users; specialized and personalized searches can also be defined (these features meet the needs of authors who usually apply the same search criteria, e.g. to search some specific topics for their discipline);

− managing existing LOs in SCORM vision, by allowing users to edit Assets, SCOs and Content Aggregations (CAs);

− creating Content Aggregations by using the resources available in the repository; − managing the changes made to the didactic contents through versioning and

differencing, both at metadata and content levels (more precisely, these features will make it possible to handle the contributions supplied by each user on the same LO, thus guaranteeing the “collaborative evolution” of LOs);

− transforming digital contents developed in technical formats unsuitable for learning platforms, into contents compliant with the SCORM standards; this functions is limited to some formats

− communicating asynchronously and/or synchronously with other users in order to support group processes; this reflects the typical functionalities available in a Computer


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Supported Collaborative Work system, providing an efficient environment for the collaborative management of didactic resources.

The Sloop project and the FreeLOms platform have been successfully evaluated both by the community of teachers grown around the project, and from the official evaluator of the EC Agency (grade: 9/10).

3 The Tenegen project: main objectives Tenegen is a 2 year project, involving 11 partners from five countries (Hungary,

Germany, Italy, Turkey, United Kingdom), promoted and coordinated by Prompt-G Educational Centre for Informatics, Hungary.

The project will valorize the results of two earlier LdV projects: SLOOP and NETIS (http://www.ittk.hu/netis/index.html). NETIS provides the philosophical, sociological, and pedagogical basis to support new paradigms of teaching and learning in the Information Society. The aim of Tenegen project is to establish an European environment of connectivism (Siemens, 2005) for VET teachers and trainers, to show the significant advantages of being connected to the Net generation instead of simply delivering knowledge through virtual classrooms and Learning Management Systems (www.tenegen.eu).

The main objectives of the project are: − to elaborate a pedagogical model of network learning and connectivism; − to develop an online repository of Open Learning Objects; − to develop a TENEGEN network learning environment based on open source LMS; − to elaborate and implement five training modules in three languages (HU, EN, TR); − to establish pilot training courses for teachers and trainers; − to validate and verify the results in VET schools; − to disseminate the results all over Europe. The project intends to deliver the new paradigm of network learning to the teachers

and trainers in the vocational education, to help them “to reach and teach the Net Generation”.

4 The OpenLO model and FreeLOMS in the Tenegen context One of the most interesting challenges we have to face in the Tenegen project is how to train teachers from traditional schools on new pedagogies for the Net Generation, by using a distance course. In fact, we are talking of 3 different educational models to be handled: learning in traditional schools, that have their roots in the first decades of the XX century, mainly teacher-driven learning; informal and self-directed learning, typical of young people who were born almost 1 century after traditional schools; and distance learning, which is not organized and managed as a school course, either as a strongly informal and social space where learning is self-organized and directly controlled by the learners.

Accordingly, the original challenge becomes: how to make transitions amongst the 3 models smooth. The answer is through the distance course that will be organized in


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Tenegen. Most of the attempts worldwide to reduce the gap between teachers and the Net Generation focus on the learning needs and attitudes of young students, and tend to train teachers on the pedagogical models that best suit young students and on the ICT tools used by them.

This is an extremely important part of the whole process, and it is one of the main goals of the Tenegen project as well. However, very few experiences focus on the learning needs of the teachers, which are as important as the teaching skills targeted by most of the research projects. How can we support teachers to speak the same language - in Prensky’s vision (Prensky, 2001) - as their students? We could organize a traditional course, maybe in the school lab; or we could invite teachers to join a social network, and try to stimulate learning through dialogue and personal interests. Both these methods will encourage learning and produce some knowledge. But do these methods suit learning needs and attitudes of teachers used to teach in a traditional classroom?

The solution adopted in Tenegen is to introduce VET teachers and trainers to the new pedagogies and tools gradually, through a distance course based on Moodle and FreeLOms, where they can still find their cultural and social references (teachers, educational resources, learning objectives to achieve, learning outcomes to produce, and so on), and at the same time to make them to experience the new pedagogical models, to use the new ICT tools and to establish social ties aimed at developing Open Learning Objects. In such a way, transitions between the different pedagogical models will be smooth enough to allow teachers to get closer to the Net Generation learning behaviors.

Specifically to the transfer of the FreeLOms platform, the new version reviewed according to the Tenegen needs, will be called the TenLOs system. As mentioned before, the TenLOs system aims at two distinct aspect: providing the Tenegen partners and the teachers involved in the project with a respository of digital learning resources; secondly, providing teachers with a tool that can allow them to cooperatively develop learning objects. The second aspect represents one of the strategic aims of the Tenegen project, consisting in the fostering of significant collaboration processes between the teachers through the Net. Online social networking mechanisms amongst students are usual: quite often, students activate informal learning processes and develop knowledge implicitly through these networks. By using the TenLOs system to cooperatively develop and share open learning objects, we provide teachers and trainers in Tenegen with an example of net-tool that can be used to develop knowledge (as digital learning resources) in a network. In this case, knowledge is produced in an explicit way.

5 Conclusions Last June, Italian students at their final year of high school were asked to write an essay concerning Social Networks, Internet and New Media, based on some excerpts from different authors, including Castells and De Kerckhove. This topic received a very positive feedback by the students. However, this raised an interesting debate in Italy, around the question if Italian teachers, and in general teachers in traditional schools worldwide, can properly evaluate and assess the thoughts expressed by the students. The debate reflects a real problem in the traditional educational system: teacher competences need to be renewed in order to reduce the gap between them and their students.


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Teacher education and training is at the top of the European policy agenda (European Commission, 2008), and similar interest can be found worldwide. Nevertheless, each initiative aimed at improving teacher competences should take into account teacher resistance to change: informal and non-formal learning; self-directed learning; collective intelligence are examples of concepts which are popular in the web 2.0 conception, typical of the Net Generation, but hardly accepted by teachers working in traditional contexts.

In this paper we have illustrated a solution to reduce the gap between teachers and their students, In the framework of an European funded project called Tenegen, based on a former project called Sloop, we encourage teachers to produce, share, comment, tag and modify Open Learning Objects, as their students are used to do on the Net with different types of information. In such a way, teachers are involved in network social activities, use Web 2.0 tools, and their learning objects are the examples of application of collective intelligence. To sum up, teachers emulate their students’ learning behaviour.

REFERENCES ADL - Advanced Distributed Learning (2006), SCORM 2004 3rd Edition, Content Aggregation Model

(CAM), Available at ADLNet.gov, November, 2006 Atkins, D. E., Brown, J. S. & Hammond, A. L. (2007). A Review of the Open Educational Resources (OER)

Movement: Achievements, Challenges, and New Opportunities. (online): OERderves. Retrieved July 1, 2009 from http://www.oerderves.org/wp-content/uploads/2007/03/a-review-of-the-open-educationalresources-o

Cardinaels, K., Meire, M. and Duval, E. (2005): Automating Metadata Generation: the Simple Indexing Interface, In Proceedings of ACM 1-59593-046-9/05/0005 International World Wide Web Conference Committee (WWW 2005), Chiba, Japan.

Collis, B. and Strijker, A. (2004) Technology and Human Issues in Reusing Learning Objects, Journal of Interactive Media in Education, 4. Special Issue on the Educational Semantic Web. ISSN:1365-893X [www-jime.open.ac.uk/2004/4]

European Commission (2008). Draft 2008 joint progress report of the Council and the Commission on the implementation of the 'Education & Training 2010' work programme "Delivering lifelong learning for knowledge, creativity and innovation" - Adoption

Fulantelli, G., Gentile, M., Taibi, D. and Allegra, M. (2007): The Open Learning Object model for the effective reuse of digital educational resources. In Proceedings of the Openlearn 2007: Researching open content in education, Milton Keynes, UK.

Fulantelli, G., Gentile, M., Taibi, D., and Allegra, M. (2008). The Open Learning Object model to promote Open Educational Resources. Journal of Interactive Media in Education. http://jime.open.ac.uk/2008/09/

Gentile, M., Taibi, D., Allegra, M. and Fulantelli, G. (2006) A collaborative “open Learning Objects” managements system. WSEAS Transactions on Advances in Engineering Education 6, 3, ISSN:1790-1979, 586-592.

Han, P., Kortemeyer, G., Krämer, B. J., von Prümmer, C. (2008) Exposure and support of latent social networks among learning object repository users. Journal of the Universal Computer Science 14,10, 1717-1738.

IEEE 2002, IEEE Learning Technology Standards Committee : IEEE Standard for Learning Object Metadata 1484.12.1.

Masseroni, M. and Ravotto, P. (2005): SLOOP: un progetto europeo per un archivio condiviso di Free Learning Object. In Proceedings of the EXPO eLearning Conference, Ferrara.

McCrindle, M. (2006). New Generations at Work: Attracting, Recruiting, Retraining & TrainingGeneration Y: McCrindle Research


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O’Reilly, T. (2005) What Is Web 2.0: Design Patterns and Business Models for the Next Generation of Software. http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html

Prensky, M. (2001). Digital Natives, Digital Immigrants. On the Horizon, 9(5). OECD - Organisation for Economic Co-operation and Development, Centre for Educational Research and

Innovation (2007). Giving Knowledge for Free: The Emergence of Open Educational Resources, SourceOECD Education & Skills, Vol. 2007, No. 3, May 2007

OLCOS (2007). Open Educational Practices and Resources: OLCOS Roadmap 2012. (online): OERderves. Retrieved Oct 30, 2007 from http://www.olcos.org/cms/upload/docs/olcos_roadmap.pdf

Ravotto P., Fulantelli G., (2007). The Sloop idea: sharing free/open learning objects. In Sloop – Sharing Learning Objects in an Open Perspective, 2007.

Siemens, G. (2005). Connectivism: A Learning Theory for the Digital Age, Retrieved Sept 15, 2008 from http://www.elearnspace.org/Articles/connectivism.htm

VV.AA. (2006). Report of the discussion on Free and Open Source Software (FOSS) for Open Educational Resources (2006). Retrieved Jan. 2008 from: http://oerwiki.iiepunesco.org/images/ 1/17/FOSS_for_OER_final_report.pdf

Wiley, D.A. (2000): Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. The instructional use of learning objects, D. A. Wiley Editor.

Applying Agent-Based Technology to University Knowledge Management

Mihaela Oprea1, Elia Petre2

(1) University Petroleum-Gas of Ploiesti, Department of Informatics

Bd. Bucuresti Nr. 39, Ploiesti, RO-100680, ROMANIA E-mail: [email protected]

(2) University Petroleum-Gas of Ploiesti, Department of Informatics Bd. Bucuresti Nr. 39, Ploiesti, RO-100680, ROMANIA


Abstract A university knowledge management system is composed by three components: the educational management, the research management, and the institutional management. The high complexity of the whole university knowledge management system, that is also a distributed system, can be handled by using a multi-agent system. Through communication and cooperation the agents are solving different problems specific to knowledge management in a real or virtual university. The agents are associated to the humans involved in all processes (e.g. educational, research, institutional) that are running in a university, such as professors, assistants, students, researchers, technical staff, management staff, administrative staff etc. The paper presents an university knowledge management system based on agents technology. Two case studies are described in detail, one for the university research management, and the other for the educational management. The implementation of the agent-based system was done in ZEUS, a toolkit for multi-agent systems development.

Keywords: University knowledge management, Multi-agent systems

1 Introduction Knowledge management (KM) became an important research area in the last decade, with applications in most of the domains (e.g. industrial, governmental, medical, economical, educational) [1], [7], [9]. It deals with knowledge and collaboration management in a specific organization. The purpose of KM is the management of activities related to knowledge creation, preservation, distribution and also, the management of the collaboration between people [8]. A strategic domain that uses and provides knowledge is the educational domain [3], [4]. In this paper, we focus on the higher education domain, and we propose an agent-based model for the university knowledge management system. Other agent-based solutions that can be adopted for the management of some university activities are presented in [2] and [6].

The university knowledge management system, that is a distributed system, can be modeled as a multi-agent system, associating agents to all humans involved in the


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processes that run in the university (educational, research, institutional etc). Thus, we have personal agents for professors, assistants, students, researchers, technical staff, management staff, administrative staff. The paper presents an university knowledge management system based on agents technology. The implementation of the agent-based system was done in ZEUS, a toolkit for multi-agent systems development. Two case studies are described in detail, one for the university research management, and the other for the educational management.

2 University knowledge management Knowledge management provides a systematic and holistic approach for the improvement of knowledge handling at all levels of an organization in order to fulfill the organization’s business goal. In the particular case of a university, knowledge management refers to the three main activities: teaching, research, and university (institutional) management. Figure 1 presents the organizational structure of a university. The basic organizational units of a university are the department and the faculty.

UNIVERSITY MANAGEMENT

FACULTIES

DEPARTMENTS

Figure 1. The organizational structure of a university

Usually, a university is composed by a number of faculties, and some independent departments (e.g. administrative, distance learning, pedagogical training, research), and has students and employees (teaching / research staff, technical / administrative staff etc). A faculty is composed by a number of departments, and a number of specializations for students (undergraduate, postgraduate, master, PhD), has students enrolled in different study programmes, and has a secretariat and a management team. Each department has teaching, research and technical staff, plus a secretariat, and a head of department, and is directly involved in the teaching and research activities. Each administrative department (e.g. accounting, personnel) has administrative staff (e.g. accountants, personnel staff), and is directly involved only in the institutional processes.

The management of a university is provided by a university management team that is composed by a rector, a number of vice-rectors, and a scientific secretary. Each faculty has a faculty management team composed by a dean, a number of vice-deans and a scientific secretary.


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Figure 2 shows the modular structure of the University KM system.

UNIVERSITY Knowledge Management System

UNIVERSITY

MANAGEMENT

INSTITUTIONAL

KNOWLEDGE

MANAGEMENT

RESEARCH

KNOWLEDGE MANAGEMENT

TEACHING

KNOWLEDGE MANAGEMENT

Figure 2. The modular structure of a University KM System

The teaching knowledge management module is dealing with all the didactical activities done in the university (e.g. teaching courses, training in laboratories, student’s examinations, and so on) for different forms of study programmes. Related to the didactical activities there are some auxiliary tasks such as admission exams (in July and September), student’s enrollment (in September), university courses and laboratories scheduling (at the beginning of each semester). The teaching knowledge sources are specific to each study programme. Examples of teaching knowledge sources and products are hard copy and electronic courses and laboratories materials, manuals, textbooks, software tools, computer networks.

The research knowledge management module is dealing with all the research activities done in the academic departments or in the independent research departments (research centers, research laboratories). The research activities are done under national and international research projects. Examples of knowledge sources and products are research papers, research reports, Master and PhD theses, computer software, inventions (e.g. new devices).

The institutional knowledge management module is dealing with all the activities done for the good functioning of the university so that its main goal is reached, i.e. a high quality educational system based on training and research, according to the current needs on the national and international employment markets. Some institutional activities are the management of all faculties and departments (i.e. including students, and all university personnel), university budget planning, management of projects for the university development (e.g. university infrastructure development projects). Examples of institutional knowledge sources and products are the university charta, university management quality guide, different university management guides and methodologies, laws and norms.


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3 An agent-based system for university knowledge management Starting from the considerations made in section 2, we have designed the generic architecture of a multi-agent system for university knowledge management, UnivKM, that is shown in Figure 3.

Legenda:

Agent

Faculty MAS

University Management

MAS

Faculty MAS

Department MAS

Department MAS

Figure 3. The generic architecture of the UnivKM multi-agent system

…

…

UnivKM multi-agent system is organized modular and hierarchically, and is

composed by agent-based modules (i.e. multi-agent systems – MAS, of less complexity) corresponding to the university management team, to each faculty and to each department. The agents (i.e. personal agents) are corresponding to students, professors, assistants, researchers, technical staff, administrative staff, and management staff. Each MAS module (university management, faculty and department) has a manager agent of it (corresponding to rector, dean, head of department, chief accountant etc), and the agents


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that collaborates between them and with the manager agent for university specific activities. The system UnivKM can be viewed in different ways depending on the activities that are followed, teaching, research, and institutional. Thus, particular architectures, specific to different applications, can be generated.

4 Case studies We have implemented the agent-based university knowledge management system for two applications of university research management, and educational management. The development of the UnivKM multi-agent system was done in Zeus, a Java-based toolkit for intelligent agents.

4.1 University research management The first application consists in the analysis of the university research activity quantified in the production of articles published in ISI journals, and the participation in national and international research projects. All the required information are collected by agents from databases with data about the research activity done by the teaching and research staff of each academic department. Figure 4 presents the architecture of the multi-agent system UnivKM specific to this first application.

University_resp Agent

Faculty_resp Agent

Mathematics_resp Agent Informatics_resp Agent

Research_Mathematics_resp Agent Research_Informatics_resp Agent

Figure 4. Specific architecture of UnivKM multi-agent system for university research management application


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Each person involved in this application has a personal agent. The involved persons are the persons responsible with research at the university level, at each faculty level, and at each department level. In our case study we have considered the Faculty of Science and Letters from the University Petroleum-Gas of Ploiesti, and two departments from this faculty, Department of Mathematics and Department of Informatics.

The University_resp agent initializes the agents’ communication asking the Faculty_resp agent to provide the faculty research report for a certain academic year (selected from the interface). To achieve this goal, the Faculty_resp agent asks the needed information furthermore to the Mathematics and Informatics departments. The two research responsibles from these departments extract the information from a MySQL database, where all the needed data are stored from the academic year 1990-1991. Once extracted from the database, the information are presented in a special report to the department responsible, and furthermore to the faculty responsible, which centralize them, and send the final report to the university responsible for analysis of the university research activity. The ontology of the multi-agent system includes terms specific to this application (e.g. ISI_article, International_project, National_project, Informatics_research, Mathematics_research), that are used by the agents during communication. Figure 5 shows the interface of the system during a run for the academic year 2008-2009.

Figure 5. System interface during a run


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Figure 6 presents a screenshot of the UnivKM multi-agent system run, with the DOS windows, corresponding to each task agent. Figure 7 presents the agents society for this application.

Figure 6. Screenshot of the UnivKM multi-agent system run

Figure 7. The agents society for UnivKM multi-agent system run


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Figure 8 presents the Zeus task graph for the application.

Figure 8. The task graph for UnivKM multi-agent system

4.2 Educational management The second application consists in an agent-assisted students examination for online examinations that provides the test score by taking into account the number of the correct answers given by the student and the total duration of the test answering. As a case study we have considered an agent-based system that simulates an Object Oriented Programming test taken by a student and revised by the teacher. Figure 9 shows the specific architecture of UnivKM for the educational management application.

TeacherAgent

StudentAgent

Give_the_results Take_the_test

Figure 9. The specific architecture of UnivKM multi-agent system for

the educational management application


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Once the student starts the application, he will be explained the test’ rules and the conditions in which the examination will take place. The 10 multiple choice questions test window appears after pressing a button. This event will trigger the timer which will be stopped only when the test is ready. The test finish is confirmed by pressing the Submit button. The responses will be sent to the TeacherAgent for revision and the test’ results are displayed in the Test Results window.

Figure 10 presents a screenshot of the system run.

Figure 10. Screenshot of the UnivKM multi-agent system run for the educational management application

Figure 11 and 12 show the user interface of the test system, and the Object Oriented

Programming test.


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Figure 11. User interface of the test system

Submit

Figure 12. The Object Oriented Programming test


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5 Conclusion The paper presented a generic architecture of an agent-based system for knowledge management in a university. Also, we have described two experimental systems developed for an application from the university research management (research activity analysis), and for an application from the educational management (online students examination). For simplicity, we have developed a specific ontology for each application. Another solution would be to use the general university management ontology presented in [5] and to add the application specific terms.

Intelligent agents can improve the benefits obtained in the implementation of an university agent-based knowledge management system, due to their characteristics of autonomy, flexibility, pro-activity and sociality [10], [11]. The collaboration and implicit, the communication involved in a knowledge management system can be modeled in a natural way in multi-agent knowledge management systems.

REFERENCES [1] Bodea C., Andone, I. (2007): Knowledge management in the modern university, in Romanian, ASE

Printing House, Bucharest. [2] Dignum, V., Dignum F. (2003): Agent-Mediated Knowledge Sharing. In Proceedings of CEEMAS 2003,

Springer, 168-179. [3] Luan, J. (2002): Data Mining and Knowledge Management in Higher Education – Potential Applications.

AIR Forum, Toronto, Canada, 2002. [4] Mikulecká, J., and Mikulecký, P. (2000): University Knowledge Management – Issues and Prospects.

Research report. University of Hradec Králové. Czech Republic. [5] Oprea, M. (2009): An Ontology for Knowledge Management in Universities, In Proceedings of the 9th

International Conference on Informatics in Economy. ASE Printing House, Bucharest, 560-565. [6] Oprea, M. (2006): Multi-Agent System for University Course Timetable Scheduling. Proceedings of

ICVL 2006, Bucharest University Press, 231-238. [7] Smith, R.G., and Farquhar, A. (2000): The road ahead for knowledge management. AI Magazine, Winter,

17-40. [8] Valente, G. (2004): Artificial Intelligence Methods in Operational Knowledge Management. PhD Thesis.

Università degli Studi di Torino. [9] Weber, R., and Kaplan, R. (2003): Knowledge-based Knowledge Management. In Innovation in

Knowledge Engineering, 4:151-172. [10] Weiss, G. (1999): Multiagent systems, The MIT Press, Cambridge, Massachusetts. [11] Wooldridge, M., and Jennings, N.R. (1995): Intelligent agents: theory and practice. The Knowledge

Engineering Review, 10(2):115-152.

Differential Geometry of Surfaces with Mathcad: A Virtual Learning Approach

Nicolae DăneŃ

Technical University of Civil Engineering of Bucharest

124, Lacul Tei Blvd., Bucharest, RO-020396, ROMANIA E-mail: [email protected]

Abstract In this paper we propose an alternative to traditional teaching techniques of Differential Geometry. The new concept is to create a virtual learning environment by using modern software with good capabilities for plotting curves and surfaces. For this purpose we used Mathcad because this software has a user friendly interface in which it is easy to combine math equations, plots and texts.

Keywords: Differential Geometry, surfaces, tangent plane, Mathcad.

1. Introduction Teaching Differential Geometry of surfaces for students in engineering is a difficult task for every teacher, because this topic requires not only that the students have solid knowledge of geometry, calculus and linear algebra but they must also have a good 3D imagination. The Differential Geometry requires the use of visual tools for better understanding, because it is three–dimensional geometry with high complexity degree. Traditionally, for the study of a surface the teacher draws on the blackboard the surface, the tangent planes and normal lines at some point of the surface, some curves on surface and the angles between them etc.

In this paper we propose an alternative to traditional teaching techniques of Differential Geometry. The new concept is to create a virtual learning environment by using modern software with good capabilities for plotting curves and surfaces. For this purpose we used Mathcad because it has a user friendly interface in which it is easy to combine math equations, plots and texts. The models initially created by teacher for his lectures can be later used by students for the visualization of new surfaces or for computation of some numerical characteristic associated to the surfaces. All these facts are possible because the environment is an interactive Mathcad e-book in which the students can make their own changes and can see immediately the answer to these modifications.

Section 2 contains some theoretical background about the surfaces. This section is necessary especially for recalling the formulas used in the rest of the paper. Section 3 contains an example. To show the possibility offered by the techniques base on Mathcad for teaching Differential Geometry of surfaces we choose to study a simple surface: the elliptic paraboloid. In Section 4 there are some short conclusions.


277

2. Surfaces in Space: A Theoretical Background

A set 2R⊂D is called a domain if it is open and connected. The domain D is called an elementary domain if it is homeomorphic to an open disk. (A homeomorphism from a geometric figure to another is a one-to-one map that is continuous and has continuous inverse.)

A set S in space is called an elementary surface if it is the image of a planar

elementary domain D under a homeomorphism 3: Rr →Dρ

. If we fix in 3R the

canonical orthogonal basis ,, kjiρρσ

then the surface S has the parametric vector equation

[1] kjirρρρρ

),(),(),(),( vuzvuyvuxvu ++= , Dvu ∈),( .

The pair of the real numbers ),( vu is called the curvilinear coordinates of the point

),,( zyxP on the surface. In what follows we assume that the functions ),(),,( vuyvux

and ),( vuz are of class 1C on D . Such a surface is called smooth.

If in equation [1] we take 0vv = as a constant and let u varying, then we obtain a

space curve on the surface S ,

[2] )( 0vvu =Γ : kjirρρρρρρ

),(),(),(),()( 00001 vuzvuyvuxvuu ++== ,

called the coordinate u – curve. The derivate vector

[3] ),(),()( 000001 vuvu

uu

du

dur

rρ ρρρ

=∂∂

=

is the tangent vector at the curve uΓ at the point ),( 0000 zyxP , where

),( 000 vuxx = , ),( 000 vuyy = , ),( 000 vuyy = . Similarly, for 0uu = and v

varying, we obtain the coordinate v – curve on S ,

[4] )( 0uuv =Γ : kjirρρρρρρ

),(),(),(),()( 00002 vuzvuyvuxvuv ++== ,

and the tangent vector at the curve vΓ at the point ),( 0000 zyxP

[5] ),(),()( 000002 vuvu

vv

dv

dvr

rρ ρρρ

=∂∂

= .

We assume that the tangent vectors ),( vuurρ

and ),( vuvrρ

are linearly independent at

every point ),( vu belonging to D . This is equivalent with the fact that the cross product

vu rrNρρρ

×= is nonzero at every point Dvu ∈),( .

The plane through point ),( 0000 zyxP parallel to vectors ),( 00 vuurρ

and

),( 00 vuvrρ

is called the tangent plane to the surface S at 0P . This plane is denoted by

)(0

STP and has the vector equation

[6] ),(),(),(),( 000000 vubvuavuba vu rrrTρρρρ

++= , R∈ba, .


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The vector

[7] ),(),(),( vuvuvu vu rrNρρρ

×= , Dvu ∈),( ,

is called the normal vector to the surface S at the point ).,( vuP The straight line

through the point ),( 0000 zyxP of the surface S orthogonal to the tangent plane

)(0

STP is called the normal line to the surface S at point 0P . The vector equation of

the normal line is

[8] ),(),()( 0000 vutvut NrLρρρ

+= , R∈t .

An arbitrary curve Γ on the surface S is locally defined by equations for the curvilinear coordinates )(tuu = , )(tvv = , with t in a real interval I . The vector equation of the curve Γ is

[9] ))(),(()( tvtut rρρρ

= , It ∈ .

The length of the curvilinear segment situated on the curve )(tρρ

between the points

)( 11 ttM = and )( 22 ttM = is computed with the formula

[10] ∫= 2

1)(')( 21

t

tdttMML ρ

ρ.

For unexplained notions about surfaces see (Rovenski, 2000) and (Lipschutz, 1969).

3. A Case Study: The Elliptic paraboloid The elliptic paraboloid of semi-axis a and b has the equation

+=

2

2

2

2

2

1

b

y

a

xz .

A simple way to obtain parametric equations for this surface is to put ux = , vy = and

+=

2

2

2

2

2

1

b

v

a

uz ,

or, uax 2= , vby 2= and 22 vuz += . Thus the vector equation of the elliptic paraboloid is

[11] kjirρρρρ

)(22),( 22 vuvbuavu +++= , R∈vu, . The plot of this surface using this parameterization is shown in Figure 1. (For all the

plot of the elliptic paraboloid we will use the values 1=a and 1=b for semi-axis.) A better parameterization for plotting this surface is given by

[12] kjirρρρρ 2)sin(2)cos(2),( uvbvavu ++= , )2,0[, π∈∈ vu R .

See Figure 2 for an elliptic paraboloid plotted using this equation. The equation of the elliptic paraboloid must be defined in Mathcad in the form:


279

We now define a point 0P on the surface. To plot this point we use the Mathcad

function “CreateSpace” defined for a constant vector function )(tP .

The coordinate curves which pass through the point 0P are defined by formulas [2]

and [4]. They are plotted by using “CreateSpace” function.

Attention! First plot the point and the coordinate curves and then the surface. For the

first three plots use the option “3D Scatter Plot” and for the last plot use the option “Surface Plot” from Graph menu. Figure 2 shows the two coordinates curves on the surface.

r

P0 Γu, Γv, r,

Figure 1 Figure 2


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To plot the tangent plane and normal line we first define the derivatives of the vector function ),( vur

ρ, that is, the vectors ),( vuur

ρ and ),( vuvr

ρ, and compute their values by

using symbolic computation.

Now we can define the normal vector at the surface

The tangent plane and the normal line to the surface at the given point 0P have the

equations given by the formulas [6] and [8], respectively.

Figures 3 and 4 show the tangent plane and the normal line to the surface at the given

point.

P0 Γu, Γv, r, T,

P0 Γu, Γv, L, r, T,

Figure 3 Figure 4


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Let us now consider the following two curves which pass through the point ),( 00 vu

in the planar domain of definition of the surface. Figure 5 shows the graphs of these curves.

0 2 4 6

3

1

1

3

5

v0v1 t( )

v2 t( )

u0

u1 t( ) u2 t( ),

P0 Γ1, Γ2, t1, t2, r,

Figure 5 Figure 6 Then we define the two corresponding spatial curves situated on the elliptic paraboloid.

For plotting these curves we use the Mathcad function “CreateSpace”.

In order to plot and to compute the angle between these two curves we define the

derivative vectors of the curves,


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and then the tangent lines to curves at the point ),( 00 vu ,

The curves on the surface and the angle between them are shown in Figure 6. This picture suggests that the angle between these two curves at the given point is

equal with 2/π . A simple computation confirms this observation.

We can also easily calculate the lengths of these two curves.

Now we consider the following three curves on the elliptic paraboloid

These curves determine a curvilinear triangle on the paraboloid as we can view in

Figure 7. To compute the perimeter of this curvilinear triangle we define the derivative vectors

of every curve.

Then the perimeter is


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Finally, we define the tangent lines to the fist two curves at origin, which is their common point, and represent these lines. (See Figure 8.)

The angle between these curves at origin is

C1 C2, C3, r,

C1 C2, C3, t1, t2, r,

Figure 7 Figure 8

4. Conclusions Differential Geometry is considered a difficult topic by the students in engineering because using it requires good skills in geometry, calculus and linear algebra. But the first difficulty for them is to “see” the surfaces and the curves in space.

The paper shows that using modern software like Mathcad the teacher can help the students to really see the surfaces and all the other elements related to them (coordinate curves, tangent planes, normal lines, arbitrary curves on surfaces etc.). By using Mathcad the teacher has a huge advantage: the equations are written in Mathcad similar to the blackboard. The students can easily see the connections between surfaces and their equations.

REFERENCES Lipschutz, M. M. (1969): Differential Geometry. Schaum’s Outline Series, McGraw-Hill, New York, San

Francisco. Lorczak, P.R. (2001): 3D Plotting from the Mathcad Treasury. Updated to Mathcad 2001. MathSoft

Engineering and Education, Inc. Rovenski, V. (2000): Geometry of Curves and Surfaces with MAPLE. Birlhäuser, Boston, Basel, Berlin.

Restructuring the Easy Learning On-line Platform

Radu Rădescu, Radu VelŃan, Raul Tudor

Polytechnic University of Bucharest,

Applied Electronics and Information Engineering Dept. 1-3, Iuliu Maniu Blvd., Sector 6, ROMANIA


Abstract The present paper deals with the methodology used to reinvent the Easy Learning platform, in order to facilitate the overall control of this e-learning system. The main goal was to increase the coherence in writing the code and in designing the database. Therefore, the programming errors are easy to detect and the flexibility of the platform modules is increased. The best solution was to use the Symfony architecture, for its independence on the database. The restructuring of the platform has two purposes: unification of the existing database components and standardization of the basic rules for programming. Keywords: eLearning platform, Symfony architecture, Modules design

1 Introduction: Implementing Problems The need to restructure the learning process without influencing the quality of information passed on to the student is the very first problem we encounter when trying to migrate from a classic education system to eLearning. As long as the tutor who creates the course bears in mind the end result, which is the current level of the student and the goal level he should reach, the teaching process’s quality will not suffer.

The eLearning term is starting to be interpreted in various ways and even if standardization is applied, it will not be able to fit the term in strict boundaries, as this term has become generic. The passing to the virtual teaching methods must be done in such a manner so that the human model will not diminish in any way its methodic and didactic skills. From this perspective, the virtualization must be done based on pragmatic, humanizes methods with applicability in real life.

This section identifies some issues that might occur and stifle the transition process and the inherent risks any change creates.

The additional work that the tutor is supposed to put into in order to modify the didactic material as well as restructuring the presentation form of that material is the first problem we encounter. Even if the manual used in the classic system contains the right information, if it is just transferred in an electronic environment the result will be far from the desired one if the material is not properly adjusted [2].

In addition, the additional work will need more advanced skills in computer science and maybe the second problem is more pressing than the first for many tutors who are


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experts in their fields, but have limited knowledge in IT. A solution to this problem could be a prior course in computer use before the actual undertaking of an eLearning course, so that tasks such as manipulating web texts and e-mail correspondence become trivial. When a tutor is forced to work, only with eLearning tools without any background training the chance of dismissal of the entire web-based system rise dramatically.

eLearning is much more than a simple web page creation for a certain course; it must also involve the constant communication between the tutor and the students of the virtual class. Only in this way, the human factor can intervene in the students forming process. The simple posting of an electronic content and password-protected access is without a doubt insufficient for the implementation of an eLearning system.

The mentioned problems generate a third one: additional funding is needed, as expenses rise (due to overtime, or the further training of already employed staff or even creating new jobs) because the finished product is directly linked to the quality of the human resource. Besides these expenses, more are generated by the need to upgrade the infrastructure (both hardware and software) of the institution.

The funding issue is therefore a serious one, even if software is purchased (such as Blackboard, WebCT, etc.) or the platform is produced in-house (such as the Easy-Learning platform). Again, the same problem pops up: the training needed for the staff that will manage the hard and soft components of the eLearning system.

This section presents the risks that might occur when the mentioned problems are treated superficially, as well as the ones generated by the unsuited handling of teaching methods and course development. The major risk involved in an eLearning system is the students loss of interest in both this kind of teaching method and the courses included by the system. An on-line course can never substitute for a tutor’s charisma and his ability to adapt to a certain situation through a subtle humor or changing the pedagogic strategies at the right time. Therefore, it is a real possibility that the rupture created by a virtual environment will cause a student to become estranged from the community. Although creating virtual communities is a priority in an eLearning system, nothing can really substitute for human interaction.

Although there are many on-line communication methods, both synchronous (chat rooms) and asynchronous (e-mail, forums), the loss of communication between the student and tutor, as well as between the students themselves is a real danger. Many times a student seeks in the education process a right of passage into the real world.

That is why the introduction of active mediators in forums and appointing a percent of the grade to the student’s involvement in the on-line discussions are suggestions that could maintain an acceptable communication level [2].

In addition, this dependency on technology for the complete teaching process is a risk in itself. Any problems that appear in the infrastructure hide the students’ access to information. That is why every precaution must be taken in order to avoid situations like the above. Although there are many risks involved, the migration to an eLearning system is strictly necessary. Society is evolving and the learning process seems to become never-ending, and this implicitly will lead to the creating of more-and-more on-line teaching systems. The key is to make the transition with at little risks as possible and always adapt the transition process to the society’s needs. This is why illustrating and describing the problems that might occur is the first step in solving them.


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2 The Structural Model of the Database The structural model of the Easy-Learning platform is centered around the relational database. It stores in well-defined tables the entire structure of the software application. It is the main component of a learning platform, and a good design is imperative for the smooth functioning of such a project.

Fig. 1. The Easy-Learning Database Diagram


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Figure 1 illustrates the database structure and its tables. As the database was implemented, the main factors that were taken into account were:

• Logic; • Homogeneity; • Simple links between tables; • Uniform structure; • Maintaining a buffer zone for further additions of tables and fields.

If these simple conditions are met, the project will have a solid foundation, extremely easy to handle.

At a first glance, it may look crowded and hard to follow. Actually, we tried to create very simple table relations, with as few link tables as possible. This was achieved by limiting the number of fields a table can have. This led to a higher table count, but it was a small price to pay considering the logic and control it offers.

We should note the fact that even the most complex query does not link more than three tables simultaneously, which dramatically reduces the query’s execution time to a few ms, a big improvement considering the old platforms results.

3 The Administrator, Tutors, and Students Modules These three modules should be analyzed and presented together because of the close relationship that exists between them. A student or a tutor, even if they will exist separately in the „students” or „tutor” table, they both will have an associated user, through which they can access the platform.

The users module is extremely important, because this module manages all permissions and access rights in the Easy-Learning platform. It must be said that this module is a plug-in for the existing platform, and it should be explained a bit first. The entire plug-in comes with 8 separate tables in the database, and it will store every user in the database, as well as the user groups, and the permission of every user profile.

The Easy-Learning platform has three types of user groups: Administrator, Student and Tutor. Each group can access just one interface of the platform. The groups and the group’s permission can be managed through the sfGuardGroup and the sfGuardPermission modules in the administrator interface. These three groups have been deemed sufficient for the current platform, and although this type of segmentation can seem stifling (as an example it can be argued that the administrator should access all the interfaces) there are strong arguments to indicate otherwise.

4 The Administrator Interface The administrator interface can be considered as the backbone of the entire application. Within this interface, users as well as their permissions are managed, as well as the school years, which are used in the new database structure as the essential separator between students and courses. As every course and student group are linked to a school year, a better management of the class book was tried, as the old platform had problems in that sense. As an example, there can now exist two student groups with the tag


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„443A”, which can have very different students, or even common ones, if a student failed a year and was obliged to retake it, but each group situation is stored and interpreted differently. In addition, because a similar link exists between any course and a school year, it means we can keep a clear statistic for every year.

As we can see from the database diagram, the „course” table is in the center of the database, because of the multiple direct or indirect links it has. As data consistency it is a must in every database, an automated generator was used to create the modules which manage every table linked to the „course” and „users” tables. The current platform allows just configuring a „generator.yml” file and a completely functional module is auto-generated by the Symfony framework.

Thus, the advantages Symfony offers were used to their full potential, and the actual work was lessened, once the manipulation process of such a generator was fully understood. Although this type of generator offers more than enough advantages, there were some moments when it was not enough and certain custom actions were necessary to maintain the logical way of introducing information into the database.

Each module is secured through the pre Execute () function, which is present in every module. The Symfony framework will execute this function before anything else in each module, and in this function, the logged user’s permission rights are verified. If he does not have the right credentials, access will be denied. This check may seem redundant, but it comes to prevent a Symfony spec saying that a logged user can access any interface. Therefore, a logged student could have access to the tutor and administrator interfaces, but this preliminary check removes any doubts regarding the platform’s security.

5 The Tutors Interface In this interface much of the actions undertaken by the administrator in the „course”, „notice” and „time table” modules have been kept, as it also a tutor’s job to create and manage the above modules, as the information he can have access to is limited.

As every tutor must log in order to access the interface, a major problem had to be overcome: how to display and manage only the information directly linked to the logged tutor. This issue had to be resolved, because the whole point of an authenticated interface is to limit the displayed information for the tutor, but also provide total control over that particular information.

Thus, the „course” module will only show the courses that are directly linked to the logged tutor, and the tutor will have full control over this data. The same criterion is applied to the „notice” and „time table” modules, because they are closely linked to the „course” module. This way we ensure the fact that tutor X will have full control over his information, but can’t access any of tutor Y’s information, leaving the administrator the only type of user who can access all the information, avoiding abuse and false data entries.

Besides the mentioned modules, which have also been automatically generated, just like every module in the administrator interface, the first custom build modules have appeared. These modules were harder to create, because the code had to be written from scratch.

It should be mentioned that even the custom modules have the same 4 base actions as the automatically generated ones, which are adding, editing, listing and deleting, for the following reasons:


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The automatically generated code is extremely robust, but also very flexible, thus the same conduct of writing code was attempted.

The php files from the view layer could be copied from the automatically generated ones to keep coherence at a visual level throughout the application

Thus two more modules have been added, „personal data” and „documents”.

6 The Students Interface The logic behind all that management in the administrator and tutor interfaces is to inform the students. Although in this particular interface the student will be able to manage just one thing, its personal data, and the real important fact is the information quantity displayed by the platform to each student.

He will have access only to the information he is interested in: which courses he is undertaking, what are his grades for each course, his colleagues, tutors and time tables for every course.

As we can see the courses are in the center of this information web, and it is represented, to be more specific, by the links created between a course and a student in the database through the administrator and tutor interface

In fact, all the work undertaken to create courses, student groups, faculties and so on was done so that the student can accumulate knowledge from only a click away, which is the end result of the Easy-Learning platform. Alongside this central goal, the tutors now have a more elegant and transparent way to manage their students and courses.

7 Conclusions The Easy-Learning platform started out as a simple project, but, as the years passed, it became, though extremely useful from the student’s point of view, a very hard to control teaching instrument. Because every year somebody else appended new code to the existing one, because every programmer has a specific style, and mostly because the database had become incoherent, any bugs that had to be handled or improving an existing segment became daunting tasks.

It became clear that a ground restructuring was needed, and it had the following guidelines:

Joining all the existing databases that served the same platform into a single one, a database that could offer data cohesion and the flexibility of adding new tables as the platform grows.

Standardization of the code written and laying some ground rules as to how the code will be written and commented, so that any programmer can easily understand and debug old code, as well as writing new one in the same manner.

The Symfony platform was a logical and inspired choice. It does not depend on a certain type of database (MySQL, PosGreSQL, etc.) certain flexibility has been ensured in the case that the platform will be moved to another type of database.

Once familiarized with the framework, any programmer will be able to improve/debug old code as well as creating new one. One of the old platforms major issues, the many


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code styles present in different segments, was resolved by using the Symfony framework, because it constrains the programmer to write code only in specific places, following OOP rules, so that any code will become more or less standard.

With this in mind, the actual implementing was quite easy, because of the many helpers Symfony provides (sfGuard plug-in, module generators and page generators).

The issues we encountered were technical ones, where the module generators (which are the foundation of the administrator interface) were not complex enough on their own. Still because of Symfony’s flexibility, any action within the generated modules could be override in any way a programmer desires, so that the module meets the specifications.

This new platform was not built to add new facilities, but to transpose the old ones in a new shape, a shape that is much more manageable and maintainable. Using the Symfony framework, a robust and heavily tested framework proved to be a very inspired choice, which can now permit the new platform to grow in an organized manner, as it now has a flexible database to rely on. We can safely assume that the reorganization of the Easy-Learning platform was a complete success.

REFERENCES

1. Rădescu R., Urse C. (2007): Graphic Tools in the Easy-Learning Platform. In The Symposium TEPE

„Educational Technologies on Electronic Platforms in Engineering High Education”, Technical University of Civil Engineering of Bucharest, Bucharest. ISSN 1843-2263.

2. Nagy, A. (2005): E-Content: Technologies and Perspectives for the European Market, in The Impact of E-Learning, Berlin, 79-96.

3. Bååth, J. A. (1982): Distance Students' Learning – Empirical Findings and Theoretical Deliberations, Stockholm, 30-32.

4. Scott W. A. (2000): Mapping Objects to Relational Databases: O/R Mapping in Detail, Practice Leader, Agile Development, IBM, Software Group.

5. Boodhoo J. P. (2006): Design Patterns: Model View Presenter, Microsoft. 6. Rădescu R., Urse C. (2007): Advanced Testing Methods in the Easy-Learning Platform. In The 8-th

European Conference E-COMM-LINE, SIV-26e/1…6, Bucharest. 7. Rădescu R., Bojin M. (2006): Function generators in the Easy-Learning Platform. In The National

Conference of Virtual Education “Virtual Learning – Virtual Reality”, Educational Software & Management, 4th Edition, University of Bucharest, Mathematics and Informatics Faculty, Bucharest, 115-120.

8. Rădescu R., Iovan R. (2005): Generating the class register in the Easy-Learning platform. In The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Educational Software & Management, 3rd Edition, University of Bucharest, Mathematics and Informatics Faculty, Bucharest, 213-220.

9. Rădescu R., Iovan R. (2005): Creating and using tests in the Easy-Learning platform. In The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Educational Software & Management, 3rd Edition, University of Bucharest, Mathematics and Informatics Faculty, Bucharest, 229-235.

10. Rădescu R.: E-learning: concepts, implementation and applications, IT&C Market Watch, Fin Watch, 50 (no. 30/2004, co-author Lăcraru C.), 61 (no 31/2004), 50 (no. 33/2004), Bucharest.

11. Rădescu R., Iovan R. (2004): Improvements to the Easy-Learning E-learning Platform. In The 5-th European Conference E-COMM-LINE, Bucharest, 275-278.

12. Rădescu R., Iovan R. (2005): New Facilities of the Easy-Learning Platform, in Proceedings of the Symposium “Educational Technologies on Electronic Platforms in Engineering Higher Education” (TEPE 2005), Technical University of Civil Engineering of Bucharest, 27-28 May 2005, Bucharest, 219-226.


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13. Rădescu R., Mărescu R. (2005): External Use of the Easy-Learning Platform: a Web-Based Application. In Proceedings of the Symposium “Educational Technologies on Electronic Platforms in Engineering Higher Education” (TEPE 2005), Technical University of Civil Engineering of Bucharest, 27-28 May 2005, Bucharest, 227-234.

14. Rădescu R. (2008): Class register optimization in the Easy-Learning platform. In The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 6th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 31 – Nov. 2nd, Bucharest, B-7-55/1...4.

15. Rădescu R. (2008): Multiple tests in the Easy-Learning platform. In The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 6th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 31 – Nov. 2nd, Bucharest, B-6-54/1...4.

16. Rădescu R. (2007): Test user interface in the Easy-Learning platform, The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 5th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 26-28, 2007, Bucharest, 85-92.

17. Rădescu R. (2007): Test management interface in the Easy-Learning platform, The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 5th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 26-28, 2007, Bucharest, 75-84.

18. http://www.symfony-project.org/book/1_0/ 19. http://www.zend.com/zend/zend-engine-summary.php 20. http://forge.mysql.com/wiki/MySQL_Internals

New Operating Tools in the Easy Learning On-line Platform

Radu Rădescu, Adrian Şişu, Raul Tudor

Polytechnic University of Bucharest,

Applied Electronics and Information Engineering Dept. 1-3, Iuliu Maniu Blvd., Sector 6, ROMANIA


Abstract The present paper deals with the new tools introduced in the Easy Learning platform. The first layer of this architecture implemented by the Symfony tool is the model layer, based exclusively on an abstract version of the database and on the users’ access to data and recordings. Following this model, the database was conceived and designed as the core of the whole project. The interaction tutor-student using the database is considered in all its statistical aspects. A conclusive example is given in the case of the testing module, emphasizing the advantages introduced for all the actors involved in the e-learning process.

Keywords: eLearning platform, Symfony architecture, Modules design

Introduction: A Short History of the Easy-Learning Platform In 2004, the first version of the Easy-Learning platform emerged. It was a new interaction method between a tutor and his students, even though it was limited to managing the laboratory class book. Thus, every student was able to see all obtained grade points, throughout the activity.

By default, this first version was somewhat limited. During the last five years, the platform suffered multiple adjustments, taking into consideration the always-emerging necessities, having good but also bad repercussions. The very first restructuring gave birth to the three known interfaces: Administrator, Tutor and Student. This structure helped limiting tasks to every type of user. The changed proved to be logical and well received.

The Administrator interface took up some of the tutor’s tasks, such like creating series and groups of students, along with populating them.

The Tutor interface gave up the administrative tasks, making life easier for every tutor (class structure, class books, timetables became the main attributes of a tutor).

The Student interface aside from viewing class books and timetables received the main role of sustaining on-line tests, taking laboratory classes etc. This way the student had permanent access to the platform’s eLearning content.

Disadvantages of the Existing Platform And the Saturation Point As any other software product out there, Easy-Learning has a life cycle, starting with the concept and ending with the saturation point. Now, the main drawback is the lack of


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homogeneity. Its backbone may not be the most suited one, so that in many cases it may lose its purpose: helping. This is due to the numerous patches made by different programmers (mostly students). It has come to a very strenuous code, any error being almost impossible to debug.

The main database ca not handles all the requests, having a much to fork, non-unitary structure. This might be proved through the power of example, because the most harmed modules are the ones on which it is acted from multiple interfaces.

The logic behind the testing module proved not to be the most suited one, on a long term. A test is based on the questions inserted by a tutor, selecting a given number of them. However, there is a limit, not imposed, so that the questions that have overcome this limit would never be taken into consideration for a test. This is also due to the overcharge of the database, with it’s too many unstable connections.

Other examples are the class book and classes modules. Any class has a structure composed by the grade points of all the afferent activities. However, for the old platform, this structure was only configurable once. Any edit on it during the academic year would turn all the activities inside out. Editing a structure is necessary because of the grade points variations or any other time factor.

In addition, all the formulas that were calculating grades aggravated a tutor’s activity, being uneven. Teaching activities had different formulas, using different percents. The tutor had to remember if for the activity X the grade was composed of points of percent of the final grade. Therefore, students viewed mistakes and so there was place for confusions.

Problems may continue with promoting series, groups and students from one year to another, this being impossible with the old platform. The tutor had to recreate them after every academic year. A counter was a solution but it was not implemented. The new Easy-Learning platform, along with its new tools, tries to solve all these problems and even more, to extend it’s functionality using the model of renowned universities.

New Modules of the Tutor Interface The tutor interface is the main relationship between a tutor and the platform. Using it may keep a strong link with the students.

It provides options for editing personal data of the authenticated tutor along with classes, timetables, documents and announcements. The main attributes of this interface are concentrated in the class book like, tests, questions and categories modules. A more detailed description for them is available next.

These modules were a challenge for the Symfony framework’s architecture. Its main system, admin generators for every table of the database proved to be insufficient. Therefore, we needed to manually build them using forms, validations, actions, editing and templates. The base classes of the framework and the tree-like architecture of the project took the main stage.

The Class Book Module Through this module, the tutor may manage grade points for every one of his students. As it may be seen in Figure 1, the list action allows viewing a complete list of grade points


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for every existing student in the database. The form contains, along with the actual list, an active filter only if there are records. If there is not any available evidence, the filter will not be listed.

Fig. 1. Available Class Book Lists

Available actions are: edit ( ) and delete ( ) which apply to he current record. In order to prevent accidents, the delete action is provided with a confirmation from the user. The Create new evidence button redirects the user to a new form, where new class books can be made (see Figure 2). At this moment, the user can return to the list or proceed with adding new evidence.

Fig. 2. Creating A New Evidence

The form contains a combo-box populated with the list of students, edit-boxes for every grade point and filters by class and student. Here comes the first innovation of this module: the tutor will insert, for every type of activity, regardless of it’s share, a score of maximum 100 points. This score is taken by the general formula, based on the actual


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shares of each activity and converted to a final score of maximum 100 points too. All this formulae and conversions are invisible to the user to ease up the task. In the student interface, he/she will see the real score detailed for every activity and as a final grade.

The Laboratory Class Book Module This module was one of the most difficult to implement (along with the test module), using the most complex tools available. Here, the tutor will be able to manage all the grade points of laboratory-like activities for his students.

The action list allows viewing all available scores, and filtering them by discipline. The same rule with the active/inactive filter will apply. In addition, the same actions are available, as seen in Figure 3: edit ( ) and delete ( ). The Create button will redirect the user, as in the previous case to the proper form. There are a few steps to be followed. The first one is choosing a class and hitting the add button. A new form will open (Figure 3), the one for the actual creation of the evidence.

Fig. 3. Creating A New Laboratory Evidence

Due to the database query, posted in actionClass, the logged in tutor, will only have access to his classes and students, thus properly limiting activities. This selection applies to all Tutor interface modules.

Through this form, a student might be chosen so that he will have evidence attributed. With a simple click on the attendance check box, the required attendance ill is added. Along with listing the right date and time, these are automatically taken from the system’s clock, with the help of a JavaScript. Annulling the attendance requires just


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another click. If the selected laboratory had a test attached, the tutor may grade it using the combo-box, which has scores between 0 and 100. This score will be part of the laboratory grade formula, based on the appropriate share of the laboratory tests activity.

The last section of the form, other grades, contains two combo-boxes with scores also between 0 and 100 for the essay and final test activities. The same formula and shares principles apply. The final test is the most complex because when a student finishes it, after grading and finalizing it, the final grade will automatically fill the right field, so that the user is exempt of writing it by hand. For a quicker search of the students in the lower side of the form, there is a filter by groups.

Tests/Questionnaires, Questions and Questions Categories modules These modules will be treated together because they are interdependent, question categories being the base of the ahead thought theory for building tests.

In order to describe better the mechanics of these modules we will refer to the crowds’ theory. Suppose a laboratory final test with 20 questions. The activity was structured on multiple sessions, every session having it’s own laboratory platform. In order to include the entire class subject, the test must contain questions from every platform. The diagram in Figure 4 represents graphically this procedure.

Fig. 4. Selecting Questions Procedure

Same as for the other modules, there is a list action for every available test of the authorized tutor, sorted by classes. This time, the actions column is far more complex. It contains the usual edit ( ) and delete ( ) buttons, but also ones for listing questions ( ) and grading the test ( ).

The Add test form becomes available after acting on the Add test/questionnaire button. This builds the skeleton of a test, to be modeled later using the earlier presented procedure. Multiple variables must be selected: class, type, name, length and number of questions. It should be mentioned that a test becomes available for a student only if the active status is selected. After setting the details, the user may create question categories.


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The categories module is specially designed for this purpose. The name of a category is attributed to an indicator number used in allocating questions.

When categories have been added, the user may return to the test module where he can build questions for the test, sorted by his own categories. This may be done with a click on the List questions button ( ) (see Figure 5)

Fig. 5. Question List For The Current Test The Create a new question form uses tools that were the hardest to implement and

develop, due to the complexity and multiple variable cases. Thus, the user will run through a series of steps, one dependent of the previous. He will select the type of the question from a combo-box. This type may be: text, unique answer, and multiple answers. When this is finished, clicking on the button Choose will open a new form, specific for the selected type. Supposing this was Multiple answers, the next step is selecting the number of options and the category.

The last step is creating a statement and possible answers. In addition, the tutor will check the right answer(s) in order to grade it later (see Figure 6).

Fig. 6. Forming A Statement And The Possible Answer Now the question can be saved and the procedure will resume in the same manner for

every question. When the test was populated with all the wanted questions, it will become


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available to the student that will sustain it (to be talked about later on). When he will have finished, it will be available for grading by the tutor. This is what the grade button ( ) is for.

The grade test form contains all the questions for the specific test along with the answers provided by the student. A score will be selected for every question, between 0 and 100, with a 10 points step, so that every question is graded percentage-like, the final grade containing all the scores. Once all the scores will have been finalized, the laboratory grade will be set in the grades evidence module. This time too, conversions are invisible, so that the final score is actually a grade (see Figure 7).

Fig. 7. Finalize Grading A Test

Conclusions The Easy-Learning platform may be considered a great way of real-time distance interaction, between tutor and student. In order to describe better this whole process, based on the diagram below, we will use the types of access to the database for the two types of users. The 90% true case is:

• the tutor will access the database by update, insert, delete, select actions, so mostly adding and deleting records that the student may use.

• the student will use ONLY select-like actions to view records. He will almost never alter the records structure because permissions do not allow him to.

The above rule is 90% valid as there is one exception: the tests module. Here, the 2-way interaction contains acting on the database by both ends. There are six steps building the procedure for sustaining a test, from its creation to listing the obtained grade:

1. The tutor builds a new test inserting it in the database; 2. The student sees a new test and opens it in order to take it;


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3. The student takes the test adding results in the database; 4. The tutor obtains the answers in order to grade them; 5. The tutor grades the test and inserts the grade; 6. The student sees his grade.

Taking into account the above description it is clear that the student editing access is extremely restricted. Even in the test case. For the evidence modules, the objective was to ease up as much as possible the work of a tutor, along with the student understanding the grade standards and detailed scores. This way, a tutor will grade of maximum 100% for every activity, regardless of importance or share. In addition, graded activities may be changed at any point in time, a missing aspect of the old Easy-Learning platform. The advantage also applies to the student, as presented throughout the article. In the end, it is a known fact that the purpose of Easy-Learning is to help and not burden.

REFERENCES

1. Nagy, A. (2005): E-Content: Technologies and Perspectives for the European Market, in The Impact of E-

Learning, Berlin, 79-96. 2. Bååth, J. A. (1982): Distance Students' Learning – Empirical Findings and Theoretical Deliberations,

Stockholm, 30-32. 3. Scott W. A. (2000): Mapping Objects to Relational Databases: O/R Mapping in Detail, Practice Leader,

Agile Development, IBM, Software Group. 4. Boodhoo J. P. (2006): Design Patterns: Model View Presenter, Microsoft. 5. Rădescu R., Urse C. (2007): Advanced Testing Methods in the Easy-Learning Platform. In The 8-th

European Conference E-COMM-LINE, SIV-26e/1…6, Bucharest. 6. Rădescu R., Iovan R. (2005): Generating the class register in the Easy-Learning platform. In The National

Conference of Virtual Education “Virtual Learning – Virtual Reality”, Educational Software & Management, 3rd Edition, University of Bucharest, Mathematics and Informatics Faculty, Bucharest, 213-220.

7. Rădescu R., Iovan R. (2005): Creating and using tests in the Easy-Learning platform. In The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Educational Software & Management, 3rd Edition, University of Bucharest, Mathematics and Informatics Faculty, Bucharest, 229-235.

8. Rădescu R., Iovan R. (2004): Improvements to the Easy-Learning E-learning Platform. In The 5-th European Conference E-COMM-LINE, Bucharest, 275-278.

9. Rădescu R., Iovan R. (2005): New Facilities of the Easy-Learning Platform, in Proceedings of the Symposium “Educational Technologies on Electronic Platforms in Engineering Higher Education” (TEPE 2005), Technical University of Civil Engineering of Bucharest, 27-28 May 2005, Bucharest, 219-226.

10. Rădescu R. (2008): Multiple tests in the Easy-Learning platform. In The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 6th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 31 – Nov. 2nd, Bucharest, B-6-54/1...4.

11. Rădescu R. (2007): Test user interface in the Easy-Learning platform, The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 5th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 26-28, 2007, Bucharest, 85-92.

12. Rădescu R. (2007): Test management interface in the Easy-Learning platform, The National Conference of Virtual Education “Virtual Learning – Virtual Reality”, Modern methods in Education and Research, 5th Edition, University of Bucharest and „Ovidius” University of ConstanŃa, Oct. 26-28, 2007, Bucharest, 75-84.

A Hybrid Recommender System for E-learning Environments Based on Concept Maps and Collaborative Tagging

Ahmad A. Kardan, Solmaz Abbaspour, Fatemeh Hendijanifard

Advanced E-Learning Technology Laboratory

Department of Computer Engineering and Information Technology Amirkabir University of Technology, Tehran, Iran

aakardan, s_abbaspour, hendijani @aut.ac.ir

Abstract

Recommender Systems could be used to suggest the items being interested for learners in an e-learning environment. These systems can be useful to recommend learning resources or any other supportive advices to the learners. Different kind of algorithms such as user-based and item-based collaborative filtering have been used to establish a recommender system. With increasing popularity of the collaborative tagging systems, tags could be interesting and useful information which could be considered as part of a metadata to enhance recommender system's algorithms. On the other hand concept maps can be a useful means for learners to visualize their knowledge. Therefore, learners could be supported in their own learning path by recommending concept maps, tags, and learning resources, and also the learning performance of individual learners could be promoted. In this paper, an innovative architecture for a recommender system dedicated to the e-learning environments is introduced. This system simultaneously takes advantage of collaborative tagging and concept maps. By mapping the tags and concepts completed by a learner, incomprehensible facts of his/her knowledge will be identified. Therefore, recommending concept maps containing related and not being understood tags, will be helpful. In the proposed algorithm the similarity of concept maps and tags being labeled by users are computed to achieve the best suggestion.

Keywords: Recommender Systems, Concept Maps, Collaborative Tagging, E-learning

1 Introduction Web-based learning environments are becoming very popular. Typical E-learning environments, such as Moodle (Riordan and Marcais) and Blackboard include course content delivery tools, synchronous and asynchronous conferencing systems, Forums, quiz modules, sharing resources, white boards and etc. In these environments, educators utilize resources such as text, and multimedia to develop the learning progress. Learners are encouraged to study the resources and participate in activities. However, for learners it is very difficult and time consuming to track and assess all the activities and resources. On the learner’s side, it would be useful if the system could automatically guide the learner’s learning path, and intelligently recommend on-line activities or resources that would improve the learning process. “The automatic recommendation could be based on


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the instructor’s sequence of navigation in the course material, or, it could be based on navigation patterns of other successful learners.” (Osmar R. Za¨ıane 2002)

A user profile is a collection of personal data associated to a specific user, and refers to the explicit digital representation of a person's identity. A user profile can also be considered as computer representation of a user model. User profiles are constructed by different kind of information such as the user’s knowledge, interests, goals, background, and individual traits. In this paper we use a collaborative tagging system in the proposed E-learning environment and utilize the tag collections of the user as the user’s interest in a specific topic. We also assume that each learner in the system is capable of illustrating his knowledge with a concept map.

In collaborative tagging system the users tag the resources they’ve studied by labeling them with specific labels. The tag collection of each user can identify his/her interests in different topics. Concept maps are an explicit graphical representation of a human’s understandings in a domain of knowledge. Concept maps represent this understanding by means of a two-dimensional network in which nodes correspond to concepts, and links correspond to the relationships between concepts. In a concept map, concepts are the labels used to refer to objects or events and linking phrases (the text on the links) are usually verbs (Novak & Gowin, 1984; Valerio et al 2008).

Given that each person’s understanding of a domain is different, even if people construct concept maps on the same topic, the maps constructed by individuals are different, reflecting their personal knowledge structures (Valerio et al 2008). Hence concept maps can be used for knowledge sharing and comparison.

In this paper, we describe the architecture of an automatic recommendation system for learning environments that considers the profiles of the learners containing his/her tags and concept maps.

2 Related Works Recommender Systems: recommender systems are a new method on the internet in which it suggests and advices the users the items that they may wish to purchase. With the large information expansion, users need a complete facility to find and navigate their needs. A recent survey of recommender systems could be found in (Maes, Guttman & Moukas, 1999).

The most popular recommender systems that are used and produced these days are the collaborative filtering type. The method is such that they aggregate information about the users and after locating the similarities between users, specific recommendation is given to them. This type of recommender systems can either be item-based or user-based. Such a system can be seen in Ringo that makes use of the user's music preferences which is calculated by taking count of albums and artists rated by the user (Shardanand & Maes, 1995).

Another well known recommender system is the content-based type, which are based on machine learning research. They have the ability to parse the content and classify it in order to make the best recommendation. "These systems use supervised machine learning to induce a classifier that can discriminate between items interesting to the user and those uninteresting."


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These two kinds of recommender systems have some differences to one another. One of the advantages of collaborative filtering is that it is suitable for suggesting any kind of resource, e.g. photos, text, videos and music (Herlocker J.L et al. 2000). The algorithm is only based on the historical data and preferences of the target user.

In this article an algorithm is suggested that acts like a collaborative filtering recommender system to provide recommendations to the learners. It aggregates the learners' interests specifically tags and concept maps, and finally by locating a similarity between the resources, provides recommendations.

Concept Maps: Concept mapping (Novak & Gowin 1984) has been widely used by individuals from elementary school students to scientists to externalize knowledge, conduct knowledge construction (David B. Leake et al. 2003), share knowledge, and compare knowledge to advance human learning and understanding (David Leake et al. 2004). In concept mapping, subjects construct a two dimensional, visually-based representation of concepts and their relationships (David B. Leake et al. 2003) . The flexibility in constructing concept maps is commonly regarded as an advantage of concept mapping for use in many fields (Valerio .et al 2008). “The map reflects what the person knows, and for experts, the map is used to represent the idiosyncrasies of each expert” (Valerio .et al 2008). The study being done by Tarouco, Geller, and Medina’s (2006) addressed that using concept maps increase the organized communication among participants (Simone C. O. et al. 2008).

Collaborative Tagging:" Tagging is a way to organize content through labeling." By this means we can relate meanings to different resources such as texts, URLs, photos and music. "Tags are keywords that can be associated with content as a simple form of metadata”. There is no restriction in associating tags to content. We can use any word and phrase that we desire. In contrary in systems like the library we have to define specific keywords as a string on the resource. (On Kee Lee. S; Hon Wai Chun. A, 2007). The phrase Collaborative tagging is the process of sharing items and recourses so that everyone can take advantage of them. Users can organize their own knowledge such that all participants can view and benefit from the labeling.

It appears that using tags as discussed above is easy and flexible, but as it is obvious the non limitation of using any phrase to explain contents can be ambiguous and cause redundancy problems. Tags used in this way lack semantic meanings and can be complicating and miss understood. For example the phrase "apple" can refer to the fruit, and also can point to Apple Macintosh computers. In this case extracting the right meaning from these phrases can be hard to accomplish.

3 System Architecture The system architecture that we have proposed in this article can be seen in figure 1. The recommendation process is composed of seven stages:

1. Users study resources 2. Users tag resources 3. Users create concept maps 4. The system finds similar tags for recommendation


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5. The system finds similar concept maps for recommendation 6. Match the words of tags and concept maps of one user 7. Give final recommendation to users

Figure 9. System Architecture

3.1 Detail in each Stage Users study the resources: In this stage users can read from the resource repository. These resources can be contents that the educator has placed for the students. We illustrate these contents with the list of n contents and defined as: .

Users tag the resources: After the user reads the content, he can tag the resource with one or more keywords to demonstrate his knowledge of that content. As discussed in (Ae-Ttie Ji et al. 2007 ) for a set of m tags T = , tag usages of k users can be represented as a User-tag matrix, A (k × m). Each represents the frequency of meaning how many times a user u has been tagging with a tag t.

Users create the concept maps: In this section each user can describe his knowledge about a particular subject by modeling it in a concept map. Each node of the concept map can contain a tag that user has used in the previous stage to describe a resource. The set of user's concept map is represented as

System finds similar tags: In this section we present a formula which makes use of the similarity between the users tags to identify users who have similar concerns. The output of this formula is a number which illustrates the similarity between the users. As discussed in paper (Ae-Ttie Ji et al. 2007 ) we can calculate the user-user similarity with equation 1.


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[1]

Where u and v are the users and the matrix A is the matrix explained in the previous section. In order to find k nearest neighbor (KNN), cosine similarities between a target user and each user with tag frequencies of corresponding user in user-tag matrix, A is calculated. KNN includes users who have higher similarity score than the other users and means a set of users who prefer more similar tags with a target user. In the next stage we find the interest of user u to a particular tag:

Find similar concept maps: To find the similarity between two concept maps a

comparison should be made. To deal with the concept map comparison problem one method is to assume each concept map as a graph and aim to achieve the best solution that depicts the similarity between two different graphs. For this, a semantic comparator is used to calculate the correspondences among the concepts and relations, represented as attributes of both graphs. “Thus, a solution to the graph matching problem represents an association between the concepts maps compared” (De Souza et al. 2008). The difficulty is the method to find the similarities of two graphs." To do this, concept maps CM1 and CM2 are represented as graphs G1 and G2 and their attributes (concepts and relations) are extracted and compared by a semantic comparator to construct the node and edge similarity matrices". More details of the algorithm can be found in: (De Souza et al. 2008). CmapTools (v.4x) has a Compare-to-Cmap feature in the Tools menu that allows people to do the comparisons (Clariana et al. 2006). An alternate approach for comparing multiple concept maps is a software tool called Pathfinder Knowledge Network Organizing Tool (KNOT; Schvaneveldt, 1990) that has analyses capability including simultaneous comparisons between multiple concept maps (Clariana et al. 2006 ) .

With these definitions one of the above techniques can be used to compare two concept maps in our algorithms. We suggest using the CMap tool as it is well known and its efficiency has been proven.

Matching process: In this part the words in the concept map and the phrases related to the tags for every user is compared with each other. This is done to know what should be recommended to the users. If tags are used in the concept maps, but are not in relationship with each other, then it is useful to suggest a concept map in which these tags are related. Otherwise, a concept map composed of more tags or a different concept map is proposed.

The algorithm for this part can be separated into three different filters. We can assume this recommender system as a collaborative filter recommender system. We briefly explain about each filter and then suggest our proposed algorithm.

Filter 1: In the first filter, we extract the tags and concept maps of user u as input and then the tags that couldn't be related in the concept map are filtered out. As output we find the concept maps of other users who have implemented these tags.

Filter 2: In the second filter, we have those concept maps which contain the unknown tags for user u. We filter out the most similar concept maps to the user u's concept map with the algorithm discussed in 3.2.5


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Filter 3: In the last filter, we have the most similar concept maps as input. We relate these concept maps with their constructors. Finally we can filter out tags most similar to the user's tags according to 3.2.4. So as the final output we have concept maps, tags and users who are most similar to one another.

An example of the utility of these three filters can be seen in figure 2. User u’s tags and concept map in topic english

Similar concept maps

Similar tags

Figure 10. Example of Proposed Algorithm In the following section we discuss the algorithm which utilizes three mentioned

above filters to achieve the best recommendation for users. Give final recommendations to users: As mentioned in the last line of algorithm 1

we recommend similar concept maps, tags and similar users to the user. In figure 3 we have placed a snapshot of our work. It's a system that depicts our

proposed algorithm. As it can be seen in the concept map link, an illustration of the user's concept map is presented. The tags related to the concept map are also provided below the map. Our algorithm is launched and the most similar concept maps are recommended. This recommendation makes use of the user's tags for a more efficient recommendation as discussed in section 3.1. In our belief these recommendations (both concept maps and tags) can guide the learner for a better knowledge in a specific topic.


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Algorithm 1. Hybrid Recommendation Algorithm : The set of tags that the user u couldn't implement in his concept map : The Concept Maps that have implemented tag i

: Friends that could implement tag i in his concept map : Other tags that the j has implemented in his Concept map that i has not

For each user u //Compare tags to Concept maps for the user u

= extract tags that are not implemented in the Concept Map of the user u For each tag i in //search for Concept Maps in the system that have implemented t = the Concept Maps that have implemented i For each concept map c in Find the most similar concept map to the user u's concept map //this has been done in part 3.2.5; we can Easley match with those found in 3.2.5 =the person who has implemented i Find similarity between u and according to 3.2.4 : = tags that the person has implemented in his Concept map that u hasn't Recommend , , to u

Give final recommendations to users: As mentioned in the last line of algorithm 1 we recommend similar concept maps, tags and similar users to the user.

In figure 3 we have placed a snapshot of our work. It's a system that depicts our proposed algorithm. As it can be seen in the concept map link, an illustration of the user's concept map is presented. The tags related to the concept map are also provided below the map. Our algorithm is launched and the most similar concept maps are recommended. This recommendation makes use of the user's tags for a more efficient recommendation as discussed in section 3.1. In our belief these recommendations (both concept maps and tags) can guide the learner for a better knowledge in a specific topic.

Figure 11. Prototype

Recommendation


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4 Conclusion and Future works We proposed an original algorithm for recommender systems which utilizes collaborative filtering and uses the user's tags and concept maps as its input. The algorithm has three stages for filtering out the best recommendations. In the first filter we take out the concept maps that have implemented the tags that have not been related in a users concept map. In the second filter the most similar concept maps are extracted and finally in the last filter we match the tag space of the users to suggest the most similar tags for the user.

For future work we would experiment our results with suitable data. The data for the tags can be provided from the social bookmarking systems such as delicious.com or last.fm.com and for the concept map collection we can ask from the users to illustrate a concept map of their knowledge. Also we can ask the user if he wants to be recommended the most similar concept maps to him or the most different concept maps compared to his own. This is because the user might want to observe other users opinions about a particular topic and concept.

REFERENCES

Ae-Ttie Ji, Cheol Yeon , Heung-Nam Kim ,Geun-Sik Jo (2007) ,Collaborative Tagging in Recommender Systems, Springer Berlin / Heidelberg, AI: Advances in Artificial Intelligence, 0302-9743 (Print) 1611-3349 (Online) Volume 4830/2007

Balabanovic, M., and Shoham, Y. (1997) Content-based, collaborative recommendation. Communications of the ACM. 40(3):67-72,

Robin Burke (2000), Knowledge-based recommender systems, In Encyclopedia of Library and Information Systems, Vol. 69

Roy Clariana, Ravinder Koul, and Kristen Albright (2006), Using Pathfinder Knot Analytic Tools For Comparing And Combining Concept Maps

David B. Leake, Ana Maguitman, Thomas Reichherzer,( 2003) Topic Extraction and Extension to Support Concept Mapping, page 325- 329, FLAIRS

David Leake, Ana Maguitman, Thomas Reichherzer , Alberto Cañas, Marco Carvalho, Marco Arguedas, Tom Eskridge,( 2004) “Googling” From A Concept Map: Towards Automatic Concept-Map-Based Query Formation, Proc. Of The First Int. Conference On Concept Mapping, Pamplona, Spain

F. S. L. De Souza, M. C. S. Boeres, D. Cury, C. S. De Menezes, G. Carlesso,( 2008) An Approach To Comparison Of Concept Maps Represented By Graphs, Proc. of the Third Int. Conference on Concept Mapping, Tallinn, Estonia & Helsinki, Finland

Herlocker, J.L, Konstan, J.A., Riedl, J. (2000): Explaining Collaborative Filtering Recommendations.In: Procs of ACM Conf. on Computer Supported Cooperative Work, pp. 241–250

Sigma On Kee Lee, Andy Hon Wai Chun,(2007), Automatic Tag Recommendation for the Web 2.0 Blogosphere Using Collaborative Tagging and Hybrid ANN Semantic Structures , Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6 , Volume 6,

Osmar R. Za¨ıane, (2002) Building a Recommender Agent for e-Learning Systems, Proceedings of the International Conference on Computers in Education, December, IEEE Computer Society

Resnick, P.; Iacovou, N.; Suchak, M,; Bergstorm, P.; and Riedl, J.( 1994) GroupLens: An Open Arch for Collaborative Filtering of Netnews, In Proc. ACM Conf. on Computer Supported Cooperative Work, 175-18.

Matt Riordan, Tom Marcais, ”Moodle An electronic classroom” Shardanand, U., and Maes, P.( 1995) Social Information Filtering: Algorithms for Automating “Word of

Mouth”, In Proc. ACM CHI’95 Conf., 210-217. Simone C. O. Conceição, Carrie Ann Desnoyers, Maria Julia Baldor,( 2008) Individual Construction Of

Knowledge In An Online Community Through Concept Maps, Proc. Of The Third Int. Conference On Concept Mapping, Tallinn, Estonia & Helsinki, Finland

Alejandro Valerio, David B. Leake,, Alberto J. Cañas(2008), Automatic Classification Of Concept Maps Based On A Topological Taxonomy And Its Application To Studying Features Of Human-Built Maps, Proc. Of The Third Int. Conference On Concept Mapping, Tallinn, Estonia & Helsinki, Finland

Ranking Concept Maps and Tags to Differentiate the Subject Experts in a Collaborative E-Learning Environment

Ahmad A. Kardan, Fatemeh Hendijanifard, Solmaz Abbaspour

Advanced E-Learning Technology Laboratory

Department of Computer Engineering and Information Technology Amirkabir University of Technology, Tehran, Iran

Email: aakardan, hendijani, [email protected]

Abstract Members of a collaborative learning environment need to refer to the subject experts. Therefore, it is necessary to identify the subject experts and to introduce them to the other members. To achieve this goal, one approach is to make use of concept map evaluation by means of ranking methods. Another approach is to utilize tagging methods for finding subject experts in a collaborative learning environment. In this article a new approach for estimating the knowledge level of the members in a virtual environment is introduced, which is based on the concept mapping and tagging. In construction of the concept maps, concepts could be linked to any type of related resources. The labels associated to these links could be assumed as tags for those resources. Therefore, tagging methods could be used as a measure for ranking the quality of the resources and the expertise of members. In the proposed method, four parameters are considered for ranking the subject experts: concept map ranking, tag ranking, tag and resource relevancy, and the relation between the number of tags and the number of concepts. This paper presents the required algorithms which examine these parameters to determine the subject experts. These algorithms and the evaluation method will be discussed in detail.

Keywords: Elearning, Concept map, tag, ranking method, collaborating environment

1 Introduction It can be not easy to get a satisfactory answer to a problem by using search engines. Instead, one may prefer to find and ask someone who has related expertise; online communities and collaborative learning environments have emerged as one of the most important places for people to seek advice or help (Jun Zhang, Mark S. Ackerman & Lada Adamic, 2007). Thus a common issue in collaborative learning environments is finding experts. Some works have been done on ranking the knowledge of people with the help of concept maps, or utilizing tagging methods to identify subject experts in a collaborative learning environment.

Concept map is a graphical representation of a human’s understandings of a domain of knowledge. Concept maps represent this understanding by using a two-dimensional network in which nodes correspond to concepts and links demonstrate concept relationships. In a concept map, concepts are the labels used to refer to objects and linking phrases (the text on the links) are usually verbs (Alejandro Valerio et al, 2008).


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Concept mapping is used to enable individuals to make new knowledge, externalize knowledge, share and compare knowledge. Given that each person’s understanding of a domain is different, even on the same topic, the maps constructed by everyone are different, reflecting their personal knowledge structures (Alejandro Valerio et al, 2008).

Another means that is used in collaborative environment is tagging. Collaborative tagging systems provide web users a new means of organizing and sharing resources such as bookmarks on the Web (M. G. Noll & C. Meinel, 2008). Such systems also allow users to search for documents relevant to a particular topic or for other users who are experts in a particular domain. However, identifying relevant documents and knowledgeable users is not a trivial task. Thus new approaches by tags are used to rank resources and users (R. Wetzker & C. Zimmermann & C. Bauckhage 2008).

In this article a new approach for approximating knowledge of members in such environments is introduced. In this approach concept maps and tagging methods are applied to identify experts in particular subjects and is discussed in detail in the following sections. Section 2 of this article includes related works. System architecture with details of each stage is represented in section 3. And the last section is about evaluation and future works.

2 Related works Tag Ranking Methods: “Studies in psychology have shown that experts involve in the ability to select the most relevant information to achieve a goal” (P. J. Feltovich et al., 2006). In the context of collaborative tagging, users assign tags to resources to facilitate retrieval of resources. “Therefore, it is believed that an expert should be someone who not only has a large collection of documents annotated with a particular tag, but tends to add high quality documents to their collections. In other words, there is a relationship between the expertise of a user and the quality of a document.” In tag ranking methods, usually spammers are omitted to find users that have used high quality tags and rank documents. Koutrika et al. (2007) are the first to discuss methods of tackling spamming activities in collaborative tagging. There are also proposals for detecting spammers in tagging systems based on machine learning approaches (A. Madkour et al., 2008; R. Krestel & L. Chen, 2008). In (Michael G. Noll et al., 2009) the proposed algorithm named SPEAR in addition to demoting spammers in the ranked list of users instead of detecting their presence; it finds experts. They believe that different types of methods, including detection, demotion, and also prevention is complementary in tackling spammers (P. Heymann et al., 2007).

Concept Maps Ranking Methods: “Despite the variety of concept maps that arise from the differences among map builders, some maps can be considered “better” than others, based on a variety of criteria. One concept map could show a “deeper understanding” of a topic than another, perhaps reflecting that the first was constructed by an expert and the second by a novice” (Alejandro Valerio et al, 2008). Therefore different methods have been done on evaluating concept maps.

An evaluation may involve making qualitative and/or quantitative remarks (John R. Mcclure et al., 1999). Topological features and semantic features are two features that assess the quality of a concept map (Alejandro Valerio et al, 2008).


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Qualitative relational methods assess the accuracy of each proposition; quantitative structural methods score the valid elements in comparison to a criterion map. “Ruiz-Primo pointed to three scoring systems: (1) of proposition accuracy, (2) of convergence with a criterion map and (3) of salience which is the “proportion of valid propositions out of all the propositions in the student's map”. Ruiz-Primo and colleagues found correlations between this convergence score of construct-a-map procedures and learners’ explanatory skills which gives evidence, that concept mapping assessment is “in fact measuring what is claimed”.” Mc Clure and colleagues compared holistic, relational and structural scoring methods without and with the use of a master map unveiling a high reliability for the latter (Steffen Schaal, 2008). Some other methods which were evaluated are: holistic, holistic with master map, relational, relational with master map, structural, and structural with master map (John R. Mcclure et al., 1999). In (Steffen Schaal, 2008) structural attributes of concept maps are scored. The relevant structural attributes were the ‘volume’ of a concept map, the ‘ruggedness’ which is the division of a concept map into un-connected sub-maps and the amount of accurate propositions in relation to the volume (Steffen Schaal, 2008).

3 System Architecture

3.1 System Outline

In the proposed system shown in figure 1, learners in a collaborative environment construct concept maps to show their knowledge for a specific subject. Learners can link resources to their maps to further explain their contents (concepts or linking phrases). Concepts associated to these links are single words or in the form of a phrase, and we can assume these concepts as tags drawn on the resources. Tags for any resource show how much the learner understood the main concepts of that source. As stated in (R. Wetzker & C. Zimmermann & C. Bauckhage, 2008) “the simplest way to assess the expertise of a user is by the number of times he has used a tag (or a set of tags) on some documents. However, this does not take into consideration the facts that quantity does not imply quality, and that there exist spammers who indiscriminately tag a large number of documents” (R. Wetzker & C. Zimmermann & C. Bauckhage, 2008). It is believed that an expert should be someone who tends to add to his collection high quality documents. “Thus there is a relationship of mutual support between the expertise of a user and the quality of a document” (A. Madkour et al., 2008).

Consequently tagging methods are used for knowledge evaluation and expert identification. To achieve this, system extracts the linked concepts – tags – from the maps for each learner, and to check relevancy of tags to the resources, compares tags with the keywords of resources. In this way quality of tags are ensured. From this part, at the first stage the score of tags will be achieve; and in the second stage a concept map scoring system will be applied on the maps. Therefore the Knowledge ranking of the learners is achieved from these two steps and then the subject experts are introduced. Details of each part are followed in section 3.2.


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Figure 1. System Architecture

3.2 Stages in Detail Tag – Keyword Matching: In this module, the linked concepts of every concept map are extracted. The list of these concepts is considered as a set of tags for each map, T=

. The keywords for each content resource are determined. Hence a keyword set K= will be attained. Tags T and keywords K are checked to investigate the equivalency between them. WordNet is used to go with the keywords and tags. WordNet is a lexical database that groups English words into sets of synonyms called synsets, provides short, general definitions, and records the various semantic relations between these synonym sets. This matching is used in the next stage for ranking tags of each concept map.

Tag Ranking: In this part, two parameters for tag ranking are applied. The first

parameter is the similarity of tags to the keywords. For obtaining this similarity, tag set T for a map is used to compare with keyword set K with the help of WordNet. The result will give a grade to the tags and is shown in the algorithm1.

It is remarkable to note that the most popular tags are considered too. These tags are attached to a resource by many users. So these words are added to the keyword set K.


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Algorithm1. Determining parameter

//Key word set of all content resources: K= //Tag set of concept map i: =

//Set of all concept maps: C= For each concept map c

For each tag in Compare tag with keywords in K with help of WordNet //use one of the below functions to grade the tag

If tag is exactly one of one of the keywords in K then s1=α Else if tag is synonym for one of the keywords in K then s1=β Else if tag is hyponym for one of the keywords in K then s1=Ω Else s1=ζ

// is the similarity of tags and keywords and shows score for this //similarity in concept map ci.

//End

The second factor for ranking tags is leveraging. Tags are classified to specific,

general and not related tags. This classification and grade for each class is determined by an expert in that subject. The result grade is used to rank tags of concept maps. Here is the algorithm for this part:

Algorithm2. Determining parameter

//Tag set of each concept map ci: =

//Set of all concept maps: C=

//Categories of tags determined by expert: =

For each concept map c

For each tag in Determine each tag belongs to which category of Cat //use one of the below functions to grade the tag

If tag is specific then s2= γ Else if tag is general then s2=δ Else s2=η

// shows how specific or general the tags in set of concept map ci are.

//End

Parameter is considered as a weight for for every concept map. It shows how

general or specific the concepts are, and this is an important factor for recognizing


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knowledge of people in a particular subject. Hence total rank for the tags is calculated as below:

• : number of tags in concept map i

• : for every concept map ci, is summation of * for

each tag in set , divided by number of tags in a concept map.

[1]

Note: grades for and in each if can be determined by comparing with what experts usually use.

Concept Map Ranking: A reliable knowledge structure is necessary for conceptual

understanding. Thus, “the interrelationship of concepts is seen as a fundamental attribute of knowledge” (Steffen Schaal, 2008). Of course, the semantic content is always more important than the topological structure, but a “well structured” concept map is considered better than a badly structured map, even if their contents are “equivalent” (Alejandro Valerio et al, 2008). The topological taxonomy classifies concept maps into seven levels of increasing structural complexity. In the taxonomy, five features are used to describe the structure of a concept map: “the existence of hierarchical structure, size of concept labels, presence of linking phrases, number of branching points, and number of cross links. Values for these features determine the level of complexity” (Alejandro Valerio et al, 2008).

In this part, a topological classifier method described in (Alejandro Valerio et al, 2008) is used to categorize concept maps into six levels of expertise. Level -1 defines the default level. The classification is determined by checking the specifications described in table 1 for concept maps.

Table 1. Required conditions for classification of concept maps

(Alejandro Valerio et al, 2008)

Level # Conditions by level as

indicated in Canas, Novak et al. (2006)

Conditions evaluated by to classify concept map M, which has concept c and linking

phrase l as the nodes of M.

Level -1 No conditions (default)

Level 0

At least 4 connected concepts Mostly long concept labels Empty linking-phrases 0 to 1 branching points

(default) (default) (default)

Level 1

More concepts than long concept labels Half or more missing linking-phrases 0 to 1 branching points

(default)

(default)

Level 2 More concepts than long concept labels Less than half missing linking-

(checked at Level 1)


314

Level # Conditions by level as

indicated in Canas, Novak et

al. (2006)

Conditions evaluated by to classify concept map M, which has concept c and linking

phrase l as the nodes of M.

phrases At least 2 branching points

Level 3

No long concept labels No linking-phrases missing At least 3 branching points Less than 3 hierarchy levels

(default)

Level 4

No long concept labels No linking-phrases missing At least 5 branching points At least 3 hierarchy levels

(checked at Level 3) (checked at Level 3)

Level 5

No long concept labels No linking-phrases missing At least 5 branching points At least 3 hierarchy levels At least 1 cross-link

(checked at Level 3) (checked at Level 3) (checked at Level 4) (checked at Level 4)

Level 6

No long concept labels No linking-phrases missing At least 7 branching points At least 3 hierarchy levels At least 3 cross-links

(checked at Level 3) (checked at Level 3)

(checked at Level 4)

Conditions labeled with (default) are met if the map fails a condition of a following level. Conditions labeled with (checked at Level N) are revised at a previous level.

Experts Knowledge Ranking: In part three of section 3.2 concept maps are ranked and each map is assigned to a class shown in table 1. Each group of maps in every level of table 1 will be classified again with regard to the rank of tags. Another parameter should be considered here: the ratio of number of tags in the whole map. As stated before, the simplest way to assess the expertise of a user is by the number of times he has used a tag. Thus, this parameter shows how much a person is expertise in one subject and how many resources one has used for different aspects of his knowledge. The quality of tags is considered in the tag rankings. The proportion of tags to the whole map is shown in formula (2):

• m= number of tags

• n= number of nodes (concepts) in the concept map

[2]

With the help of from formula (2) and due to the previous grades of concept maps and tags for each member, experts in this learning environment could be introduced. So members from the top level with the greatest tag grades and greatest will be introduced as subject experts.


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4 Evaluation and Future Works For evaluation of this work, a group of concept maps which are linked to some text resources can be used. By applying the algorithms on each map and determining the grades, experts will be determined. In some concept map repositories, such as repositories of CmapTools, there are expert and novice concept maps. With the help of this information and comparing the results of algorithms, system will be evaluated.

For future works we can determine and verify quantities of α, β, Ω, γ, δ and η during different experiments to use in algorithms of part two of section 3.2.

In addition, the quotient in formula (2) is believed to be different in the maps related to the experts and usual maps. This parameter can be certified by analyzing maps constructed by experts, such as professors’ maps.

Considering for experts maps as a threshold, another work is to change map levels pointed in table 1, with regard to . For example check validity of stage amending of one’s map from level n to level n+1 if is θ percent of this threshold.

RESOURCES

A. Madkour, T. Hefni, A. Hefny, and K. S. Refaat (2008), Using semantic features to detect spamming in

social bookmarking systems. Proc. of ECML PKDD Discovery Challenge Workshop, Belgium Alejandro Valerio, David B. Leake,, Alberto J. Cañas (2008), Automatic Classification Of Concept Maps

Based On A Topological Taxonomy And Its Application To Studying Features Of Human-Built Maps. Proc. of The Third Int. Conference On Concept Mapping, Tallinn, Estonia & Helsinki, Finland

G. Koutrika, F. A. E_endi, Z. Gyongyi, P. Heymann, and H. Garcia-Molina (2007), Combating spam in tagging systems. Proc. of Int'l Workshop on Adversarial information retrieval on the web, pages 57-64

John R. Mcclure, Brian Sonak, Hoi K. Suen (1999), Concept Map Assessment Of Classroom Learning: Reliability, Validity, And Logistical Practicality. Journal Of Research In Science Teaching, Vol. 36, No. 4, 475–492

Jun Zhang, Mark S. Ackerman, Lada Adamic (2007), Expertise Networks in Online Communities: Structure and Algorithms. WWW 2007, Banff, Alberta, Canada

M. G. Noll, C. Meinel (2008), Exploring social annotations for web document classi_cation. Proc. of ACM Symposium on Applied Computing, pages 2315-2320, Fortaleza, Brazil

Michael G. Noll, Ching-man Au Yeung, Nicholas Gibbins, Christoph Meinel, Nigel Shadbolt (2009), Telling Experts from Spammers:Expertise Ranking in Folksonomies. Proc. of the 32nd international ACM SIGIR conference on Research and development in information retrieval

P. Heymann, G. Koutrika, and H. Garcia-Molina (2007), Fighting spam on social web sites: A survey of approaches and future challenges. IEEE Internet Computing, 11(6):36 -45

P. J. Feltovich, M. J. Prietula, K. A. Ericsson (2006), Studies of expertise from psychological perspectives. The Cambridge Handbook of Expertise and Expert Performance, pages 41-68. Cambridge University Press, USA

R. Krestel, L. Chen (2008), Using co-occurrence of tags and resources to identify spammers. In Proceedings of ECML PKDD Discovery Challenge Workshop, collocated with ECML/PKDD

R. Wetzker, C. Zimmermann, C. Bauckhage (2008), Analyzing social bookmarking systems: A del.icio.us cookbook. Proc. of Mining Social Data Workshop, collocated with ECAI, pages 26-30

Steffen Schaal (2008), Concept Mapping In Science Education Assessment: An Approach To Computer-Supported Achievement Tests In An Interdisciplinary Hypermedia Learning Environment. Proc. of The Third Int. Conference On Concept Mapping, Tallinn, Estonia & Helsinki, Finland

Validation of Messages in Discussion Groups Using the Learner Model: An Approach to Enhance Trustworthiness

Ahmad A.Kardan, Mehdi Garakani, Somayeh Modaberi

Department of Computer Engineering and Information Technology

Amirkabir University of Technology. Tehran, Iran E-mail: [email protected]

Abstract Discussion groups are collaborative tools in the context of e-learning. They can be used for several purposes, including a simple question/answer mechanism or achieving higher phases of critical thinking and knowledge construction. Evidently, in these cases the common attribute is the quality of the opinions expressed in the messages. Thus, there should be a mechanism to assess the quality and validity of the messages being transmitted among the participants.. Related works in this domain have so far focused on network analysis using quantitative methods to identify experts as the source of valid messages. However, since these methods calculate the expertise level of a user based on the number of messages being sent or received, an expert user with low number of transmitted messages would not be identified as an expert. In this paper, we introduce a novel approach which is qualitative and uses a learner model for scoring and validating the messages. In the proposed model, every message is mapped to the defined fragments and according to the learner knowledge in the corresponding fragment. A score is then assigned to each message that could be used to establish a trust mechanism in discussion groups.

Keywords: Discussion groups, Learner model, Collaborative learning, Trust

1. Introduction Collaborative learning is an umbrella term for a variety of approaches in education that involve joint intellectual effort by students or students and teachers (Smith and MacGregor, 1992). In the context of Learning Management Systems, collaborative learning refers to a collection of tools which learners can use to assist, or be assisted by others. One of these tools is discussion groups that can be used for several purposes, such as a simple question/answer mechanism or achieving higher phases of critical thinking and knowledge construction. Discussion groups offer important advantages in the field of e-learning such as facilitating self-directed learning due to their time and place-independent nature (Harasion 1990; Murphy and Colman, 2004), and the learning that occurs in a distributed environment (Tennet and Hyland, 2004). However, there are some challenges in use of discussion groups; one common challenge is related to the message trustworthiness (Kim and Wah, 2007). In order to establish trust in massages, there should be a way to assess the quality and validity of the messages being transmitted between the participants. Related works in this domain have so far, focused on network


317

analysis using quantitative methods to find experts as the source of valid messages. In this paper, we introduce a novel approach which is qualitative and uses a learner model to score and validate messages. A learner model presents the knowledge about the learner, either explicitly or implicitly encoded, that is used by the system to improve interaction and adoption (Kass and Finin, 1998). Each learner model has five popular and useful features: the learner knowledge, interests, goals, background, and individual traits (Brusilovsky and Millan, 2007). Since knowledge is the most important feature in a learner model (Brusilovsky, 1996), in this paper, a learner model is constructed based on the learner knowledge using an overlay model approach. The overlay model is the most popular form of a structural knowledge model. “The purpose of the overlay model is to represent an individual user's knowledge as a subset of the domain model, which reflects the expert-level knowledge of the subject” (Brusilovsky and Millan, 2007). This paper is organized as follows. Related works will be reviewed in section 2. In section 3, we will describe our approach to message validation. Conclusion and future work will be discussed in section 4. 2. Related works Message verification is a significant challenge in discussion groups. Previous research on this topic can be placed into two main categories. The first category consists of expertise finder systems that have been surveyed in a series of studies (e.g., Streeter and Lochbaum, 1988; Krulwich and Burkey, 1996; Ackerman and McDonald, 1996; Yenta and Foner, 1997), and most recent commercial systems from Tacit and Microsoft. Most of these systems employ modern information retrieval techniques to identify expertise. A term vector is usually used to express each person’s expertise in a discussion group which is applied later for matching expertise queries using standard IR techniques. Since the result is usually a list of related people with no ranking order, it is difficult to distinguish the relative level of expertise for each person. Such a list only shows that a person knows about a topic, but does not show how much is known. The second category includes works such as Campbell et al (2003) and Dom et al (2003) that try to improve expertise finder systems (in category one), and reduce their problems. In these studies graph-based ranking algorithms in addition to content analysis are used to rank users’ expertise levels. The results of these studies show that a graph-based algorithm effectively extracts more information than is found in content alone. Zhang, Ackerman and Adamic (2007) extend this work for grater networks. In general, the limitation of the works in this category is assessing the expertise level of a user based on a calculation of the number of messages being sent or received. Thus, a expert user with low number of transmitted messages would not be identified as an expert. In the next section, we discuss our proposed novel approach which estimates the validity of the messages being posted in discussion groups.

3. Message Validation Discussion groups are such places where participants can express their ideas; yet, there is no way to determine how valid and trustworthy the expressed statements are. In this


318

section, we discuss the proposed process of message validation in a learner knowledge model which can be used in discussion groups and similar environments to enhance trustworthiness. 3.1 Learner Model Modification As mentioned before, the learner knowledge model has to be modified in order to be used for message validation. The proposed modification consists of assigning several tags to each context fragment in the learner knowledge model. These tags, which are used to describe each context fragment in the best possible manner, should be defined precisely by the domain experts. Figure 1 demonstrates the proposed modification.

Former Learner Knowledge Model Modified Learner Knowledge Model Fragments Level Fragments Tags Level Fragment 1 8 Fragment 1 Tag 1, Tag 2, Tag 3 8 Fragment 2 2 Fragment 2 Tag 1, Tag 4, Tag 5 2 Fragment 3 6 Fragment 3 Tag 2, Tag 4, Tag 7 6

Figure 1. Learner Knowledge Model Modification As shown in figure 1, some tags are assigned to more than one fragment. This is because, the fragment concepts may overlap with each other For example, “Fragment 1” and “Fragment 2” may indicate the learner’s knowledge in the fields of “Perl Programming Language” and “Python Programming Language” respectively. Therefore, these fragments are indicating two distinct subjects; however, they are both programming language and have this attribute in common. So, they are both tagged with “Tag 1” which could be “Programming”. 3.2 Correlating a Message to Knowledge Fragments Having learner knowledge model modified, the next step is to determine the subject of a specific message and correlate the message to related fragments according to fragments’ tags. There are several methods to determine the subject of a message; however, in this paper TF-IDF method is used. TF(w) is indicating the Term Frequencies, which is the number of occurrences of w and IDF(w) is indicating the Inverse Document Frequencies which weaken the influence of terms that occur very frequently in the whole collection of messages, e.g. the term “the”. So, the following term will be calculated for every word that appears in the message.

[1] )()( wIDFwTFS ×=

Where [2] wcontainthatMessages

MessageswIDF

___#

#log)( =

There could be a threshold to select n words with the highest TF-IDF quantities (S values) as the Message Representative Tags (MRT). MRTs will present the subject of a message. They help to understand what the message is all about. Therefore, MRTs will be matched with fragments’ tags in the learner knowledge model to determine whether the learner knows about what has been stated in the message, or not.


319

3.3 Scoring the Messages After a message is correlated to several fragments, it is time to score the message according to the level of knowledge the learner has acquired in those fragments. Before getting to this step, the S values calculated for every word of a message should become normalized. The normalized MRT is expressed in equation [3]:

[3] n

ii MRTMRTMRT

MRTMRTNormalized

+++=

..._

21 Having MRT values normalized, it is time to score the message based on the learner’s knowledge in each fragment. Each MRT value should be assigned to exactly the same, or synonym tags (e.g., WordNet could be used) which exist for each knowledge fragment. The message’s score is calculated from equation [4].

[4] numMaxk

FragmentofLevelKnowledgeTag

ScoreMessage i jiij

×

×

=∑∑ ___

_

In this equation, i is the number of fragments, j is the number of tags related to each fragment, MaxK is maximum level of knowledge for each fragment and num is the number of fragments that have at least one tag in MRT set, and its value is specified. To obtain a better result, the fragments, whose sum of the tag values are less than a predefined amount, could be eliminated from calculations. In the next subsection, an example is presented to shed more light on the subject. 3.4 Example In this example we assume that the message has been posted to a programming discussion group. After calculating the S value for all the words in the posted message, “perl”, “loop” and “condition” are three words that occur most frequently and their S values are 1.5, 2.7 and 3.3 respectively. The normalization process is as follow:

2.03.37.25.1

5.1_ 1 =

++=MRTNormalized

36.03.37.25.1

7.2_ 2 =

++=MRTNormalized

44.03.37.25.1

3.3_ 1 =

++=MRTNormalized

Modified Learner Knowledge Model Fragments Tags Level Fragment 1 perl, loop, notation 8/10 Fragment 2 perl, while, notation 9/10 Fragment 3 recursive, algorithm, structure 2/10 Fragment 4 java, loop, condition 7/10

Figure 2. Learner Knowledge Model Example


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There are 3 fragments that include at least one tag from the MRT set. So, only these three rows will be counted for scoring the message. Also, the sum of tag values for fragment 2 is less than the predefined threshold (e.g., 50% here). Consequently, this fragment of knowledge will be eliminated from the calculation. The score calculated for this message will be as follows:

5.0210

78.0856.0

___

_

≈×

×+×=

×

×

=∑∑

numMaxk

FragmentofLevelKnowledgeTag

ScoreMessage i jiij

Hence, the more the calculated value is, the more trustworthy and valid the message is. 4. Conclusion and Future Work In this paper we addressed the existing problem with trustworthiness of a message in discussion groups and other similar environments. We proposed a novel approach using the learner knowledge model to estimate the validity of a message based on the expressed statements and ideas in the message. In order to perform estimation, it was suggested that it is necessary to modify the learner knowledge model and to try to relate every message to the corresponding fragments in the learner knowledge model. We used tagging to bring up mapping, and based on each fragment level of knowledge we scored messages with a number between 0 and 1. Messages with higher scores are regarded as more valid and trustworthy. Our current objective is to implement this mechanism in a real environment and to seek the best possible results by adjusting the thresholds.

REFERENCES

Brusilovsky, P. (1996): Adaptive hypermedia, an attempt to analyze and generalize. In: Brusilovsky, P., Kommers, P., Streitz, N. (eds.): Multimedia, Hypermedia, and Virtual Reality. Lecture Notes in Computer Science, Vol. 1077. Springer-Verlag, Berlin 288-304.

Brusilovsky, P. and Millán, E., (2007): User Models for Adaptive Hypermedia and Adaptive Educational Systems. The Adaptive Web, LNCS 4321, pp. 3 – 53.

Campbell, C.S., Maglio, P.P., Cozzi, A. and Dom, B., (2003): Expertise identification using email communications. In the twelfth international conference on Information and knowledge management, New Orleans, LA, 528-231.

Dom, B., Eiron, I., Cozzi, A. and Zhang, Y., Graph-based ranking algorithms for e-mail expertise analysis. In DMKD, New York, NY, 2003, ACM Press, 42-48.

Foner, L.N., (1997): Yenta: a multi-agent, referral-based matchmaking system. In Proceedings of Agents '97, ACM Press, Marina del Rey, CA, 301-307

Harasim, L. (Ed.). (1990). On-line education: Perspectives on a new invironment. New York: Praeger. Kass, R. and Finim, T., (1998): Modeling the User in Natural Language Systems. Computational Linguistics,

14, 3, 2. Kim, T. L. S and Wah, W. K, (2007): Asynchronous Electronic Discussion Group: Analysis of Postings and

Perception of In-service Teachers. Turkish Online Journal of Distance Education-TOJDE 8, 1, 2, 3. Krulwich, B. and Burkey, C., (1996): ContactFinder agent: answering bulletin board questions with referrals.

In the 13th National Conference on Artificial Intelligence, Portland, OR, 10-15


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Murphy, E., & Coleman, E. (2004). Graduate students’ experiences of challenges in online asynchronous discussions. Canadian Journal of Learning and echnology, 30(2). www.cjlt.ca/content/vol30.2/cjlt30-2_art-2.html

Smith, B. L., and MacGregor, J. T. (1992): What Is Collaborative Learning. In Streeter, L. and Lochbaum, K., (1988): Who Knows: A System Based on Automatic Representation of

Semantic Structure. In Proceedings of RIAO, 380-388 Goodsell, A., Maher M., Tinto V., Smith, B. L., and MacGregor, J. T. : Collaborative Learning: A

Sourcebook for Higher Education. National Center on Postsecondary Teaching, Learning, and Assessment at Pennsylvania State University.

Ackerman, M.S. and McDonald, (1996):Answer Garden 2:merging organizational memory with collaborative help. In Proceedings of CSCW '96, Boston, MA, ACM Press, 97-105

Tennet, B., & Hyland, P. (2004). The WebCT discussion list and how it is perceived. Turkish Online Journal of Distance Education, 5(3). http://tojde.anadolu.edu.tr/tojde15/articles/tennet.htm

Zhang, J., Ackerman, M. S., Adamic, L., (2007): Expertise Networks in Online Communities: Structure and Algorithms. In WWW '07: Proceedings of the 16th international conference on World Wide Web, 221-230.

Using Genetic Algorithms to Increase the Quality of University Research Management

Florentina Alina Chircu

Department of Informatics, Petroleum–Gas University of Ploiesti, Romania


Abstract In the context of global change and institutional diversification, the research disciplines are developing and demands for research results are changing and growing. Institutions or departments with high performance in the research activity are populated by individuals with a high career motivation and which are willing to assume research and to cooperate with others. In these circumstances, inter-human relationships have an important role in the success of research projects that require teamwork. In this paper, the authoress presents an implementation of genetic algorithm, aiming to increase the quality of university research management. With this application, she intends to identify the most suitable combination for a research team consisting of members from an university department. The result has to be composed of people which can work well together, putting emphasis on achieving a more productive team.

Keywords: Research management, Artificial intelligence, Genetic algorithms.

1 Introduction

In the perspective of changes that have occurred in the university management field, one can notice the pronounced development of the research discipline. At the same time, the demands for research application and results are growing and changing. To fulfil these requirements, a method to optimally use all the resources (financial, human and physical) has to be found [2].

Higher education institutes are trying to encourage the research field and the development of researchers’ teams. Nevertheless, it is to be noticed that the success of such teams depends primarily on each individual part, beyond the other secondary factors that influence it. Departments with notable results and high performance in the research activity can be described as teams composed of individuals with a high career motivation and which are willing to assume research and to cooperate with others [2]. In these circumstances, inter-human relationships have an important role in the success of research projects that require teamwork

In this paper, the authoress presents an implementation of genetic algorithm which aims to increase the quality of university research management. With this application, she intends to identify the most suitable combination for a research team consisting of members from a university department. The result has to be composed of people which can work well together, putting emphasis on achieving a more productive team.


323

2 Genetic Algorithm Genetic Algorithms are part of evolutionary algorithms, representing an area of artificial intelligence that has known a great development. They represent an evolutionary search technique used with the purpose of identifying an approximate solution for optimization and search problems. These algorithms make use of techniques inspired by evolutionary biology, such as inheritance, mutation, selection and crossover (also called recombination) [1].

Genetic Algorithms are implemented as computer simulations. They are represented as a population of abstract representation (called chromosomes) of candidate solutions (called individuals) to an optimization problem evolves toward better solutions [1].

Solution evolves to the right answer following the rules built on evolutionary concepts:

• Survival of the strongest individuals; • Adaptation to environment; • Species evolution.

The components of a genetic algorithm are: • A method to represent solutions as chromosomes; • A method to generate initial populations of potential solutions; • Fitness evaluation function; • Runtime parameters (population size, crossover possibility, mutation

probability and evolution interval). This algorithm starts with a complete or partial randomly generated population and the

evolution is performed over several generations. The main feature of these algorithms is that they attach to each individual a fitness function. This function represents the individuals’ performance based on several criteria.

For each generation, a genetic algorithm calculates the fitness function value and represents the quality of each solution. Based on this evaluation, the best individuals are selected from the current population and recombined to form the new generation.

The new population is obtained from the old population by tracking 3 important stages:

• Selecting the best parents; • Obtaining new individuals from parents combination (crossover

operation); • Mutation appearance.

Crossover operation is represented by the disposal of two chromosomes, the results being combined to form other chromosomes which will be included in the new population. In this way one can achieve the propagation of the best genetic material and determine an increased performance of the candidate solution population. The mutation is represented by a chromosome modification applied to one or more genes.

The genetic algorithm finishes when either the maximum number of generation or the maximum number of generation members has been reached. At this moment there are selected the best individuals with the highest fitness function, which represents the solution offered by the algorithm.


324

Genetic Algorithms may find their application in many fields as bioinformatics, chemistry, mathematics, physics, engineering, computational science and others. They frequently have application in problems as [1]:

• Classification problems; • Tasks planning; • Network flow problems; • Real time optimization; • Prediction systems (economical, geological, structural and others); • Neural network design; • Robots trajectories determination.

3 Description of the Proposed Genetic Algorithm The Genetic Algorithm presented in this paper aims to be an application that helps to increase the quality of university research management. This application intends to identify the most suitable combination for a research team consisting of members from a university department.

The considered university department consists of 20 members and the research team that will work on a very important project must be formed by 8 persons. Thereby, the plan is to identify the best combination for this research team.

Inter-human relationships have an important role in the success of research projects that require teamwork. Therefore, for each member of the department, the authoress of this paper proposes a list of favourite colleagues. This list is represented as an input text file for the application, named “date_in.txt” and is also presented in Table 1.

Genetic codification of candidate solution is: (M1 M2 M3 M4 M5 M6 M7 M8)

where Mi represents a member of the proposed research team. The implementation of this genetic codification in C++ Builder is:

typedef struct cromozom

int g[8];//genetic codification of candidate solution

int fitness; //fitness function value

individual;

The performance of each individual is assessed as the objective function value. The fitness function has the initial value of 50 points. For each member it is to be verified if the team colleagues are in his list of friends. If a friend is found then 15 points are added to the fitness function, otherwise it is decreased by 1 point.

The implementation of the fitness function in C++ Builder is:

int fitness(individual ind)

int i,j,f;

f=50; //initial fitness function value

for(j=0;j<8;j++)

//search for friends


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for(i=1;i<=fr[j].nr;i++)

if(fr[j].friends[i]==ind.g[j])

f=f+15;//a friend has been found

else

f=f-1;//not a friend

return f;

Genetic operators used in this application are: roulette selection, one-point crossover,

rotation mutation. Roulette selection consists in choosing future parents by simulating the launching of a

roulette needle on the field of objective values for current population individuals. One-point crossover is an operator used to combine the genetic material of two parent

individuals, in order to obtain new individuals. Rotation mutation is an operator that performs minor modifications on the individual

by randomly selecting a block of genes, with random length, and reversing genes’ order. Genetic algorithms parameters are:

• Initial population size (with values between 5 and 50); • Maximum population size; • Maximum generation number; • Crossover probability (with values between 0.1 and 1.0); • Mutation probability (with values between 0.01 and 0.2).

The parameters’ values may be set-up by using the application interface. After pressing the “Generate” button, the application will show the results offered by the Genetic Algorithm in the right side of the window. Thereby, the value of the maximum fitness function and the optimal assignment with the maximum fitness function will be displayed. All the intermediary results will be stored in a data output text file named “testout.txt”

The solutions shown in the text box represent the team proposed by the application, based on the fitness function value, as seen in Figure 1.

Figure 1. User Interface


326

4 Experimental Results To test the application presented in this paper the authoress proposes a list of favourite colleagues. This list is represented as an input text file for the application and it is presented in Table 1.

Table 2 represented 3 sets of input data for the genetic algorithm. The genetic algorithm parameters are different for each test to guarantee the covering of a great diversity of cases.

Table 1. List of favourite colleagues. List of friends Member no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Member no. 2 1 3 7 10 13 20 Member no. 3 1 2 Member no. 4 1 19 17 15 Member no. 5 1 8 9 7 10 11 15 17 19 20 Member no. 6 1 11 20 Member no. 7 1 2 5 Member no. 8 1 5 Member no. 9 1 5 10 11 13 14 15 17 18 19 20 Member no. 10 1 2 5 9 13 16 Member no. 11 1 5 6 9 Member no. 12 1 20 Member no. 13 1 9 10 16 Member no. 14 1 9 Member no. 15 1 4 5 9 19 Member no. 16 1 9 12 17 18 20 Member no. 17 1 4 5 9 16 20 Member no. 18 1 9 18 Member no. 19 1 4 8 14 20 Member no. 20 1 2 5 6 9 12 16 17 19

Table 2. Experimental Values Set

Values set Parameters

1

2

3

Number of tests 5 5 5 Initial population size 10 15 25 Maximum population size 100 120 150 Maximum generation number

20 25 30

Crossover probability 0.5 0.3 0.6 Mutation probability 0.07 0.05 0.15

After the execution of 5 tests for each set of input values, the final results are synthesized in Table 3.

Best performances mean is calculated as the average of highest values of the fitness function obtained in the 15 sets of results. Worst performances mean at last generation mean is calculated as the average of lowest values of the fitness function.


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Mean of performances means at last generation is compute as the average of the medium performance for each of the experimental set of results.

Table 3. Final Results

Final results Best performances mean at last generation 97.93 Worst performances mean at last generation 16.87 Mean of performances means at last generation 59.76 Best performance 131 Number of solutions with the best performance 1 Best performance solution (12 7 10 2 15 11 20 1)

After all tests, it has been established that the highest value achieved by the fitness

function is 131 and only one solution has managed to reach this value. So the best team, based on relationships among teammates, is composed of persons corresponding to numbers:

12 7 10 2 15 11 20 1

5 Conclusions In the perspective of increasing demands regarding research application, a method to optimally use all the resources (financial, human and physical) has to be found. The success of a research project depends primarily on each individual part of the research team. In this context inter-human relationships have an important role in the success of research projects that require teamwork.

In this paper, the authoress presents an implementation of genetic algorithm in this area. The application receives as input data a list of favourite colleagues and aims to identify the most suitable combination for a research team consisting of members from a university department.

The genetic algorithm parameters’ values may be set-up by using the application interface. The value of the maximum fitness function and the optimal assignment with the maximum fitness function will be displayed and all the intermediary results will be stored in a data output text file.

After several test, the authoress has identified the solution with the highest fitness function. The selected research team is composed of people who work well together putting emphasis on achieving a more productive team.

REFERENCES

Oprea, M., Nicoara, S., “Artificial intelligence”, Petroleum–Gas University of Ploiesti, 2005. ***, University Research Management, http://www.oecd.org/document/37/0,3343,en_2649_35961291_35536165_1_1_1_1,00.html, accessed on

1.07.2009.

Section

INTEL® EDUCATION Innovation in Education and Research

21st Century challenges (IntelEDU): • Digital Curriculum, collaborative rich-media applications,

student software, teacher software

• Improved Learning Methods, interactive and collaborative methods to help teachers incorporate technology into their

lesson plans and enable students to learn anytime, anywhere

• Professional Development, readily available training to help teachers acquire the necessary ICT skills

• Connectivity and Technology, group projects and improve communication among teachers, students, parents and

administrators

Digital education usage models for the classroom of the future

Peter Hamilton, Eileen O’Duffy

Intel Corporation, Intel IT Innovation Centre (UK),

E-Mail: [email protected]

Abstract We present a model for teaching and learning with technology to improve the comprehension of key concepts and to support the development of 21st century skills will be outlined including: Curriculum learning content to support the knowledge acquisition of key curriculum objectives; Advanced open-ended learning and teaching toolkits to explore and deepen the students’ understanding of key concepts; Project and activity based learning for knowledge deepening and knowledge creation; Open ended learning to support innovation, problem solving, decision making, teamwork and collaborative learning; Communities of practice enabling teachers share best practice and communicate with students and classes in private and secure environments. This paper is based on our experience developing Intel skoool™.com learning and teaching technology programme which has developed education content and tools in 30 countries and 12 languages and dialects. Keywords: knowledge creation, curriculum objectives, problem solving, collaborative learning.

1 Introduction Flexible, cost effective and well planned ICT design is required to meet the pedagogical needs of learners and to enable teachers and administrative staff in education institutions work effectively.

Personalised Learning-shaping teaching around the different ways children learn. The need is for: • Anytime, anywhere learning – both within the school and in the wider community • Personalised learning where each learner can deepen their knowledge at their pace

and using their learning style, with the help of learner-centered 1-1 mobile computing

• Flexible learning spaces – moving beyond “traditional” classroom models towards learner-centered spaces conducive to collaboration and mentoring

Learning solutions need to provide more that standardized progression and teach to the test. Rich activity-based knowledge deepening and knowledge creation activities require learner-centered 1-1 models with high levels of mobility.

For example, ICT resources enable learners to learn at whatever level is appropriate for them from knowledge acquisition (Knowledge, Comprehension) to knowledge deepening (Application, Analysis) to knowledge creation (Synthesis, Evaluation).


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Instruction objects such as multimedia lessons can be used for knowledge acquisition, toolkits and scaffolded experiments for knowledge deepening and open-ended projects and research activities for knowledge creation and the synthesis of uncertain information.

Standardised

Instruction &

Testing

Standardised

Instruction &

Testing

Learner Enabling Resources

Lecture Coaching Student Centered

KnowledgeCreation

KnowledgeDeepening

KnowledgeAcquisition

‘Personal

Progression’

Open-Ended

Higher Order

Individualised

Open-Ended

Higher Order

Individualised

From Personal Progression to Personal ePortfolio

‘Personal

Portfolio’

Fig. 1 Learner Enabling Resources

2 Learner Enabling Resources The Digital Learning Space: The Digital Learning Space is at the core of the learning models for the 21st Century. The flexibility, adaptability and scalability required and demanded by today’s learners and teachers can be addressed through careful design of the ICT infrastructure, leading to a better learning and teaching experience. The demand for “anytime, anywhere” mobile learning, for example, requires high levels of reliability, manageability and security in the total system to ensure services and applications are always available and secure. Critics of ICT have argued that using ICT may drive and accelerate a standardization approach. Others may argue that ICT helps to encourage or even drives an open-ended learner centric and personalized model of learning. ICT does not in itself drive either approach: ICT is a tool and resource to support and facilitate whichever approach is adopted.

Tethered desk and thin client models may be highly limiting. 1-1 mobile computing with a strong set of software tools and content will support higher order knowledge deepening, knowledge creation and problem solving. This will provide learners with a positive and unlimited learning potential and the resources to develop 21st century skills. Cloud computing: Increased connectivity and significantly improved bandwidth including the wide spread of 100mbps and greater connection speeds in the developed world and the wider spread of DSL, WIMAX Wireless in developing markets and the advent of 4G mobile networks with connection speeds of between 10 and 40 mbps. This growing ease of connectivity together with the trend towards‘Cloud Computing’ represents the next mega-trend.


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“We will move from the Digital Immigrant phase through the Digital Native phase to the Online Native phase” Young users today are very comfortable to live in the Internet Cloud with increasingly more of their data and applications there and increasing levels of online security and privacy. Importance for Economies and Societies. Societies whose students and future workforce and learning in these rich open-ended learning systems supported by technology which foster these 21st Century Skills will have a significant competitive advantage over societies who do not move in these directions. If education transformation and reform policies are not adopted widely and applied based on equality of access digital divides will widen with resulting social and economic impact.

“With technology I can assign much higher level tasks to my students.” Deputy Head

Teacher of St. Thomas More School in London ranking in the top quartile in UK schools ranking. Sept. 2008.

Example: English Literature Assignment. The English teacher (or other first language literature teacher) sets an assignment around a particular author. The assignment requires critical analysis of the author’s writing style. Learners have become familiar with the writings of the author through reading the author’s novels. The teacher provides analysis of the writings in a “classic” manner. There is testing of learner’s knowledge and then the move is towards building on this knowledge. The assignment requires that students firstly work together in groups, so collaboration is very important. The ability to use instant messaging software to share ideas and debate and discuss with other learners …and possibly the author … provides richness and depth to the learning. All participants have an equal input and learning experience. Further knowledge is gained working alone – surfing the internet, accessing libraries of information, looking at analysis of experts on the author.

Finally, the students’ assignments can be published for critique by teacher and colleagues.

Throughout the assignment, the learners can have access through technologies such as email, discussion boards, weblogs, to the teacher, their colleagues, data and information –where and when they decide. Vision Personalised Learning - shaping teaching around the different ways children learn.

The emphasis on personalised learning is a key principle underlying recent educational initiatives. Personalised learning is about tailoring education to ensure that every pupil reaches their full potential, one of the aims of the Five-Year Strategy for Children and Learners,1United Kingdom Department for Education and Skills (DfES) July 2004. It is not individualised learning, where children work alone, nor is it pupils being left to their own devices. It means a strategic and structure approach to shaping

1 DfES : http://www.dfes.gov.uk/


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teaching around the different ways children learn. Many schools and teachers have tailored their curriculum and teaching methods to meet their pupils’ needs for years with various initiatives. What is new is the drive to make these practices universal.

A strategic approach to ICT both in the classroom and linking the classroom and home is a key facilitator and enabler of personalised learning. The DfES publication Harnessing Technology: transforming learning and children's services 2 reflects the ever changing and effective use of ICT across the whole education system and highlights the need for a more strategic approach to the future development of ICT in education, skills and children's services. The strategy addresses priorities in workforce development, organisational change, personalisation of learning, content, access and the procurement of services and identifies six priorities which will apply to 14-19 year olds and lifelong learning as well as schools and children's services:

• an integrated online information service for all citizens • integrated online personal support for children and learners • a collaborative approach to personalised learning activities • a good quality ICT training and support package for practitioners • a leadership and development package for organisational capability in ICT.

3 Learning Styles and Learning Strategies The term “learning styles” has no one definition – in much of the literature it is used loosely and often interchangeably with terms such as “thinking styles”, “cognitive styles” and ‘earning modalities” In addition, a significant number of theorists and researchers (e.g. Kolb) have argued that learning styles are not determined by inherited characteristics, but develop through experience. Styles are therefore not necessarily fixed, but can change over time, even from one situation to the next. The risk here is to do students a disservice by implying they have only one learning style, rather than a flexible repertoire from which to choose, depending on the context. Theorists such as Entwistle, are more interested in how students tackle a specific learning task (learning strategy) than any habitual preference (learning style). What these authors have in common is an emphasis not simply on the learner but on the interaction between the learner, the context and the nature of the task. If, therefore, learning styles are not fixed personality traits, the emphasis shifts from accommodating learning styles to encouraging a balanced approach to learning and – perhaps more importantly – an explicit awareness of the range of approaches available to the learner. Thus for content developers it may be more appropriate to think in terms of accommodating, rather than matching, a range of modalities and styles. Moreno and Mayer (1999)3 found that mixed modality (visual/auditory) presentations were the most effective and Gregorc (1984)4 also observed that learners prefer a variety of instructional approaches. The good news is that

2DfES : http://www.dfes.gov.uk/ 3 Moreno, R and Mayr, R E (1999), ‘Cognitive principles of multimedia learning: the role of modality and contiguity’, Journal of Educational Psychology, 91, 358–368 4 Gregorc, A F (1984), ‘Style as a symptom: a phenomenological perspective’, Theory into Practice, 23(1), 51–55


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ICT today has the flexibility to enable this variation in usage happen in a seamless manner.

Each learning style uses ICT hardware and software in different and multifaceted ways. The key message is that the ICT designs need to take account of these differences. Teachers and Learners can select from a range of multimedia and digital applications to match their preferred learning style and strategy and to experiment and investigate different approaches. Advantage can be taken of the opportunity current and future VLE/LMS and other ICT systems can provide, to support personalised learning paths. Thus there is a benefit in enabling learners to reflect on how they learn. Encouraging metacognition (being aware of one’s own thought and learning processes) is therefore perhaps the most important advantage that can be claimed for applying learning styles theory to learning and teaching.

The following table shows some examples of ICT applications supporting varying

learning styles. Visual– learning by seeing

IT Application Examples of Usage Models Modern ICT supports visual learning with high quality graphics, animations, simulations and visualisations. Abstract concepts are brought to life and effectively explained.

Digital photography and video enhances learning and provide rich presentation. Teachers can present concepts and ideas using rich visual media, capturing the learners attention Interactive whiteboards bring this visualisation alive for the whole classroom.

Auditory- learning by hearing

IT Application Examples of Usage Models Auditory learners learn most effectively through dialogue and listening. ICT based learning supports simultaneous, audio, visual and text-based learning.

High quality sound and editing capability enables deeper learning and creative presentations Collaboration with other schools and peers using video and audio tools deepens knowledge

Kinaesthetic- learning by doing

IT Application Examples of Usage Models ICT can truly come into its own for the kinaesthetic learner providing engaging activities to draw the student back into the learning process. Computer based activities have been proven to have significant positive impact on

Advances in gaming technology and policies that support the use of this technology in school will enhance the student’s numeracy, literacy, logic skills and self-confidence. Live data from a physics practical experiment can be captured for a


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confidence levels, attendance rates and drop-out levels, particularly among this group of students5. Kinaesthetic learners benefit from using devices that involve touch, like mice and joysticks, or a Tablet PC, which enables users to write or draw onto a computer using a pen.

measuring device directly to the learner’s notebook, which they can analyse using the PC tools available. Graphic design software and animation tools provide the kinaesthetic learner with the environment for knowledge creation.

4 21st Century Skills and Key Competencies for the Knowledge Economy There is a growing and widely accepted understanding that a different set of skills need to be developed by our students in our school systems. In the United States and also in UNESCO strategies these are referred to as the 21st Century Skills. The European Union in the Lisbon framework outlines eight domains of Key Competences for Lifelong Learning.

These 21st Century Skills are critically important to support the challenges of the modern work-place and the dynamic and rapidly changing knowledge society. Highly structured and disciplined schooling systems do not necessarily prepare students well for the dynamics and challenges of the 21st century workplace and society. More self-motivated, individualized, group and collaborative learning processes, supported by ICT will contribute significantly to the preparation of a more agile modern workforce.

21st Century Skills identify: The EU eight domain of key competence are: 1 Creativity and innovation 2 Critical thinking 3 Problem solving 4 Communicatin 5 Collaboration 6 Information fluency 7 Technogical literacy

1 Communication in the mother tongue 2 Communication in a foreign language 3 Mathematical literacy 4 Basic competences in science and technology 5 Digital competence 6 Learning-to-learn 7 Interpersonal and civic competences 8 Entrepreneurship and Cultural expression

(Source: http://ec.europa.eu/education/policies/2010/doc/basicframe.pdf6). A Vision for Virtual Learning Environments – enabling Curriculum Progression and

Higher Order Teaching and Learning Models. Previously a progression of learning and teaching models, starting with Knowledge

Acquisition through Knowledge Deepening to higher order Knowledge Creation and Concept Synthesis, was discussed. It was identified how multi-media curriculum resources can enhance the knowledge acquisition stages while improving student motivation. It can be seen how creative multi-media resources, simulations, learning toolkits, games and project activities can contribute significantly to knowledge deepening and concept understanding. Broader scope research project or experiment assignments will drive students to higher levels of knowledge creation and synthesis.

5 Studies of notebook computer deployment in Henrico County Virginia, Minneapolis, Minnesota, Michigan and Maine, and in the Freedom to Learn Evaluation Report, January 2004


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The figure below illustrates how each of these activities works together to complete a teaching and learning process:

• Curriculum Foundation: Knowledge Acquisition meeting Curriculum Key Objectives providing a foundation knowledge base in each curriculum subject.

• Learning Activities: Knowledge Deepening and Concept Synthesis through problem solving, project activity, experiments and research.

• Reference: to support Learning Activities and Research to provide deeper information. Internet resources and conventional library resources.

• Collaboration and Communication: Student Collaboration and Communication to support problem solving and project work, developing 21st Century Skills.

• Student Centered with Educator as Facilitator. • VLE/LMS will support activity management and tracking allowing the teacher

communicate with students, assess portfolios of work and assign activities. These systems are not yet being extensively used in schools but we believe that as the complete system maturity increases these systems will become essential over the next 5 years.

Fig. 3 Learning Activity and Resource Diagram

The higher order activities and projects and the collaboration, team-work and

reference skills developed in these processes will support the development of 21st Century Skills.

5 Mini Case Studies 5.1 Blogging “The Secret Life of Bees” In 2003 a grade 10 English teachers in the United States set up a Weblog (“Blog”) within the school learning management system to allow students discuss different aspects of Sue

Fig. 2 Skills for the 21st Century


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Monk Kidd’s acclaimed novel about race and prejudice in the southern United States. In the Blog the teacher asked the students several questions which drove them to propose different interpretations of sections of the book. Other teachers and people with a background in literature joined the Blog discussion. Finally a mystery contributor joined the Blog discussion and added some different perspectives to the discussion. The mystery contributor was unveiled as the author of the book creating enormous motivation among the students while creating an interest and much deeper understanding of literature.

5.2 Science Experimentation with real-time Data Collection. IT provides enormous potential for exciting Science projects which can make the experience much more like the real-world and engaging for students. Several techniques for data capture and data analysis add significant extra dimensions to the activity including:

• Data capture with electronic sensors including simple motion sensors, temperature sensors etc.

• Data analysis, graphing and interpretation using spreadsheets. • Digital video and still photography of experiments and scientific phenomena. Professor Adrian Oldknow of the UK Mathematical Association has written a number

of papers describing techniques with motion sensors enabling students to create basic time and motion graphs in the classroom. This technique can be extended into the gymnasium with students running, introducing the principle of acceleration and undertaking exercises to illustrate Newton’s laws of motion. Similar approaches can be envisaged where the data from experiments in physics, chemistry and biology can be captured using the techniques outlined above. The underlying mathematics can also be revealed using the graphing and charting techniques such as some of the principles of calculus in the acceleration example outlined. These techniques address many significant issues in teaching and learning among which are: the integration of mathematics and science, providing real-world context and drawing in the less motivated students including difficult to reach kinesthetic students. Students complete project reports with the data and observations from these activities and answer some questions designed to confirm their comprehension of the topics covered. These reports are submitted in the VLE/LMS for grading by the teacher and can become part of the student’s ePortfolio.

5.3 The skoool™ Maths Toolkit From the www.skoool.com website an open-ended toolkit for teaching and learning Mathematics can be downloaded free of charge by all teachers and students. The UK Mathematical Association and Intel collaborated to develop this toolkit which won the BETT award for Key Stage 3 and 4 Maths in 2006. The toolkit provides resources which are designed to encourage learners to explore the more difficult to understand topics by emphasising the effect of changing variables. The resources support the understanding of the number system, graphical representations, transformations and statistical methods. The toolkit is ideal for whole-class teaching on the interactive whiteboard and also for individual learning at school or home to broaden a student’s understanding of key concepts.


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Fig. 4 skoool.com mathematics toolkit and numberline

Learning Anytime Anywhere The possibilities of learning beyond the school environment are extended through and by the use of ICT. Mobile technologies enable this type of learning and learners can access resources and content in a manner and place that is most suitable to them. Learning at home or in any Wi-Fi location, enables more learning by providing learners with the structure and resources for anytime/anywhere learning. The figure below illustrates that given the proper resources learners will access resources outside of the normal school house and beyond the school week. This data is extracted from web hits on the Skoool™ London Grid for Learning resource and show both hourly and daily activity.

Fig. 5 Daily and weekly usage patterns of skoool.co.uk content in the London

Grid for Learning May 2009


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6 Motivation: A Case Study Building confidence and motivating learners is conducive with improved attainment. This is especially the case for those hard to reach learners, or learners that face extra challenges in their education. ICT has a role to play in increasing confidence and enable a level playing field evolve where all students can achieve to the best of their abilities. A recent deep dive study undertaken by Intel at two secondary in the UK, provided first hand evident of how ICT can improve confidence and motivate learners and teachers.

Case Study: Two schools in Nottingham - Djanogly and Minster Two schools in Nottingham, UK - Minster located in Southwell and Djanogly in the

inner-city – volunteered to undertake a pilot study using Ultra Mobile PC’s. The objective was to better understand the usage need for the ultra mobile form factor requirements in the education sector. The results of the study provided fascinating and valuable data around usage models and the interaction between the learners and the devices. In particular, on the subject of motivation and self esteem, there were a number of findings. Confidence grew as learners took ownership of the devices as they were given the responsibility to use and work with them.

The Ultra Mobile PC provided opportunities for self-paced learning with in turn challenged students at their own level and built up self esteem. The immediacy of continuous feedback also added to this factor. For those students with learning challenges, the “levelling of the playfield” was in evidence. One autistic student’s interaction with his peer group was sub optimal. His teacher witnessed a number of improvements in his learning and social skills once he started working with the UMPC. For example, before, his written work was difficult to read but he could now hand in legible assignments typed on his UMPC. Handwriting was no longer a major barrier to expression so the teacher could better assess his work.

Another student with limited attention span had his self confidence boosted as he collaborated more frequently and shared his learning and became somewhat of an expert in using the Ultra Mobile Device. His advice was sought to solve problems. Teachers witnessed a decrease in his disruptive tendencies and an increase in self-esteem. This illustrates that for this difficult-to-reach learner, the hands-on aspect of learning with ICT drew him into the learning process.

Finally, mobility means students could use the devices wherever and whenever they wanted. The size and style of the ultra-mobile form factor device better fits the lifestyle and style choice of teenage students. This enabled them become familiar with the device and provided opportunities for students to build up their self reliance, which boosted confidence and increased motivation.

REFERENCES

DfES : http://www.dfes.gov.uk/ Moreno, R and Mayr, R E (1999): Cgnitive principles of multimedia learning: the role of modality and

contiguity” in Journal Educational Psychology, 91, 358–368 Gregorc, A F (1984): Style as a symptom: a phenomenological perspective , in Theory into Practice, 23(1),

51–55 Studies and Report (2004): Studies of notebook computer deployment in Henrico County Virginia,

Minneapolis, Minnesota, Michigan and Maine, and in the Freedom to Learn Evaluation Report, January 2004

UE (2004): Implementation of “Education and Training 2010” work programme, Key Competences for LifelongLearning, European Commission,

http://ec.europa.eu/education/policies/2010/doc/basicframe.pdf

Effective eLearning

Olimpius Istrate

Intel Corporation, Romania Repr. Office

2 Teheran Str., Bucharest 011932, ROMANIA E-Mail: [email protected]

Abstract A variety of studies have evaluated the eLearning and concluded that it can help produce positive outcomes. Which are the common elements of the various successful eLearning programmes? What should somebody take into consideration when designing such a programme? Today it is well known that eLearning is effective if it is supported by holistic approaches that include appropriate policies, infrastructure, professional development, and curricula. The present paper is trying to point out some basic elements concerning the design and implementation of an effective eLearning programme.

Keywords: eLearning, research, evidence-based effects

1 eLearning overview Technology integration to support education has been underway for many years. Some of the common ways of integrating technology into education include:

• Teacher PC programs provide encouragement and financial assistance for teachers to acquire PCs and integrate ICT into their teaching practices. When most effective, these programs include professional development and policy modifications, as well as updated digital content and curriculum resources to help teachers use technology to enhance teaching and learning.

• PC labs are frequently used to offer technology access when resources are severely constrained. While PC labs provide some exposure to technology, they limit teachers’ ability to incorporate technology into the curriculum, and often are used only to teach computer literacy.

• Classroom eLearning brings PCs into the classroom, typically via systems stationed at the back of the classroom or computers on wheels (COWs) that are shared by different classrooms. Students have a dedicated device for part of the school day, with the focus on using PCs to enhance learning across the curriculum and not simply to develop technology skills.

• One-to-one (1:1) eLearning provides each teacher and student with a dedicated laptop for use at school and, in many cases, at home. Laptops serve as personal teaching and learning tools that are used throughout the day for many educational tasks and subjects. In a 1:1 environment, students get the maximum value from access to PCs, Internet connectivity, and their integration into the education environment.


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Figure 1: eLearning Continuum Effective eLearning comes from using information and communication technologies

(ICT) to broaden educational opportunity and help students develop the skills they—and their countries—need to thrive in the 21st century. While conclusive, longitudinal studies remain to be done, an emerging body of evidence suggests that eLearning can deliver substantial positive effects:

• Students are more engaged and able to develop 21st century skills. • Teachers have a more positive attitude toward their work and are able to provide

more personalized learning. • Family interaction and parental involvement may increase. • Communities benefit from bridging the digital divide. Economically disadvantaged

students and children with disabilities benefit particularly. • Economic progress can result from direct job creation in the technology industry as

well as from developing a better educated workforce. The effects of 1:1 eLearning appear to increase as technology is more deeply

integrated into the educational experience and students and teachers have technology access throughout the day.

• Trucano’s review of papers dealing with ICT’s benefit for education in developing nations showed that placing PCs in classrooms rather than separate labs enables much greater use of technology for higher order skills. (Trucano, Global)

• In West Virginia, one of the poorest US states, students who experienced classroom eLearning had higher gains in overall scores and in math than those who had technology access only in computer labs. The authors compared classroom eLearning against other policy interventions of similar cost (such as smaller class


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size, additional instructional time, and cross-age tutoring) and found that technology can be one of the most efficient ways to boost outcomes. (Mann et al, USA)

• In a study comparing COWs and 1:1 eLearning environments for fifth, sixth, and seventh graders at a small-town school district in the American Midwest, researchers found that students in the 1:1 environment gained significant advantages on writing performance, including ideas/content, organization, style, and conventions. In addition, math, science, and social studies achievement scores were higher on average for students in the 1:1 environment compared to those using COWs. (Ross et al, USA)

2 Student learning Studies show that eLearning can help increase student engagement, motivation, and attendance—key requisites for learning.

Effective eLearning can also improve performance on core subjects and foster the development of 21st century skills, whether in mature or emerging countries.

• The US state of Maine created 1:1 eLearning environments in schools reaching over 42,000 middle school students and 5,000 teachers. More than 80 percent of teachers surveyed said that students were more engaged and more actively involved in their learning and produced higher quality work. Principals and teachers reported “considerable anecdotal evidence” that eLearning increased student motivation and class participation, and improved behavior. (Silvernail, USA)

• In a 1:1 eLearning program at 10 primary and secondary schools in Malaysia, 85 percent of teachers, many of whom were initially skeptical, reported that the program helped them create an innovative and collaborative eLearning environment within their classrooms. (Malaysia Ministry of Education and Intel Malaysia, Malaysia)

• At a large rural high school, attendance rose from 91 percent to 98 percent after the 1:1 eLearning program began. (Mitchell Institute, USA)

• A meta-analysis of 42 peer-reviewed papers published between 1996 and 2003 found a positive significant correlation of .448 with cognitive outcomes, indicating that average students who used technology would be at the 66th percentile while average students without technology would be at the 50th percentile. The authors observed that “the overall effects of technology on student outcomes may be greater than previously thought.” (Waxman et al, Global)

• In South Africa, a three-year randomized controlled study of the large-scale Khanya project showed math scores were significantly higher for students who participated in a technology program. Khanya is an award-winning project to provide a technology-rich environment and professional development activities to students and teachers throughout the Western Cape region. (Wagner et al, South Africa)


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• Penuel et al performed a research synthesis of 19 programs in Europe, the Middle East, Africa, and the US that used technology to link home and school. They found that technology-supported programs produced positive effects on reading achievement (+0.08 to + 0.10), writing (+0.20 to +0.34), and math achievement (+0.18 to +0.23), as measured by traditional methods and standards. (Penuel et al, Global)

• A meta-analysis of over 500 studies indicated that students receiving computer-based instruction tend to learn more in less time. (Chinien, Global)

• In a 1:1 class in Puebla, Mexico, teachers observed an improvement in second to fourth grade students’ skills at searching information and ability to write—both important 21st century skills. The eLearning environment gave students the opportunity to conduct Internet research and evaluate the quality of information found. (Escorza and Rodriguez, Mexico)

Although numerous studies report positive outcomes, there are also indications that improper use can lead to negative student behaviors, from playing games to tampering with security measures. (Keri et al, USA) However, solutions such as classroom management software and technology usage policies are well documented and effective at overcoming such obstacles. The potential for negative outcomes underscores the importance of holistic planning, with attention to access, policies, connectivity, professional development, and curriculum, in order to achieve desired benefits.

3 Teaching and Administrative outcomes Researchers have reported that issuing laptops to teachers, or helping them purchase laptops, can empower them to teach better, increase lesson planning and preparation productivity, gain a more positive attitude about their work, and improve efficiency of management and administration tasks.

• Using technology, teachers can access tools that enable them to deliver customized assessments and gain immediate feedback on individual and class progress. (Kerr et al, USA)

• With this feedback, teachers can provide personalized learning opportunities, using remediation and enrichment to deliver more differentiated instruction that better meets each child’s needs. (Warschauer et al, USA)

• In Maine’s state-wide eLearning deployment, teachers with personal PC access said that technology helped them locate and develop better instructional materials and conduct research related to their teaching assignments. Teachers gained access to better quality curricula and learning materials, especially when schools created eLearning portals where teachers could share resources they found or developed. (Silvernail, USA)

• In a Turkish study of primary school teachers and students, 87 percent of teachers surveyed said eLearning improved their ability to conduct project-based learning. They also stated that eLearning supported the shift from teacher-centered to student-centered

• teaching, and enabled them to act as facilitators more than lecturers. (Aydin, Turkey) • Personal PC access has been shown to increase teacher productivity. UK agency

Becta cites a 2005 study by PricewaterhouseCoopers indicating that teachers


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creating a lesson plan from scratch using digital resources saved an average of 26 minutes compared to those who did not. (Becta 2007, UK) When 400 teachers were surveyed on how they used time saved on lesson planning and other tasks, 31 percent said they performed additional preparation, planning and other core tasks, while 47 percent performed new tasks or performed existing tasks to a higher standard. (PricewaterhouseCoopers, UK)

• A review of 17 recent European studies reported that teachers’ roles can be more rewarding in an effective eLearning environment. Teachers who perceive a highly positive impact from ICT tend to use technology in project-oriented, collaborative, and experimental ways. Teachers function as advisors, dialogue partners and facilitators for specific subject domains. (Balanskat et al, Europe)

• In evaluating the Notebooks for Teachers and Principals Program implemented by the Victoria Department of Education and Training, researchers found that teachers felt more valued as professionals as a result of having their own laptops. They also felt that parents viewed them more respectfully, and that they were recognized as important by the government. Some 70 percent of teachers said the program had increased their professional competence in areas such as teaching practices and assessing and reporting student learning. (Gough et al, Australia)

4 Management and Administration

• Students and teachers are not the only people who benefit from eLearning. When a rural Pennsylvania school district equipped all students in grades 3-12 with a laptop and home Internet access, principals said they could provide more effective instructional leadership because they had better visibility into students’ progress and work products. Principals said the enhanced connectivity also improved their capacity to communicate with parents, faculty, and district leaders, and enabled them to perform their responsibilities more efficiently. (Kerr et al, USA)

• There is growing evidence that eLearning supports school improvement efforts. A recent study surveyed the head teachers of 181 British schools that had improved enough to be removed from a “Special Measures and Notice to Improve” list, and found that 82 percent of head teachers indicated technology had played a key role in their school’s achievement. Effective approaches ranged from adopting systems for monitoring and analyzing student progress, to using technology to engage underachieving students. (Hollingsworth, cited in Becta 2008, UK)

A less positive aspect of eLearning environments is that they can expand teacher workloads by increasing clerical expectations or creating a need to adapt curriculum materials. To a certain extent, this can be addressed with professional development, supportive leadership, and improved policies.

5 Dual Investment Strategy for optimal elearning Research indicates that elearning is most effective in a 1:1 eLearning environment where:

• Technology tools and connectivity are deeply integrated into the classroom and used across the curriculum.


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• Teachers are skilled and comfortable using digital resources to enhance teaching and learning.

To achieve this integration and skill, governments and educators must invest in professional development and curriculum resources as well as in PCs and networks. These two areas of investment reinforce each other and increase the return on either type of investment: professional development and curriculum resources help teachers actually use technology to transform teaching and learning, and adequate technology access enables teachers to apply what they learn in professional development activities.

The Organization for Economic Co-operation and Development (OECD) states that to reap educational benefits from ICT, countries and educational systems must reach a threshold of investments in ICT and in the skills and educational organization to use them (OECD, Global). Backing this up, a survey of 11 international eLearning deployments found that teachers are more likely to integrate technology into their pedagogy when they have technology in the classroom. The average implementation rate for teachers who had lab access only was 71.7 percent, increasing to 87.2 percent when teachers had one PC in their classrooms and reaching 94.8 percent when teachers had access to two to six classroom computers. (Martin, et al, Global)

A second global survey highlights the importance of effective teacher professional development and support. It found that teachers who are most likely to use technology effectively to improve education are those who have completed professional development programs, work in a school with ample support, and have technology in the classroom rather than in a PC lab. (Light and Martin, Global)

6 Social and Community Effects By issuing a laptop to each student, schools aim to meet the educational needs of students who ordinarily could not afford a PC and thereby improve the performance of all students. Research shows that this strategy is working.

• At-risk and low-achieving students, and students whose parents do not have a bachelor’s degree, experience greater positive impact than other groups when 1:1 eLearning is deployed. For example, the Texas Technology Immersion Pilot showed that economically disadvantaged students reached proficiency levels matching the skills of advantaged control students. (Texas Center for Educational Research, USA)

• A qualitative study focused on two US schools with high percentages of immigrant and/or impoverished students. It analyzed the use of 1:1 eLearning to help English language learners develop academic literacy. At an elementary school, Latino fourth-grade students used laptops for pre-and post-reading. At a middle school, immigrant and refugee students used laptops in community projects that required independent reading and research. At both schools, students achieved reading test scores that were higher than their state averages, and the middle school students’ writing scores were above average as well. (Warschauer, USA)

• In studies of students with disabilities, researchers have observed improved student self-esteem, increased motivation and ability to work independently, and other


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academic achievements such as improved quality and quantity of student writing. (Harris, USA)

A number of studies suggest that, from a long-term perspective, a wide array of social and community benefits are associated with improved education. These benefits include reduced criminal activity, reduced reliance on welfare and other social programs, increased charitable giving and volunteer activity—even attainment of desired family size and improved health for the individual and his or her family. (Riddell, Global) Knowing the many ways in which eLearning can improve education, it’s intriguing to consider that eLearning may indirectly enhance these areas as well.

7 Economic Development So far, we’ve discussed research showing how eLearning improves educational achievement. Now we turn to studies that examine how improved achievement can affect a nation’s economic prospects. For many countries, economic development is the driving reason behind eLearning investments.

Recent examples indicate that eLearning investments can improve economic development in two ways: by direct job creation as governments procure the PCs, networks, software, and services to support the eLearning deployment; and indirectly, by developing a better educated workforce.

Direct Economic Impact: Portugal In July 2008, Portuguese Prime Minister Jose Socrates announced Project Magellan, an investment by the Government of Portugal to provide locally-built classmate PCs to all Portuguese students aged 6-10. Classmate PCs would be supplied by local technology company JP Sá Couto, Linux* software provider Caixa Magica, and other local ICT companies. JP Sá Couto plans to manufacture and export 4 million classmate PCs in addition to 500,000 units intended for use within Portugal. With Project Magellan, the Government is making a two-fold investment in the nation’s knowledge economy: Portugal’s children will be equipped with the skills to compete for high paying jobs in the future, and Portuguese workers will gain access to high-quality, high-value-added jobs in the near term. According to analysis by Vital Wave Consulting, Project Magellan will generate a total of 1,470 jobs and produce a total economic impact of EUR 2.26 (USD 3.131) billion (Table 1). (Coppock, Portugal)

Indirect Impact: Economic Benefits of a Better-Educated Workforce Although no research clearly addresses the indirect impact of eLearning on the economy, it certainly seems reasonable to think that, by increasing educational achievement, eLearning may be able to ultimately enhance economic attainment.

International comparisons show that education plays a pivotal role in fostering labor productivity and economic growth. For example, Harvard economist William Barro’s analysis of education and economic growth concludes that an increase of one standard deviation in test scores would raise the growth rate of real per capita GDP by 1 percent per year. (Barro, Global)


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A World Bank study further underscores these findings: it reports that raising test scores on the OECD Program for International Student Assessment (PISA) test by 47 points (the equivalent of one country-level standard deviation) will drive approximately a 1 percent increase in gross domestic product (GDP). The World Bank report also references US research suggesting that an increase of one standard deviation in math performance at the end of high school translates to 12 percent higher annual earnings. (Hanushek and Wossmann, Global)

REFERENCES

*** Intel (2009) Positive benefits of eLearningWhite Paper.Intel World Ahead Program: Education. Becta (2008) Harnessing Technology Review 2008: The Role of Technology and Its Impact on Education,

Summary Report. November 2008. Chinien, Chris (2003) The Use of ICTs in Technical and Vocational Education and Training. UNESCO

Institute for Information Technologies in Education. Făt, Silvia & Adrian Labar (2009) Eficienta utilizarii noilor tehnologii in educatie. EduTIC 2009 (Efficiency

of ICT Use in Education. EduTIC 2009). Bucharest: Centre for Innovation in Education. Hanushek, Eric A. and Wossmann, Ludger. (2007) Education Quality and Economic Growth. World Bank. Martin, Wendy, Katherine McMillan Culp, Andrew Gersick, and Hannah Nudell (2003) Intel Teach to the

Future: Lessons learned from the evaluation of a large-scale technology-interpretation professional development program. Education Development Center’s Center for Children and Technology.

Organization for Economic Co-operation and Development (2009) Education Today: The OECD Perspective. OECD.

Toma, Steliana et al. (2009) Teaching in the Knowledge Society: The Impact of the Intel Teach Program in Romania. Bucharest: Agata Publishing House.

Vlada, Marin (2009) Utilizarea Tehnologiilor eLearning: cele mai importante 10 initiative si proiecte din Romania (Using eLearning Technologies: the Most Important 10 Initiatives and Projects in Romania). In: Elearning.Romania. Bucharest: TEHNE- Centre for Innovation in Education. Available online: http://www.elearning.ro

The evolution of Learning Object repository: Towards the Learning Object Management System

and dynamic use of metadata

Gentile Manuel1, Fulantelli Giovanni1, Taibi Davide1, Allegra Mario1

(1) Italian National Research Council, Institute for Educational Technology

Via Ugo La Malfa 153, Palermo, ITALY E-mail: gentile,fulantelli,taibi,allegra@ itd.cnr.it

Abstract In this paper we illustrate how a dynamic vision of the metadata concept can dramatically improve the management of Learning Objects. Specifically, the ideas elaborated in this paper are contributing to the improvement- in terms of effectiveness and usability of Learning Objects - of FreeLOms, a Learning Object Management System we have developed in the framework of the EU-funded SLOOP Project, Sharing Learning Objects in an Open perspective. Keywords: Open Educational Resource, Open Learning Objects, Communities of practice, Learning Object Management Systems, Web 2.0

1 Introduction The debate about the pedagogical effectiveness and adoption of Learning Object metadata models is a long-lasting one. Actually, the difficulties experienced by teachers in the use and management of metadata models risk to compromise the potentials offered by these models. The e-learning environments and tools that have been developed so far rarely take into consideration some important factors such as: the life-cycle of the resources to be described, the intrinsic differences existing between the typologies of information (descriptive, management, structural, and so on) related with the resources, and how each kind of metadata should be associated to the resources.

Several studies (Cardinaels, 2007) highlight that a dynamic view of the concept of metadata would foster innovative ways of using and managing educational resources. In this context, not only does the definition of the OpenLO model (Fulantelli et al, 2007) strengthen the vision of dynamic metadata, but it also requires a further step towards the definition of a comprehensive methodology to define the management of dynamic information and, at the same time, to develop the appropriate technological tools.

Starting from an analysis of the state of the art about learning object metadata, we analyse the recent research on the concept of dynamic metadata. Then, we present the results of the research work forming part of the activities of the EU-funded project SLOOP: Sharing Learning Objects in an Open Perspective (Masseroni and Ravotto, 2005), aimed at encouraging the definition, development and management of Open


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Educational Resources based on the Learning Object paradigm (Wiley, 2000). In particular, we present the Open Learning Object (OpenLO) model and the consequences on the life cycle of learning resources; afterwards, we analyze how a dynamic vision of the metadata should be integrated in the design of effective environment to manage LO, called LOMS in order to improve the management of Learning Objects.

Finally, we illustrate the evolution of a LOMS developed in the framework of the Sloop project, named FreeLOms (Gentile et al, 2006), based on a dynamic vision of the metadata concept and the advantages offered by this approach for teachers and educational professionals in terms of effectiveness and usability of Learning Objects.

2 Lifecycle of Learning Resources: the OpenLO perspective Different research works analyze the life cycle of learning resources. In (Strijker, 2004; Collis and Strijker, 2004) a general model of the life cycle is proposed. The stages of this model appear complex, and do not allow to identify the task that is necessary to carry out within each phase. For example, the “Using” phase could also contemplate the adaptation of the resource.

In (Van Assche and Vuorikari, 2006) an use scenario for learning resources is proposed; it draws attention to the complexity of the learning resources life cycle and to the different paths and cycles that a learning resource can follow. Starting from several works (Strijker, 2004; Van Assche and Vuorikari, 2006), (Cardinaels, 2007) proposes a life cycle called “dynamic life cycle”. This model aims to stress two main concepts: the reusability of learning resources and the dynamic view of learning object metadata.

In particular after the “Repurposing” stage, the user can directly integrate the resource in its own learning context or can edit the resource to adapt it or creating a new learning object and the creation of new learning object. Moreover, the “Labeling” stage becomes a transversal stage to allow the generation of metadata in parallel with all the other phases. These changes point out that the description of a learning resource may benefit from the analysis of the information collected from different sources, such as the information related to the context of use gathered from the learning management system.

Finally, in (Lehmann et al, 2008) it is possible to find an analysis of the life cycles previously proposed, and a re-establishment of the models previously listed, distinguishing 4 fundamental phases which are called Authoring, Provisioning, Re-authoring, Learning and Consumption according to a scheme that allows the creation of different scenarios.

All these works aim at iterative life cycles in which it is possible to reuse educational resources through composition and/or adaptation (and therefore editing) of existing resources.

These models of life cycle presuppose that there is the possibility to modify the learning resources at a “content” level.

At the moment, the used models for Learning Object (e.g. SCORM) (ADL, 2001)consider the re-usability only in terms of composition of existing resources in complex teaching units, according to the Lego model (Wiley, 2000).

In (Fulantelli et al, 2007), the concept of OpenLO was introduced, according to the idea that facilitate the activation of processes in which the active role of teachers is


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essential, in order to move towards a pedagogical concept of reusability in which a LO can evolve to meet specific educational requirements.

To this aim we have to facilitate the personalization, the changing and the adaptation of learning resources. Following the point of view of the OpenLO model, scenarios such those proposed in (Van Assche and Vuorikari 2006; Cardinaels, 2007; Lehmann et al, 2008) may actually take action.

3 Learning Object Metadata: State of the art The importance of metadata in managing digital resources for learning is underlined in several works. (Duval and Hodgins, 2003; Motelet and Baloian, 2005; Duval and Hodgins, 2006).

Learning Object Metadata, initially proposed in order to facilitate the retrieval and the reuse of the digital resources for learning, are raising an increasingly interest in the research area and therefore are often reason of debate.

Different metadata schemas have been proposed as a solution for the description of learning resources; the two main models are the Dublin Core (ISO 15836: 2003.2003) and the IEEE LOM (IEEE, 2002). From a comparison between the two models, the IEEE LOM appears the most used in the field. In fact, since it was designed exclusively for the description of educational resources, it allows the management of the information which may be appropriate to such description.

The main reason for the success of the standard IEEE LOM is due to its extreme flexibility. In fact, as it is claimed in (Duval and Hodgins 2006) “LOM effectively standardizes how to structure metadata about learning objects, not which metadata elements to include”.

The extreme flexibility of the standard has encouraged the growth of proposals for the standard extension, usually named “Application Profile”(AP). An “Application Profile” is an extension of the standard which defines new elements or attributes or specifies the value space of some elements.

Despite the presence of about 76 different aspects by means of which it is possible to describe the educational resources, some works underline gaps in the expressive power of the standard, especially with respect to the pedagogical features of the resources in specific contexts. In fact these Application Profiles have been defined to adapt the IEEE LOM in particular contexts of interest. This variety of specific raises an obvious problem of interoperability between the descriptions carried out following the guidelines imposed by the various APs. For a deeper analysis of this issue, refer to (Sampson, 2004).

From a technical point of view, different works highlight the limits of binding XML LOM, indicating as essential points of criticism, on the one hand, the lack of a shared vocabulary and by other the impossibility to bind to the descriptions the different contexts in which these descriptions are created (Brooks and Mccalla, 2006). (Forte et al, 1999) proposes a shared thesaurus of possible values in order to promote interoperability of the generated metadata.

Other studies (Motelet and Baloian, 2005; Brooks and Mccalla, 2006) suggest an ontological approach and the use of the RDF binding (Brase et al, 2003) allowing the insertion of these descriptions into a graph of concepts. Some authors show how the


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correctness of the generated metadata by automatic instruments is however approximate (Greenberg, 2004). In this sense (Cardinaels et al, 2006) proposes a formal model for the LOM which allows the definition of “fuzzy” metadata in which value of confidence is associated.

4 Automatic Learning Object Metadata Generation Different works, while stressing the importance of the IEEE LOM standard, highlight the excessive complexity of the labeling task; in fact people need time and expertise to assign all the values to the metadata attributes of the LOM schema.

For these reasons many researches look in detail the possibility of simplifying the description of learning resources by means of automatic generation of metadata. In the work of (Cardinaels, 2007) a framework for the automatic generation of metadata is proposed, that is based on a formal analysis of the nature of metadata defined in the IEEE LOM standard (IEEE, 2002).

Starting from the analysis of the learning object life cycle, it is possible to classify metadata in order to identify the set of metadata that can be obtained from the information generated by each stage of the life cycle. In particular, these information can be collected from various sources of data, e.g. the Learning Management System where these resources are used.

While some works in the definition of tools for the automatic generation of metadata are concentrated only on single issues, such as, for example, the context of use of resources, in (Cardinaels et al, 2005; Cardinaels, 2007; Lehmann, 2008) several possible sources of data from which it is possible to extract information useful for the description of the resource are analyzed.

Many works considered the authoring phase as a key element for the automatic generation of metadata. In this phase for example, the metadata can be analyzed in the light of the relationship that exists between the learning resource as a whole, and the parties that compose it.

In the works of (Hatala and Forth, 2003; Cardinaels, 2007) the metadata IEEE LOM are classified to highlight when these may be inherited by the parties or vice versa when the metadata of the parties may contribute to the definition of metadata of learning resource (accumulate metadata).

Some works look in detail how some ontological relationships between educational resources may be translated into relations between the values of the related metadata. In this sense the ontological relationships between the learning resources may generate simple rules that may facilitate the automatic generation or the validation of metadata (Motelet and Baloian, 2005). The ontological relationships between the learning resources may take an important role in other phases of the cycle of life as the design phase or stage of retrieval. Starting from the learning unit syllabus and analyzing the relationships between the resources that make it up, the LessonMapper Toolkit (Motelet and Baloian, 2006) allows to obtain a description of the resource that it intends to find or create ex-novo.

Many researches insist on the relationship that exists between the learning resource and the users and on the information that may be obtained to describe the learning


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resource from the analysis of context of use or user profile. Some authors insist on subjective nature of metadata (Duval et al, 2002) and propose indeed an active role of users in the implementation of metadata. (Brooks and Mccalla, 2006) propose a so-called “ecological approach” in which it is by analysis of the user profile that is possible to derive information useful for the categorization of the resource. The central role of users is emphasized also in those works that analyze the mechanisms of collaborative filtering and recommendation for the retrieval and the evaluation of educational resources.

The central role of users is emphasized also in those works that analyze the mechanisms of collaborative filtering and recommendation for the retrieval and the evaluation of educational resources. These works exploit social relationships between users trying to first locate people who might “…share a great deal of interests with the searching person”(Freyne et al, 2004).

5 Towards the Learning Object Management System (Fulantelli et al, 2007) highlights how the functionalities offered by Learning Object repository (LOR) are not enough to manage learning resources with a dynamic life cycle as in the case of the OpenLO model. In fact, in general the LOR uses the metadata exclusively to improve the management of categorization and retrieval of learning materials. Only in recent years, some LOR have been improved with tools that allow users to annotate and comment the resources in order to promote a collaborative process of evaluation of educational resources.

Some experiences promote a close integration between LOR and learning management system (LMS) (Fulantelli et al, 2007; Han et al, 2008); in particular, these integrated environments facilitate/allow users to find learning resources from LOR and integrate it into the learning context directly from the LMS.

Few LORs use data from the context of the use of resources, in order to complete the description of educational resources (Broisin et al, 2005), and perhaps no experience plan on using the information on the model user present in LMS to encourage the ecological approach suggested by (Brooks and Mccalla, 2006).

The dynamic life cycle of OpenLO model requires the transition towards a new kind of system called Learning Object Management System (LOMS).

LOMS are environments that facilitate the management of learning resources throughout their life cycle. Within the framework of the EU-funded sloop project, sharing learning objects in an open perspective, we have developed FreeLOms (Gentile et al, 2006), a learning object management system aimed to managing learning objects according to the OpenLO model. The main objective of FreeLOms is to provide a community of teachers with an on-line platform to share and produce learning resources collaboratively.

Two different approaches can be used to implement such kind of systems: the close integration of a LOR with other tools like authoring system, LMS to build a unique global environment; the creation of a network of services, according to a service oriented architecture (SOA) approach, to facilitate a light integration with existing systems.

In comparison to the first the second approach seems more suitable in order to create a Web 2.0 environment. Moreover, some works as (Ochoa et al, 2006; cam, 2007) move


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already in the direction of encouraging the creation of networks of services. In our vision, a LOMS is both a rich Internet application and, at the same time, a set of services accessible through the web from different applications. The goal is to make it easy to use the services provided by a LOMS, and not to impose specific software, but rather to propose a philosophy that makes the creation, management and reuse of digital educational resources efficient and effective.

For these reasons, the platform FreeLOms, in addition to providing an online collaborative environment with the features typical of a LOR, offers a series of services to facilitate the management of their life cycle of the learning resources. For example FreeLOms allows end users to access the repository as though they were accessing a shared drive in different ways through mechanisms like WebDAV, CIFS, alcohols or SharePoint protocols. FreeLOms also makes use of mechanisms of sequencing that allow you to analyze content in different formats and extract the parties and relations in order to allow a navigation of the content through different views.

6 Conclusions and future proposals In this paper we have illustrated how a dynamic vision of the metadata should be integrated in the design of a LOMS in order to improve the management of Learning Objects.

Currently our research is concentrated on the improvement of usability of the user interface of the FreeLOms platform; moreover, we have been developing a set of web services that can facilitate the management and reuse of digital educational resources in efficient and effective way. For example, in relation to integration with the LMS currently we have been developing the integration between FreeLOms and the Moodle platform. The goal is to create a set of services that allow LMS not only to use the content stored in FreeLOms, but also allow LOMS to exchange information about the context of use of the learning resources according to the dynamic metadata approach previously analyzed.

Finally, in our vision we have to explore how the informal learning opportunities created by the Web 2.0 applications can make use of learning resources. The increasingly use of social networks, allow users to interact and collaborate in new ways, and in this sense a LOMS must allows teachers and experts to create a network where they can participate collaboratively in the processes of design, development, sharing, reusing and evaluation of open learning resources.

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http://www.adlnet.org/Scorm/docs/SCORM_2.pdf Brase J., Nilsson M., and Palmer M. (2003): The LOM RDF binding - principles and implementation. In

Proceedings of 3rd Annual Ariadne Conference, Leuven, Belgium. Broisin, J., Vidal, P., Meire, M., Duval, E. (2005): Bridging the Gap between Learning Management Systems

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Brooks, C. and McCalla, G. (2006) Towards flexible learning object metadata, International Journal of Continuing Engineering and Lifelong Learning 16, 1/2, 50-63.

CAMs (2007), Conceptual Base Scheme, http://ariadne.cs.kuleuven.ac.be/empirical /attention/CAM%20schema_Document_v1.5.pdf.

Cardinaels, K. (2007): A Dynamic Learning Object Life Cycle and its Implications for Automatic Metadata Generation. PhD thesis: Katholieke Universiteit Leuven, Faculteit Ingenieurswetenschappen, Departement Computerwetenschappen, Leuven.

Cardinaels, K., Duval, E., Olivié, H. J.(2006): A Formal Model of Learning Object Metadata. In Proceeding of Innovative Approaches for Learning and Knowledge Sharing, First European Conference on Technology Enhanced Learning (EC-TEL 2006), Crete, Greece, 74-87.

Cardinaels, K., Meire, M. and Duval, E. (2005): Automating Metadata Generation: the Simple Indexing Interface, In Proceedings of ACM 1-59593-046-9/05/0005 International World Wide Web Conference Committee (WWW 2005), Chiba, Japan.

Collis, B. and Strijker, A. (2004) Technology and Human Issues in Reusing Learning Objects, Journal of Interactive Media in Education, 4. Special Issue on the Educational Semantic Web. ISSN:1365-893X [www-jime.open.ac.uk/2004/4]

Dahl, D. and Vossen, G. (2007): Learning Object Metadata Generation in the Web 2.0 Era. In Proceedings of IADIS International Conference e-Learning 2007, Lisbon Portugal.

Duval, E. and Hodgins, W. (2006): Standardized Uniqueness: Oxymoron or Vision of the Future?, Computer, vol. 39, no. 3, 96-98.

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Duval, E., Hodgins, W., Sutton, S., Weibel, S. L. (2002) Metadata principles and practicalities. D-Lib Magazine 8, 4. URL http://www.dlib.org/dlib/april02/ weibel/04weibel.html

Forte, E., Haenni, F., Warkentyne, K., Duval, E., Cardinaels, K., Vervaet, E., Hendrikx, K., Forte, M. W., and Simillion, F. (1999). Semantic and pedagogic interoperability mechanisms in the ARIADNE educational repository. SIGMOD Rec. 28, 1 (Mar. 1999), 20-25.

Freyne, J., Smyth, B. (2004): An Experiment in Social Search. In Proceeding of 3rd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, 95–103, Lecture Notes in Computer Science 3137,Springer.

Fulantelli, G., Gentile, M., Taibi, D. and Allegra, M. (2007): The Open Learning Object model for the effective reuse of digital educational resources. In Proceedings of the Openlearn 2007: Researching open content in education, Milton Keynes, UK.

Gentile, M., Taibi, D., Allegra, M. and Fulantelli, G. (2006) A collaborative “open Learning Objects” managements system. WSEAS Transactions on Advances in Engineering Education 6, 3, ISSN:1790-1979, 586-592.

Greenberg, J. (2004) Metadata Extraction and Harvesting: A Comparison of Two Automatic Metadata Generation Applications, Journal of Internet Cataloguing: The International Quarterly of Digital Organization, Classification, and Access, 6(4), 58-82.

Han, P., Kortemeyer, G., Krämer, B. J., von Prümmer, C. (2008) Exposure and support of latent social networks among learning object repository users. Journal of the Universal Computer Science 14,10, 1717-1738.

Hatala, M. and Forth, S. (2003) A comprehensive system for computer-aided metadata generation. In Proceedings of 12th International Conference of The World Wide Web Consortium (WWW2003), Budapest.

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E-portfolio and semantic web to support informal learning in social network environment

Taibi Davide, Gentile Manuel, Fulantelli Giovanni, Allegra Mario

Institute for Educational Technology, Italian National Research Council,

Via Ugo La Malfa 153, 90146, Palermo ITALY E-mail: davide.taibi;manuel.gentile;giovanni.fulantelli;[email protected]

Abstract The informal learning opportunities created by the Web 2.0 applications and the increasingly use of social networks, allow users to interact and collaborate in new ways. Students use new learning environments which are structurally different from traditional e-learning environments, in which the boundaries between the learning contexts and social spheres disappear. In these informal unstructured learning contexts, the definition of the students’ competences plays a central role. The use of software environment to model learner profiles using semantic technologies appears more and more important. In this paper we propose to extend the FOAF ontology, used to describe people and their personal relationship, with an ontology related to student portfolio used to model competencies. In particular, we integrate FOAF with the IMS Learning Portfolio model in order to support the creation of new Web 2.0 learning environment based on social networks and competencies. This type of environment is useful to manage the evolution of student educational experiences in the informal learning activities carried on in social network.

Keywords: semantic web, e-portfolio, social networks, informal learning

1 Informal learning and social communities The significant changes in society that (Castells, 2006) sums up in what he calls "The Rise of the network society" also have considerable implications in the definition of learning activities. The Information Society dramatically increases the opportunities for knowledge acquisition. Beyond the structured training activities designed by specialists in the education field, we have to consider the large number of educational opportunities related to everyday activities that define the so-called "informal learning”. In this perspective, the concept of networked learning is drastically changing. The informal learning opportunities created by information technologies, such as Web 2.0 applications and social networks, allow users to interact and collaborate in new ways thus leading to the definition of new learning environments; these are structurally different from traditional e-learning environments, since the boundaries between the learning contexts and other social spaces tend to disappear. In these unstructured learning contexts, the definition of the skills acquired by the users is a central objective. Consequently, the use of software environments that model learner profiles and can deal with them in a semantic way appears increasingly important.


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In (Lave and Wenger, 1991) the authors argue that learning is related to the activities, the environmental and cultural contexts in which it is developed and therefore social interaction is a critical factor. From this point of view learning can be described as a process: students are involved in a community of practice that represents knowledge and behavior in which students play a more active role in the cultural sphere. The concept of situated learning comes from Vygotsky’s social development theory, which affirms that social interaction has a fundamental role in the knowledge development process (Vygotsky, 1978). This theory argues that situated learning is generally unintentional and for this reason learning is more efficient if the student is a member of a community of practice he has chosen to join rather than being assigned to a group by external actors such as teachers.

The social aspect in learning activities is extremely important and leads to a further consideration. For example, (Tinto, 1997) claims that participation in a collaborative learning group allows students to develop a supporting network, that helps students to maintain relations with a wider social community.

A peer-to-peer community promotes participation in learning activities. Moreover, the communities of learners provide students with the opportunity to satisfy simultaneously both social and academic requirements. These unstructured learning contexts give rise to the need to measure and asses the acquired knowledge; the traditional competence based certification systems are not designed for this type of environment and for this reason are less suitable in this kind of educational context.

The semantic web provides a technological substrate which can overcome the limits of current web technologies, setting the base for creating ontological systems in order to model competences in informal educational contexts that are being developed in web 2.0 environments. In this paper we consider the problems connected to the description of competences in informal learning environments within social networks mediated by technologies. In particular, we propose the integration of the FOAF (Friend Of A Friend) ontology, which is used to model people and their personal contacts, with semantic ontology related to student e-portfolios used to model their competences. The use of ontologies and the surrounding semantic web technologies allow us to create relationships between the students’ ongoing educational experiences and the evolution of their social network. For this to happen, we integrate FOAF ontology with the IMS Learning Portfolio model in order to support the creation of a new Web 2.0 learning environment based on social networks and competences.

2 Social Semantic Web At present a huge amount of shared contents such as bookmarks, images, videos and photos are being created within so called web 2.0 sites. This kind of applications is very popular in social and personal spheres as well as in professional and organizational ones. They possess common features like the creation and sharing of contents (images, photos, papers), discussions (comments) and connections between users (group of friends, private messages, and so on). This scenario raises new considerations related to the sharing of social contributions between software applications and the interoperability of social networks.


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Due to the heterogeneity of the nature of social contribution sharing models, searching, connecting and retrieving these kinds of contents has become more complex. The semantic web technologies provide standards and models which are useful for creating a network of data, with unified models which can represent data from different sources appropriately. The unification of semantic web technologies and social paradigms gives rise to "Social Semantic Information Spaces" in which information is socially created and managed, as well as being interconnected and available in a machine understandable format, promoting new methodologies to discover information present on the web (Breslin, 2008).

Moreover, the semantic web offers a generic infrastructure to interchange, integrate and reuse structural data, in order to overcome the limits of Web 2.0 platforms. Currently, in fact, web 2.0 applications have search mechanisms based mainly on tags and few keywords. Adding semantics to the web would enable this kind of problem to be solved, by providing easier search mechanisms, supporting the reuse of contents and creating more connections between different types of contents. Moreover, the use of ontologies is useful to structure and elaborate information. Ontologies represents entity-relationship models related to a specific knowledge or practice domain. A typical web ontology contains the definition of classes, objects and their relationships, and a set of deduction rules that give inferential power about the concepts.

Through ontologies the semantic web provides the basis for enriching the resources description with a well defined meaning and in a comprehensible format which can be elaborated by software applications.

The strict relationship between documents produced in web 2.0 environments and the specific social network (Jung and Euzenat, 2007) bring us to consider the information objects as the result of the activities of the network; consequently, we should also represent social relationships in a well structured way, using approaches based on the semantic web concepts.

FOAF, the acronym of “Friend of a friend”, uses semantic web technologies, in particular the Resource Description Framework (RDF) and the Ontology Web Language (OWL), to define a machine-readable ontology describing people, their activities and their relations to other people and objects. FOAF is useful for describing social networks and their relationships.

3 Learner model in social semantic networks Educational activities adopt web 2.0 technologies and social networks more and more frequently. The interaction paradigms at the basis of web 2.0 technologies and social networks are different from those adopted by conventional e-learning tools.

FOAF is considered the most common vocabulary for constructing social networks, it has been very successful in the applications that use semantic web technologies, and it is useful to model learner in social networks (Ounnas et al., 2006).

Each student can be described through an FOAF file that can be extended and modified at any time. This is useful, for example, for publishing data regarding students using the URI that represent them. To facilitate the creation of the profiles it is possible to use an interface based on foaf-a-matic; in this way, it will be possible to describe social


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links in the community of practice. Defining ontologies it is possible to use a inferential engine like Jena and the SPARQL language to work with data and generate new knowledge about the domain. As reported by (Ounnas at al., 2006) there are several advantages in using the FOAF approach to model student profiles:

• the use of RDF facilitates extensibility and interoperability • the presence of different extensions of the FOAF vocabulary, makes FOAF very

flexible • the creation of FOAF files is simplified by the use of foaf-a-matic • FOAF simplifies the identification of people with common interests, which is

essential for creating communities of practice To use FOAF in a learning context, it is necessary to extend this model to include

specific characteristics related to learning. Regarding this aspect we should take into consideration elements related to: the extension of the FOAF vocabulary to include specific information regarding students’ activities; the consideration of privacy problems in sharing personal information; the evaluation of the ties strength between students belonging to the group.

In conclusion, using FOAF as a basis for learning models makes it possible to exploit the benefits of the numerous existing tools, and also to use the extension of the model to define specific aspects and personal and group relationships, which are indispensable for creating and supporting social learning networks.

FOAF is used successfully to describe a student’s profile, in particular the profile can be extended to bring together information coming from other models containing student data, like, for example the competences described following the IMS e-portfolio standard.

The model of students’ competences plays a key role in making the use of social networks to support learning activities more efficient.

4 e-portfolio and ontologies in social learning environments An e-portfolio is defined by the EDUCAUSE NLII (National Learning Infrastructure Initiative) as "a collection of authentic and diverse evidence, drawn from a larger archive, that represents what a person or organization has learned over time, on which the person or organization has reflected, designed for presentation to one or more audiences for a particular rhetorical purpose."

As sustained by (Mason et al., 2004), an e-portfolio can be used to developmental, presentation, assessment purposes, and it can contain different information related to personal and professional achievements, competences, digital works. This relevant information about students can be stored and maintained by different institutions in different sites, so the management can be improved by the use of web-based e-portfolios. A key concept in this scenario is the interoperability between different institutional systems which requires a unified model describing students’ e-portfolios.

The pedagogical objectives of e-portfolios are various: they allow students to describe their learning path, increase awareness of their strengths and weaknesses, take responsibility and increase their autonomy and have a unified way of presenting their competences.


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At present, the lack of common standards to describe e-portfolio information means that most e-portfolio systems are using different proprietary formats to store this type of information, and moreover, they don't provide features for importing and exporting e-portfolio information from other systems. In this scenario the interoperability between e-portfolio systems is hindered, and for example, it is difficult to integrate the e-portfolio information coming from a university system and from an enterprise.

For these reasons it is desirable to use a common standard in order to unify the description processes of competences in lifelong learning.

There are two main standards for describing student learning experiences. The IEEE Learner Model working group has defined the Public and Private Information for Learners (IEEE P1484.2.1/D8, 2001) as a standard for a student model, with the aim of gathering information related to competences, personal data, learning style, and so on. This standard considers six types of data related to personal, Relations, Security, Preference, Performance and Portfolio information; in addition, it is possible to extend and integrate the standard in order to enrich the student description.

In 2005 the IMS consortium released the (IMS e-Portfolio Best Practice and Implementation Guide, 2005). This specification uses the XML language to define the characteristics of an e-portfolio. XML is at the basis of the semantic web layer cake, so this specification constitutes the first step towards a semantic description of student competences. The use of specific ontologies can enrich this description by considering also the relationships between the concepts that are at the basis of e-portfolio systems.

An e-Portfolio can bring together different kinds of information such as: digital and non digital works; activities in which the student has participated, is participating, or plans to participate; competences and skills of the student; student’s achievements, whether or not certificated; student's preferences; student's goals and plans; student's interests and values; any notes, reflections or assessments relevant to any other part; the results of any test or examination taken by the student; contextual information to help the interpretation of any results.

5 Semantic framework for e-portfolio management Many educational approaches are based on groupwork, since peer learning promotes cognitive processes. There are many different kinds of collaborative work that allow students to learn in different modalities, such as group discussions, group problem solving and group study. The form of collaboration differs according to the duration, the complexity and the level of collaboration.

Social interactions can help students to share their experiences and to work collaboratively on relevant topics. In this sense social networks occupy a key role in the learning dynamics. The number of informal learning activities which take place in technology supported social networks is constantly increasing.

Collaborative group activities are frequently used by teachers in the educational curriculum. In these activities it is necessary to create well balanced groups with the aim of maximizing the attainment of the learning objectives.

To ensure the success of a learning activity, teachers must consider the constraints that can affect the entire group or an individual performance, such as previous experiences by students in similar educational contexts, cultural background or interests and competences.


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The importance of a system based on competences in informal learning environments such as those developed using social software is undeniable. For example, there are clear benefits in involving members with different levels of experience within the group in order to improve the dynamics of collaborative work in problem solving activities.

From this point of view it is increasingly important to have software applications that can store data related to the user profiles and process these data semantically.

The approach proposed in this paper consists in integrating and extending FOAF ontology, used for modeling contacts and personal relationship, with semantic data related to students’ competences.

Enriching the description of social networks using semantics can provide precious information to support teachers in leading to a more efficient use of the network for educational purposes. Social learning experiences must consider the competences and the e-portfolio of the participants, so web semantic technologies are an essential substrate for merging models related to the social network description with models used to define and structure competences.

In particular, the use of ontologies and semantic web technologies makes it possible to relate the evolution of educational activities experienced by the students with their relationships.

The description of a students’ social network using FOAF, integrated with the definition of competences by means of the IMS model, is the basis for the creation of a competence based ontological system for virtual learning environments using social networks and web 2.0 technologies. The result is a learning environment which is no longer based on the transmission of information from teacher to student but rather is focused on the ability of the students to play an active role in their learning activities.

6 Conclusions Collaborative group activities are frequently used by teachers in the educational curriculum. In these activities it is necessary to create well balanced groups with the aim of maximizing the attainment of the learning objectives.

To ensure the success of a learning activity, teachers must consider the constraints that can affect the entire group or an individual performance, such as previous experiences by students in similar educational contexts, cultural background or interests. The greater the number of constraints to consider, the more complex becomes the management of the learning experience.

Semantic web technologies offer the substrate needed to overcome the problems of social network with large groups of students. The versatility of these technologies means that they can be successfully applied for describing social networks and competences in learning experiences.

An interesting approach for creating an ontological system based on semantic web technologies that makes it possible to define a social network considering the competences of participants, the quality of the group and its robustness, is based on the use of an ontology as a result of an extension of the FOAF vocabulary, to create a semantic data base including specific references to educational paths.


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In particular, the approach proposed in this work is based on the creation of a specifically designed ontology that extends FOAF ontology, in order to describe the domain of competences as defined by the IMS e-portoflio standard.

REFERENCES

Backstrom, L., Huttenlocher, D., Kleinberg, J. and Lan, X. (2006): Group formation in large social networks: membership, growth, and evolution. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, New York, NY, USA, 44-54.

Breslin, J.G. (2008): Social Semantic Information Spaces. In S.R. Kruk and B. McDaniel (Eds): Semantic Digital Libraries. Springer.

Castells, M. (1996): The Information Age, Economy, Society and Culture Volume I: The Rise of Network Society. Blackwell, Oxford.

IEEE P1484.2.1/D8, (2001): Draft Standard for Learning Technology — Public and Private Information (PAPI) for Learners (PAPI Learner) — Core Features Sponsored by the Learning Technology Standards Committee of the IEEE Computer Society.

IMS ePortfolio Practice and Implementation Guide (2005), IMS Global Learning Consortium. Jung, J., Euzenat, J. (2007): Towards Semantic Social Networks. In Proceedings of the 4th European

Semantic Web Conference, Innsbruck, Austria,267-280. Lave, J. and Wenger, E. (1991): Situated Learning: Legitimate Peripheral Participation, Cambridge

University Press. Liccardi, I., Ounnas, A., Pau, R., Massey, E., Kinnunen, P., Lewthwaite, S., Midy, M., Sarkar, C., (2007):

The role of social networks in students' learning experiences. SIGCSE Bulletin 39,4, 224-237. Mason, R., Pegler, C. and Weller, M. (2004): E-portfolios: An assessment tool for online courses. British

Journal of Educational Technology, 35,6, 717-727. Ounnas, A., Liccardi, I., Davis, H. C., Millard, D. E. and White, S. A. (2006): Towards a Semantic Modeling

of Learners for Social Networks. In Proceedings of the International Workshop on Applications of Semantic Web Technologies for E-Learning (SW-EL) at the AH2006 Conference, Dublin, Ireland.

Tinto, V. (1997): Classrooms as communities: Exploring the educational character of student persistence. Journal of Higher Education, 68,6, 599-622.

Vigotsky, L.S. (1978): Mind in Society. Harvard University Press. Cambridge.

Integration of Multimedia in class work and lab activities

Carmen – Gabriela Bostan1, Ştefan Antohe1

(1) University of Bucharest, Faculty of Physics, Physics Doctoral School,

405 Atomiştilor, P.O.Box: MG-11, Măgurele-Ilfov, 077125, România E-mail: [email protected], [email protected]

Abstract Physics laboratory has for a long time an important tool of school physics education process and it must still remain in any physics curriculum at primary, secondary, high-school and academic level, too. In addition, in last time, the informatics technologies (IT) known an explosive development and the students at any level, are fascinated by these. Particularly, the Multimedia (MM) tools have an important impact for the teaching – learning process of Physic, and they could be successfully integrated as MM activities in school work, home-work and in distance learning, respectively. The Computer Assisted Instruction stimulates the visual hearing memory and transposes the students in the middle of physical phenomena. The realism of dynamical pictures, the video joined with the sound and the motion, the possibility to recreate the physical reality with digital technique make the didactics movies the most important teaching tools. In firs parts, of this paper we explained why important is to use simulated experiment. In succeed step, we propose a scenario of the lesson plan and we are illustrated how the teacher can perform, by integrated audio – video tools, an efficient instruction in different stages of unit lesson, using specialized software to create simulations of physics experiments. Keywords:Virtual physics laboratory, Information Technology in physics, Multimedia activities, teaching/ learning physics.

1 Introduction In the last years, the developing of a new technologies meet unrecorded progress, forcing us to adapt to these challenges, whose main characteristic is complexity. To cope with continuous change and uncertainty characteristic of market economies, students need strategic skills, such as the ability to learn how to learn, skills to solve problems, assessment skills.

The informative and technologies society needs important changes in educational programs. Learning physics is difficult for many students and, by using the Technologies of Information and Communication, introduces Physics in a modern and attractive way. Computers are used in different ways to teach Physics and can affect drastically the way of teaching Physics (de Jong, 1999; Iskander, 2002; Esquembre, 2002; Almeida Barretto et al, 2003).


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Due to the rapid development of information and communication technology our society can be considered as “network society”, meaning a society in which access to information is made via modern means of communication and use of information requires the success of any approach. The famous “Time is money”; is complemented by “knowledge is power” and if we add to this “We intercommunicate, so that we exist”, then we can express the reality of the contemporary world.

In such a society, where you find the information thorough, you should be able to decide what information helps us in our work, to adopt a variety of methods to search, sort, organize and present data to make interference information in a logical manner, to apply knowledge already gained to discover new ones. In schools, information technology and communication can be more than just a means of education; can become a concept to make radical changes in education. Its potential to improve the quality and standards of performance of participants in the educational process is significant. The class isn’t made with chalk on the black board and traditional means; in the interactive class, we will corroborate diverse teaching means, so traditional to modern tools. It is better that the teacher stimulate the students. The teaching will be better if they “play” than a discourse, in which we present the new information (UNESCO, 1983; Popa, 2005).

The computer can become a tool for all those who wish to find in him a friend and the mysteries will turn into knowledge. This tool is equally useful to student and teacher. Computer used in class aims to develop skills related to communication, procurement, presentation and transmission of information in forms as varied. The Crocodile Physics program allows simulation of experiments that cannot be completed in class, completion of laboratory experiments, to realize animated graphics, contributing in this way to develop skills to organize specific information and use it to produce new knowledge.

Physics is par excellence an experimental object, but many of the phenomena are too fast to be studied and understood fully, or it can not be done in a laboratory school. Via computer it can be simulated and presented these phenomena so that they can be pursued by each student. On the other hand it is known that the possibility of understanding of material is different from one individual to another, not all students can understand it. The computer gives everyone the opportunity to adjust the learning of new knowledge in their own pace and the quality of learning and deep understanding of the phenomena will increase incontestably.

Introduction of the computer in the didactical activities going to increase students motivation in learning physics, offers alternative suggestions for the teaching-learning, the approach to issues of physical phenomena, encourages creative and critical thinking, and the students will be develop skills for processing and presenting of information.

2 Method 2.1 Theoretical Background Movement on the slope is teaching to ninth grade to the students of 15 years.

The slope is a simple machine, used to raise the certain big mass at another height. It is found in nature in the form of slopes to be climbed or descended by foot or with various devices.


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It supposed that an object of mass m, slide freely on an incline of angle α. In illustrations (Figure 1) of physical situations, sometimes called space diagram, force vectors may be drawn at different locations to indicate their points of applications. However, because we are presently concerned only with linear motions, vectors in free-body diagrams may be shown as emanating from common point, which is usually chosen as the origin of the x-y axes (Pearson International Edition, 2007).

A module by forces acting on it is calculated according to formulas:

[1] gmG ⋅= , weight object

[2] αsin⋅= mgGt , tangential weight of the object

[3] αcos⋅= mgGn , normal weight of the object

[4] NFf ⋅= µ , strength of the sliding friction

We applied the Newton's second law and it get

[5] ft FGma −=

[6] nGN −=0 Acceleration to downlink is calculated by the formula

[7] ( )αµα cossin ⋅−=−

= gm

FGa ft

[8] AA cpA EEE += Total Mechanical Energy in point A; the total mechanical energy

E to be the sum of the kinetic and gravitational potential energies [9] hgmE

Ap⋅⋅= initial Gravitational Potential Energy

[10] 02

2

=⋅

= Ac

vmE

A Kinetic Energy, initial Kinetic Energy equal to zero,

where Av is initial velocity [11]

BB cpB EEE += Total Mechanical Energy in point B

[12] 0=Bp

E final Gravitational Potential Energy equal zero

[13] 2

2

Bc

vmE

B

⋅= Total Mechanical Energy in point B

where Bv is final velocity [14] αµµµ cos⋅⋅⋅⋅=⋅⋅=⋅⋅=⋅= dgmdGdNdFL nf

Work Done by friction

[15] LEE BA +=

Figure 1 Free-Body Diagram


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The Law of conservation of total energy: In a conservative system, the sum of all type of kinetic energy and potential energy is

constant and equals the total mechanical energy of the system. Or The total energy of an isolated system is always conserved. In our case,

[16] AB EEL −= , the system is not conservative, friction is a nonconservative force. Otherwise, if

[17] BA EEL =⇒= 0 , conservative system

2.2 Experimental Background We will be use the experimental kit, the tribometer and the objects with different surfaces of contact (Figure 2).

The experiment is carried out on front or groups of pupils.

2.3 Computational Background The audio – video tools are technical equipments that permit the stock up of the image and their future reproduction (Nicola, 1994; Jinga and Vlăsceanu, 1989).

The software that will be used is Crocodile Physics 605, is dedicated simulation software for physics experiments.

The simulation will be in front, the teacher will present it on the electronic board or video projector. If the school has a physics lab with a computer on each table, the experiment can be practiced by each student.

2.4 Didactical Methods Teaching methods used are: explanation, conversation, experiment, demonstration, discovery, computer modeling.

3 Delineate of Lesson The unit by learn: Simple mechanisms The form (gradual level): the class-9th grade (the student’s age – 15 years old) The name of lesson: Inclinated plane The type of the lesson: teaching/ learning The didactical tools: video, TV, experimental kit and after, completed with

simulation on the computer (Crocodile Physics) The didactical intention: learning notions of motion on slope; force vectors,

acceleration of the body at motion on slope, conservation of energy. Instructions for teacher and the students: – The teacher will verify the knowledge, which the students must learn.

Figure 2 Tribometer


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– The teacher will make connection with the new lesson. In this moment the teacher can use the audio – video means or the training films, can tell a joke about babies in sleighing, or something.

– The teacher starts a practical activity. Activities include mechanical kit and the students must observe, practice and draw conclusions.

– The teacher must guide the students to draw conclusions, to generalize their observations.

– The teacher starts a simulation on the computer (Figure 3, Figure 4, Figure 5).

[18] NFf 53.5= [19] md 1,1≈

[20] NdFL f 83,5≈⋅=

[21] NEA 83,14≈

[22] NNNEEEBB cpB 95,45,4 =+≈+=

[23] NNLEE BA )83,59(83,14 +=⇒+= is true

Figură 4 Conservation of Total Mechanical Energy

[24] NEA 15≈

[25] ( ) NNEEE

BB pcB 155,75,7 =+≈+=

[26] BA EE = is true

Figure 3 A Nonconservative System


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Figure 5 Velocity-Versus-Time Graph The teacher writes on the board the equations on the board, the law of motion, draw

the diagrams and the students write it in their notebooks. The students identify other application for the motion on slope.

4 Discussion On computer simulation of motion on slope, reveals as follows:

– Forces – vectors and forces modules;

– Diagrams )(tfv = ), )(tfEc = , )(tfEp = (Figure 3, Figure 4, Figure 5);

– Conservation of Total Mechanical Energy (Figure 3, Figure 4). Advantages: – To gain time; – Completing and fixing the knowledge acquired through classical experiment; – Experimental data more accurate. Disadvantages: – Passive participation in front simulation; Computer simulation of physics experiments is well come as a complement to

classical experiments on laboratory, together leading to a deep learning, for the duration.

5 Conclusions A good lesson, a successful one is achieved when the teacher and the students work together. The teacher must choose the appropriate teaching methods, types of activities and interaction by taking into account the level of his/her students, the materials he/she has and the goals. Activities can include so experiments and other modern tools, like audio – video tools, when the students must observe, practice and draw conclusions. They can watch training films, make use of maps, cards, pictures, real objects and other teaching tools. Methods used must vary, according to the topic, the students' response or moment of the lesson where they are used. It is good traditional and modern methods as


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well, like: demonstration, problem-solving, observation, conversation, learning through discovery, modelling on the computer, didactic games on the computer or practical games. The lesson will prove to be successful if the students understand the concepts and use them in exercises and problems. The teacher can avoid improvised or useless activities and stimulate his students to progress gradually, by avoiding boredom and lack of interest, wasting time and effort. The lesson must contribute to their systematic knowledge and to their maturity. The information they learn must be used in everyday life, so that teaching and learning can connect with their life.

The audio – video tools make an interactive lesson, the students haven’t time to bore, and they wake up the interest in a nice manner. It isn’t must insisted, the modern tools must combination with the traditional tools for a dynamical lesson, not monotone. It is danger that the students “sleep” in the class.

The access to the different soft, the access to the Internet or other information means determine that the student’s evaluation isn’t only traditional also: memory the lesson or resolve the problems. In this time we can assess the student’s portfolio or the student’s individual paper or team paper.

In this way the audio – video tools have one important impact for the teaching – learning processing of Physics and the Computer Assisted Instruction stimulates visual memory and hearing memory and transposes the student in the thick of the Phenomena.

REFERENCES Books: Jinga, I., Vlăsceanu, L., (1989), Pattern, Strategy and Performances in Education, Editure Academy. Malinovschi, V. (2003), Didactics of Physics, E.D.P., R.A. Bucureşti. Nicola, I. (1994), Pedagogy, E.D.P., Bucureşti. Pearson International Edition, (2007), Sixth Edition College Physics, WILSON BUFFA LOU, Pearson

Prentice Hall, Upper Saddle River, New Jersey 07458 Popa, M. (2005), Interdisciplinarity Evaluation, Piteşti; Editure Delta Cart EducaŃional. Tereja, E. (1994), Teaching Physics’ Methods, Iaşi; Editure University „Al. Ioan Cuza”. UNESCO, (1983), Interdisciplinarité et sciences humaines, UNESCO, (ouvrage collectif), vol. I. Văideanu, G. (1985), Interdisciplinarity Promotion in the Pre-University Level, Iaşi; Editure University „Al.

Ioan Cuza”. Journal Articles: Almeida Barretto, S.F., Piazzalunga, R., Guimaraes Ribeiro, V., Casemiro Dalla, M.B., Leon Filho, R. M.

(2003), Combining interactivity and improved layout while creating educational software for the Web, Computers & Education, Volume 40, Issue 3, pp. 271-284, April.

de Jong, T. (1999), Learning and Instruction with Computer Simulations, Education & Computing, 6, pp. 217-229.

Esquembre, F. (2002), Computers in Physics Education, Computer Physics Communications,147, pp.13-18. Institute Pedagogical Sciences, (1970) Interdisciplinary Research in Education. Iskander, M. F. (2002), Technology-Based Electromagnetic Education, IEEE Transactions on Microwave

Theory and Techniques, V.50, no. 3 pp.1015-1020, March. Internet Sources: http://www.yenka.com/ Computer Programs: Crocodile Physics 605

Using data mining techniques in higher education

Elena Şuşnea1

(1) National Defence University "Carol I", Bucharest, 68-72 Panduri St. Bucharest 5,

ROMANIA E-mail: [email protected]

Abstract Data mining (DM) is useful for collecting and interpreting significant data from huge database. The education field offers several potential data sources for data mining applications. These applications can help both instructors and students in improving the learning process.

Keywords: Data Mining, Education, k-Means Algorithm

1 Introduction Development of educational means has become a priority for most member states and the rate regarding higher education presents a tendency increased globally.

Also, universities need to develop a special interest in using ICTs in education:”the application of ICTs to teaching and learning has great potential to increase access, quality and success” (UNESCO, 2009).

Following this direction, the use of e-learning technologies has grown to be an alternative solution to improve traditional education. E-learning systems allow collecting huge quantities of data that can be used both by universities and other institutions. The educational database can provide personal information regarding the users’ profiles, their academical grades, and also data regarding interaction among different users.

The KDD process (knowledge discovery in database) can be very useful in the student-centered educational system due to the fact that the information from educational database allow improvement of the teaching and learning level, also improvement of the students’ grades, better understanding of students’ behavior, adjusting the curriculum to the students’ needs, improvement of the quality of educational management etc. This information can be presented as rules, graphics, decisional trees and networks.

Within the KDD process, there can be used different means of DM analysis, that allow getting important information from the database such as: Bayes classifiers, association rules, tree decision, neural networks, genetic algorithms, support vector machines, clustering etc.

Next, we are presenting some aspects regarding the existing differences between models and patterns, and after that a detailed description of k-means method (frequently used in DM), and an application of this method in the educational field.

2 General aspects regarding discovery of models and patterns within the database

The DM process consists mainly in discovering some ”valid, new, possibly useful and comprehensible” structures from the dates (Fayyad, U.M., Pitatesky-Sapiro et al, 1996).


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The structures discovered during the DM process can describe the entire (the most of the) set of data and they are called models. There are also cases when the structures discovered get some local properties of the data, and in this case the term of ”pattern” is used.

From the geometrical point of view, we can represent the set of data by using an pn× matrix, where n is the number of samples (logins) and p is the number of

characteristics (variable or attribute). Thus, for each sample, a number of p measurements, represented by a p-dimensional vector. The set of data X can be used

under the form ,...,, 21 nxxxX = . If the structure discovered in the p-dimensional space is a model, then we can get

information for each point in this space and thus for each sample. In case some values of the characteristics are missing (the vector is incomplete), these can be determined by customizing the model. In linear regression, a simple model could have the forma

baYZ += , where Y and Z are variable, and a and b are the model parameters (constants determined during the DM process) known as regression points.

Unlike the models, the pattern structures provide information regarding some areas of

the p-dimensional space. For example, a statement as the following if aYi > then

1)( pbYprob j => has certain constraints imposed to the values of the variables Yi and

Yi. From a semantical point of view, the relationship is equivalent to

1)( paYbYprob ij =>>. For example, a database research can show that the family

income is a decisive factor for education. Such a research [Kane, J. 1970], that aims to identify the major risk factors in predicting the students’ grades (passes/failed), shows a strong positive connection between the family income and other attributes that characterize the family educational accomplishments: admission, perseverence and graduation. For example, the students with poor financial status have a much reduced class attendance as compared to the students whose families provided a medium income. Thus, we can identify a group of logins (pattern) different from the others (which can be considered a central cloud in the p-dimensional space).

The distinction between models and patterns is useful in many cases. Although, sometimes it is not clear whether a certain structure should be considered a model or a pattern.

3 DM techniques used in e-learning The problem regarding the educational curriculum is present and complex, leading to opinions, theoretical solutions and practical ways of applying, sometimes different, and even contradictory. In a restricted way, a curriculum represents all the official school documents that contain the main information regarding guiding of the educational process. The core of the curriculum consists of the teaching objectives. They are ”are specific statements about exactly what a student should know, be able to do, or value as a result of accomplishing a learning goal” (Reed, 2005).


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By using DM techniques, we can get new valid reports, even comprehensible models from the databases available in higher education. The discovery o hidden patterns allows the development of some good decisions and also has the advantage of being student-centered. In this way, the educational process can be improved according to the discovered models and patterns.

Next, we are presenting the clustering, that is a DM technique often used when creating a classifying model, and then we are showing an example on how this techinique can be used for deviding the educational database in homogenous groups. For example, by using the clustering we can identify the main elements for creating and producing of the educational curriculum within an e-learning system.

As far as the automatic learning is concerned, clustering represents an unsupervised learning method. Unlike the classification, which involves the existence of some predefined training classes and clusters meant to develop some predictions, clustering has a descriptive target and learning is done by observational learning, instead of exemplifying learning.

The main objective of the clustering process consists of deviding the data set so that the distance among the clusters should be minimal, whereas the inter-cluster distance should be maximal. In order to verify if two objects are similar or not, we use two types of measures: similarity measures and dissimilarity (distance) measures. Often, in order to determine the dissimilarity ratio between certain objects, we use euclidian distance.

The database can be devided through clustering methods either by using partition-based methods, or hierarchical ones. One of the methods frequently used in data partition is the k-means data.

The k-means algorithm is the easiest and the most common algorithm based on squared error criterion. This represents a simple clustering procedure that desires to minimize J criterion function in an iterative way:

[1] ∑ ∑= ∈

−=k

j Cnjn

j

xJ1

2µ

where, k is the number of clusters, and jµ represents the point average of jC

cluster and it is given by

[2] ∑∈

=jCn

nj xN

1µ

This criterion measures how well represented the X data set is by the cluster centers ,...,, 21 nµµµµ = . The methods that use such a criterion are called minimum variance

methods (Duda et al., 2001). The algorithm can be summarised as it follows: Step 1. defines k, the number of clusters to which the data set should be partitioned Step 2. initializes the clusters, providing a random set of k logins that will initially be

considered centers Step 3. finds the closest cluster center for each login. Usually, the ”closiness: of the

cluster center is determined by using the euclidian distance.


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Step 4. for each of the k clusters, the average is determined [2] and each sample is allotted to the appropriate cluster according to the nearest average obtained.

Step 5. repeats step 3 till convergence or finish point. There are two major stept in the

algorithm, identifying the distance among all the points and center re-evaluation. The cost is determined according to the number of iterations as it follows:

[3] )( InkdOT = where n represents the number of points, k the number of clusters, and I the number of iterations.

Case study Course Management Systems

(CMS), offers a variety of channels and working spaces in order to improve information sharing and communication among a course participants. This system collects huge quantities of information which are very useful for the analysis of the educational process. Traditional

analysis of the data within the e-learning system is based on ”hypothesis or assumptions” (Gaudioso, E., Talavera, L., 2006) meaning that the analyst starts with data exploring according to personal intuition, whereas data mining allows an inductive approach with automatic discovery of some patterns hidden within the database.

The study has been conducted in 5 institutions of higher education that dispose of the CMS system, such as Moodle, Ilias or Blackboard. 200 students have been questioned.

By using the k-means algorithm we have realised 3 clusters taking into account the study year and the answer to the question ”How much do the teaching objectives stated in the educational plan and analytical program correspond to your aspirations?”.

In Figure 2 we have presented the dissimilarity matrix. Based on the dissimilarity criterion, we can determine the three clusters (Figure 3 and Figure 4).

Figure 2. Dissimilarity matrix

Figure 1. Development of cluster centers during

the iterations (Duda et al.)

Figure 3. Information regarding cluster centers


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Figure 4. Medium distance within the clusters It can be noticed that there is a bigger dissimilarity between clusters 1 and 3 and a

bigger similarity between the elements belonging to cluster 1. The disadvantage of using k-means algorithm is represented by the fact that ”best

number of k clusters is not known, as it is chosen relatively as an initial value of the algorithm” (Molder, C., 2004).

4 Conclusions The development of some adequate and efficient teaching strategies is not a simple operation. It implies a contextual, original and unique combination of the elements of the entire teaching-training process. Lately, most teachers with an open mind regarding the teaching methods, have begun to reorganize their classes, tackle new topics, and present the contents in a dynamic form so that to make the students get better scores.

REFERENCES

Duda, R. O., Hart, P. E., Stork, D. G. (2001) Pattern Classification, second ed.John Wiley & Sons, Inc. Fayyad, U.M., Pitatesky-Sapiro, G., Smyth, P., Uthurasamy, R., (1996): Advanced in Knowledge Discovery

and Data Mining, AAAI/MIT Press. Gaudioso, E., Talavera, L., (2006). Data mining to support tutoring in virtual learning communities:

Experiences and challenges, In C. Romero & S. Ventura), Data mining in e-learning, Southampton, UK: Wit Press.

Kane, J., (1970): College entry by blacks since 1970. The role of college costs, family background and the returns to education, J. Political Econo., 102: 878-911.

Khan, B.H., Web-based Instruction (WBI): What is it and Why is it? In Web-based Instruction, Engelwood Cliffs, New Jersey: Educational Technology Publications. http://www.odysseylearn.com/resource/ emod.html

McLachlan, G.J., Krishnan, T. (1996), The EM Algorithm and Extension, Wiley. Molder C. (2004), Recunoașterea formelor. Metode de clasificare, Editura Academiei Tehnice Militare,

București. UNESCO, Paris, (5-8 July 2009), 2009 World Conference on Higher Education: The New Dynamics of

Higher Education and Research For Societal Change and Development. http://sacs.utdallas.edu/sacs_glossary

Classification techniques used in Educational System

Elena Şuşnea

National Defence University "Carol I", Bucharest,

68-72 Panduri St. Bucharest 5, ROMANIA E-mail: [email protected]

Abstract Using classification algorithms can lead to discovering relevant knowledge contained in educational databases. These findings can be used for providing feedback to learners in the educational process. Keywords: Data mining, Classification algorithms, Educational databases

1 Necessity to use data mining methods in WBI

Web-based instruction (WBI) is an alternate solution for the traditional classroom-based education. WBI is ”an innovative approach for delivering instruction in online using the WWW as the instruction delivery system” [Khan, B.H..].

The tendency of using web-based educational technologies has grown a lot during the recent years, causing the development of long-distance study programs and growth of the number of students enlisted in this program. In this way, there have been created different means in order to share and present the digital content (texts, animations, simulations, graphics) as well as means for synchron and asynchron communication between teachers and students (e-mail, chat, forums, wiki).

On-line platforms, known as LMS (Learning Management System), as well as WebTC, Moodle, Ilias, IBM, have been projected in order to automize and conduct WBI training activities. LMSs are software programs on installed servers used for managing, sharing and checking the activities in progress within a certain e-learning environment. The main LMS functions are: recording and management of the users, of the training resources and activities; access verifying; realizing a good management of communication means (forums teleconference). In general, an LMS does not include possibilities of content creation and management.

In order to create digital contents for courses, it is necessary to use an LCMS (Learning Content Management System). An LCMS is a technology focused on ”development, management and publishing of the content” which is usually used in training via an LMS.

Within WBI, the systems previously mentioned generate daily a huge quantity of information that analysed through adequate data mining methods can provide valuable information regarding understanding of students’ behavior, assessing the students’ learning process, error detecting etc.


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2 Classification methods used in the educational system As we have already seen in the previous section, WBI generates huge quantities of data that analysed with adequate DM instruments can lead to the development of the educational process and also of the students’ grades.

Data mining is the process that analyses the data from different points of view and summarizes the results as useful information. This is defined as ”nontrivial process of identifying valid, novel, potentialy useful and ultimately understandable patterns in data” [Fayyad, U.M., et al.].

Another phase of the DM process, leading to data modeling is data understanding and data preparation.

Many of the recordings from an educational database are unprocessed, incomplete and noisy. For example, it may contain: fields that are obolete or redundant, missing values, wrong values, extreme values, data in a form not suitable for DM models, values not consistent with policy. Such data need to be cleaned and transformed in order to be used in modeling.

Data modeling involves using certain techniques in order to describe the patterns already existing within the database. This phase also implies the use of some DM techniques as it follows: supervised-learning techniques (Bayesiane methods, Decision Trees, Neural Network, Support Vector Machines) or unsupervised-learning teachniques (Clustering, Asssociation Rules). A certain technique is chosen according to the intended target (description or prediction) and also according to the data type. In case the data are numerical, then we can say that we have a regression problem, otherwise, we have a classification problem. Next, we will focus on the classification problem.

The classification process is based on the following main components: • label attribute – represents the labels that will be used for the classified data. They

belong to a category dependent variable (characteristic, attribute). • predictor attribute – represents a set of independent attributes based on which

classification is done. • training data set – contains values for the two previous components. It is used for

data training so that it should recognize the corresponding class according to the available predictors.

• testing data set – contains new data that are to be classified following the previously built model.

Formally, the classification problem is the following: „Let

mXXX ,...,, 21 (predictor attributes) and C (label attribute), be random variables

has domain dom(Xi), mi ≤≤1 , respectively dom(C)=c1,c2,…,cj. A classifier is a function

[1] )()(...)()(: 21 CdomXdomXdomXdomf m →××× .

Let be )','( CXP be o probability distribution on

)()(...)()( 21 CdomXdomXdomXdom m ×××× and let ).,,...,.,.( 21 CtdtdXXtdXtdtd m=

be a transaction randomly from P. )','( CXP is probability that

'),...,.,.( 21 XtdXXtdXtd m ∈ and '. CCtd ∈ .”


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In particular, if , 21 ccC = , then we say that we have a decision tree. Decision trees have as objective identifying a set of independent variables whose data will be then splitted by deviding the set of original data in two subsets of dependent variables.

An example of traning data set is shown in Figure 1. and a sample classification tree is shown in Figure 2.

Figure 1. Example of traning data set

Figure 2. Examples of classfication tree By using the modules for the decision trees, made available by SPSS, for the above

data we can build a decision tree taking into account at the top level that the root of tree contains all the recordings from the database. The second level represents the first partition of the data according to the most important factor suggested by the algorithm. The following levels repeat the partition procedure from the second level.

The ”age” attribute is a factor applied only to the students enlisted in a military university.


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The algorithms used in classification based on decision trees conduct researches such as top-down, recursive, greedy within the space of all possible decision trees.

The criteria used in deviding the decision trees are the following: entropy, GINI, chi-square.

Decision tree metods are robust to errors, including both errors in classifying the training data set and errors in the attribute value that describe this data set.

3 Concluding remarks The classification can fi used to better understand student’s behavior, to assist instructors, to improve teaching, to evaluate and improve e-learning systems, to improve curriculums and many other benefits (Romero, C., Ventura, S., 2008).

The purpose of this paper was to stress the necessity of using DM models within WBI and then to present some aspects regarding the use of classification trees in the educational field. Moreover, there are also other data mining techniques that can be used to discover different patterns for identifying some methods in order to support adaptive instruction by adjusting the teaching content, the teaching units etc to the student’s knowledge parameters.

REFERENCES

Fayyad U.M., Pitateskey-Shapiro, P., Smyth and Uthurasamy R. (1996): Advanced in knowledge discovery and data mining, AAAA/MIT Press.

Grabmeier, J., Lambe, L. (2007): Decision trees for binary classification variables grow equallyy with the Gini impurity measure and Pearson’s chi-square test, International Journal of Business Intelligence and Data Mining, 2, 213-226.

Han, J., Kamber, M. (2006): Data mining: Concept and techniques (2nd ed.), Boston, , MA: Elsevier. Khan, B.H.., Web-based Instruction (WBI): What i sit and Why is it? In Web-based Instruction,

http://www.odysseylearn.com Romero, C., Ventura, S., (2008): Data mining in course management system: Moodle case study and tutorial,

Computer & Education, Vol. 51, No. 1, pp. 368-384. http://en.wikipedia.org/wiki/Learning_management_system

Intelligent Agents as Data Mining Techniques Used in Academic Environment

Irina Tudor1, Liviu Ionita2

(1) Petroleum-Gas University of Ploiesti, Department of Informatics, Bd. Bucuresti, No.

39, 100680, ROMANIA E-mail: [email protected]

(2) Petroleum-Gas University of Ploiesti, Department of Informatics, Bd. Bucuresti, No. 39, 100680, ROMANIA


Abstract A knowledge-based society determines organizations to focus their activities on improving management quality by using knowledge. Huge data stores become important once the real significance of data is discovered. Data mining techniques are involved in different knowledge processes, as one can notice in various public applications of the researchers. Managers can use these techniques in order to extract patterns, relations, associations from data initially considered of little value. Nowadays, intelligent agents represent an important opportunity to optimize knowledge management. Agents and data mining can work together in various domains such as finance, assurance, medicine, engineering and education. In this paper the authors considered an example of "data mining agents", outlining their major involvement in the complex process of knowledge management in academic environment. Keywords: Intelligent Agents, Data Mining, Knowledge Discovery, Academic Environment

1 Introduction A society based on knowledge determines managers to develop better methods and techniques to organize their data, as these become increasingly significant. In a competitive world, modern organizations focus on locating, storing, transferring and efficiently using their own information in order to better manage their intellectual capital.

Concepts of knowledge management, decision support, data mining are well-known in different areas such as business, engineering, communications, transport, medicine, education etc. Data can be transformed into usable knowledge as part of knowledge management initiatives using data mining techniques to increase organizations’ assets.

To manage knowledge is not an easy task. Data from various activities fields are produced and stored daily, processed, transmitted in different locations without taking into account their meanings. Managers focus their activity mainly on finding methods and techniques to organize huge data provided by transactions or other activities and to extract useful patterns, relations, associations from data etc. Data mining task is to


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translate structured data into knowledge. In recent years, organizations have attempted to transform raw data into usable knowledge as part of their knowledge management initiatives.

In different applications, it is necessary to know what to do, when and how to do it, in order to complete the pre-established tasks for the proposed objectives, by means of self-decision systems. These systems are known in literature as agents. Intelligent agents act robustly in a flexible, open environment. The recognized domains of intelligent-agents applications are education, communication, engineering, business, e-commerce, assurance, telecommunication etc. Knowledge discovery process can be assisted by agents in order to increase the quality of knowledge and to simplify the main processes of identifying patterns from huge data volumes. Intelligent agents and data mining share the same objectives in order to assist decision making process.

A data mining agent is a software program built for the primary purpose of efficiently finding information that operates in a data store. This type of agent is able to detect both major trend changes and new information.

In the current paper we discuss data mining agents that make a significant contribution to a knowledge management effort in the education field. Authors illustrate how agents such as DM techniques can be used for building educational knowledge, which would lead to a better performance in the academic environment.

2 Intelligent Agents and Data Mining Agents, i.e. special types of software applications, have become increasingly popular in computing world in recent years. Some of the reasons for this popularity are their flexibility, modularity and general applicability to a wide range of problems (data filtering and analysis, information brokering, condition monitoring and alarm generation, workflow management, personal assistance, simulation and gaming).

Because of the explosive development of information source available on the Internet and on the business, government, and scientific databases, it has become quite necessary for the users to utilize automated and intelligent tools to extract knowledge from them [Seydim, 1999]. Intelligent agents can help making computer systems easier to use, enable finding and filtering information, customizing views of information and automating work. An Intelligent agent is software that assists people and acts on their behalf. Intelligent agents work by allowing people to delegate work that they could have done to the agent software [Gilbert, 1997].

On the other hand, data mining is the process of posing queries and extracting useful information, patterns and trends previously unknown from large quantities of data [Thuraisingam, 2000]. Data mining is also a multidisciplinary field, working in areas that include artificial intelligence, machine learning, neural networks, pattern recognition, knowledge-based systems, information retrieval, high performance computing, and data visualization [Han and Kamber, 2001].

The concept of knowledge is very important in data mining. In order to get the correct knowledge from the data mining system, the user must define the objective and specify the algorithms and its parameters exactly with minimum effort. If the data mining system produces large number of meaningful information by using a specialized data mining algorithm (association, clustering, decision trees etc.), it will take more time for the end-


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users to choose the appropriate knowledge for the problem discussed. Even choosing the correct data mining algorithm involves more time for the system. A solution for this problem could be an intelligent system based on agents. Data mining and intelligent agents can make a common front to help people in the decision making process, to elaborate decisional models and take good decision in real time.

“Data mining is a difficult and laborious activity that requires a great deal of expertise for obtaining high quality results”. New methods are necessary for intelligent data analysis to extract relevant information with minimum effort. With the use of the autonomous intelligent agents several data mining steps are possibly be automated [Rajan and Saravanan, 2008].

3 Agents in Academic Environment Intelligent agents can successfully perform complex tasks within the educational process.

An example of intelligent agents in academic environment is given by eUNIV project [Oprean et al, 2002], consisting of five categories of applications:

educational (courses, seminars, practical activities, lectures, assessment sessions, graduation and admission, curricula, text-books, e-learning);

research (projects: national grants, international grants, co-operation, internal; reports; scientific papers, books; events);

administrative; secretarial; others. For this project the authors [Oprean et al, 2002] used the architecture presented in the

figure below. A casual scenario is the following: when a

department prepares the new academic year structure, a software agent presents a snapshot of the situation providing the information needed in the educational process for a given situation. Users can obtain information about all the professors and assistants specialized in a certain course, the software available in the department, the configuration of the networks in laboratories and the necessities for students’ practical works, how many workstations are needed taking into account the number of hours/student and the number of students in the last educational year. The system [Oprean et al, 2002] offers alternatives for the location of courses and practical works, if the timetable is implemented. An intelligent agent checks the pre-requisite for

attending the course. All these operations being automatic provide a valuable support to the department staff.

Figure 1. E-Univ architecture [Oprean et al, 2002]


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On the other hand, timetable planning can be a significant task for agents. The constraints are related to the availability, timetabling and preferences of each professor, to rooms’ availability, number of students, and curricula. In order to solve this problem for the particular case of university course timetable scheduling, an agent-based approach is a viable solution. The designed multi-agent system, MAS_UPUCT, has as main purpose the modelling of the university courses timetable scheduling [Oprea, 2006].

The authors propose a multi-agent system designed to offer advisory support for candidates in order to enrol them at postgraduate school courses from a certain faculty. The application works online and an online registration request form is necessary to help the advisor in accepting or declining candidate registration request. A registration form contains personal information and education history (e.g. graduated domain) for each candidate. When the candidate fills the registration form, there must be mentioned the postgraduate school(s) he/she wants to attend. An advisor agent assigned to the respective candidate may accept or decline his/her online registration request on the basis of candidate’s past study domain. In case of acceptance, the candidate can be enrolled, following the university methodology for postgraduate school examination approved by the university senate. In case of the request being declined by the advisor, the “candidate” repeats the process of filling the form manually and submitting the online registration request after rectifying the previous errors. If the candidate request is rejected, he/she may contact the board of examiners to obtain a supplementary advisor support.

The multi-agent system contains both mobile agents (Candidate Agent (CAgent), Advisor Agent (AAgent)) and stationary agents (University Agent (UAgent)).

CAgent is a personalized mobile agent and it is created when a candidate initiates a registration request. It sends the request to the advisor and back to the candidate, after having been accepted or declined.

To each candidate there is assigned a personalized Advisor Agent. AAgent is an intelligent mobile agent that performs two tasks: collects the academic and financial information and provides advice, once it has an intelligent analysis on the collected data and the request based on the specified registration rules.

The purpose of University Agent is to provide information on the academic history of the candidate to AAgent (in case the candidate graduated from the same university as the one he/she wants to enrol on for postgraduate school), as well as to inform the candidate about the registration’s confirmation through e-mail. The UAgent task consists in book keeping the taxes paid by each candidate.

The multi-agent system works as follows (fig.2): first of all, the candidate initiates the request by selecting postgraduate schools out of the offered list in the registration form. To initiate the request, a personalized mobile CAgent is invoked that takes the request to the advisor and waits until acceptance/ rejection is provided. When receiving a request, a personalized AAgent is activated. After getting information about the candidate, AAgent returns and performs the critical task of an intelligent advisor

Advisory process works as follows: On the basis of the collected information on the candidate (the domain of study attended before, his/her final examination marks etc.), he/she is being evaluated according to pre-established rules. Rules’ checking is performed by an inference engine of the AAgent. In simple cases, acceptance/rejection is provided on the basis of basic or inferred rules. Having received the response to the request from


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the AAgent, the proposed multi-agent informs the candidate about the acceptance or rejection of his/her registration request form. The candidate comes in front of the examiners board and follows the steps stipulated in the postgraduate school methodology examination. Finally, the UAgent generates an e-mail confirming tax payment by the candidate.

For a robust behaviour of the system, there must be a good coordination of the agents. Communication between agents of the proposed system is realized by means of interaction strategies in which there are specified the conditions to which agents may pass when receiving messages that contain certain information.

Among the advantages of using intelligent agents, one may mention higher work efficiency, meaning that the user saves time, as agents work autonomously and more effectively, as they can search and filter huge amount of information, which would be impossible for humans. This opens new approaches for researchers in combining data mining with intelligent agents.

This paper proposed a multi-agent workflow-based system for postgraduate school registration in order to automate this complex process. The proposed system is characterized by the advantages of autonomy, mobility and collaboration of different software agents in order to provide simple and fast registration workflow process for a candidate. Using agents as data mining techniques to reduce enrolling time in the described process is a new approach within artificial intelligence field. The proposed system is in the design phase and the presented theories will be tested by authors in their future research work.

REFERENCES

Gilbert, D. (1997): Intelligent Agents: The Right Information at the Right Time, IBM Corporation, Research Triangle Park, NC USA.

Han, J., Kamber, M. (2001): Data Mining: Concepts and techniques, Morgan Kaufmann Publishers, 5-7. Oprea, M. (2006): Multi-Agent System for University Course Timetable Scheduling, The 1st International

Conference on Virtual Learning, ICVL 2006, Bucuresti, 231-238. Oprean, C., Moisil, I., Candea, C. (2002): eUniv: an e-business solution for a university academic

environment. In Proceedings of 3rd Global Congress on Engineering Education, Glasgow, Scotland, United Kingdom, 363-366.

Rajan, J., Saravanan, V. (2008): A Framework of an Automated Data Mining System Using Autonomous Intelligent Agents, International Conference on Computer Science and Information Technology, 700-704.

Seydim, A.Y. (1999): 'Intelligent Agents: A Data Mining Perspective, Dept.of Computer Science and Engineering, Southern Methodist University, Dallas, TX 75275.

Thuraisingam, B. (2000): Data Mining: Technologies, Techniques, Tools, and Trends, CRC Press, 4- 6.

Figure 2. The multi-agent system components

Knowledge Exchange in an Experimental E-learning System

Iuliana Dobre

Petroleum-Gas University of Ploiesti 39, Bucharest Boulevard, Romania E-mail: [email protected]

Abstract At present E-learning systems are used widely in various contexts. These contexts have been transformed with the large support of information and communication technologies in effective teaching and learning environments. The E-learning systems not only provides new possibilities to reduce the amount of resources, especially financial ones, involved by traditional educational systems such classroom based trainings, but also introduces new forms of knowledge exchange from trainers to trainees as well as between trainees. In this paper, the author will describe an experimental e-learning system which can enhance the knowledge exchange, with application in higher education, computer science discipline.

Keywords: E-learning, Knowledge Management, Knowledge Transfer

1 Introduction E-learning is a word commonly used at present but is also a word which does not have a common definition. Frequently seems to be used for distance education coverage without covering as well face-to-face interaction. Of course, e-learning has been defined by various authors, the definitions provided being dependent on the context in which it is used. For example, where E-learning is said to be “pedagogy empowered by digital technology” (Nichols, 2008), the digital technology is referenced as a support for the learning process. Furthermore, it is often used interchangeably with various other related terms, such as distance learning, distributed learning, and electronic learning (Oblinger et al, 2005).

Distance Education and Training Council (DETC) has a specific definition for distance education which is: “It is the enrolment and study with an educational institution that provides organized, formal learning opportunities for students. Presented in a sequential and logical order, the instruction is offered wholly or primarily by distance study, through virtually any media. It may also incorporate or make use of videotapes, CD or DVD ROM’s, audio recordings, facsimiles, telephone communications, and the Internet through e-mail and Web-based delivery systems. When each lesson or segment is completed, the student makes available to the school the assigned work for correction, grading, comment, and subject matter guidance by qualified instructors. Corrected assignments are returned to the student. This exchange fosters a personalized student-instructor relationship, which is the hallmark of distance education instruction.” (http://www.detc.org, 2009).


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As a conclusion, it is nearly impossible to define what it is, as it has different meanings to different people (Dublin, 2003). For example, in companies, it often refers to strategies using company information technology (IT) network to deliver training courses to employees. In higher education institutions the e-learning word is used to define a specific mode to attend a course where the students rarely or never meet face-to-face, nor access on-campus educational facilities, because they study online.

Despite of multivocal definitions the E-learning represents today a serious and a good business. Governments, companies, research institutes, different levels of educational institutes are involved more and more in looking for new solutions or to improve the existing techniques and technologies which are supporting the E-learning. Such solutions are not only about infrastructure and hardware & software, but in the past decade were directed on people and on the environments in which the people work.

Technology is often thought of as replacing certain skills, when in fact it is more about people using technology skillfully (Shaw, 2001). Assuming that large capital investments in infrastructure, tools and facility areas alone will address and solve a host of organizational problems, and even important teaching and learning issues, is perhaps one of the biggest errors in judgement that higher education has made in the past few years. Our collective experiences have shown time and time again that the human issues are the ones that will ultimately determine whether new methods and tools in the work place will fail or succeed (Shum, 1997).

One of the main roles is played by Internet. Various researchers (Kalakota et al, 1996; Turban et al, 2000; Owens, 2002) have identified that the Internet offers unique opportunities in both teaching and learning applications. Students appear very keen on using the Internet for entertainment, peer communication, and also as secondary source of data (Ackoff, 1989; Dearing, 1997). In some cases, the researchers claimed that for students the information does not exist if it is not available on the Internet (Lissenburgh, 1999).

2 Knowledge At-Glance As the societies and economies around the world become more global and the use of PC’s more and more important, there has been a dramatic increase in e-learning necessities. E-learning is closely linked to and overlapping with, but not equal to knowledge management. E-learning can be an effective medium for knowledge management deliverables (Liu et al, 2002). The final goal of E-learning is to gain and share knowledge. Today, we are requested to deal with significant amounts of data and information. To transform these data and information in knowledge we need to know how to extract the value what we need from those. To achieve such performance is necessary to implement and apply the knowledge management principles.

2.1 Brief History of Knowledge Management During 70's, a number of management theorists have contributed to the evolution of knowledge management (Liu et al, 2002), such as:

Peter Drucker: information and knowledge as organizational resources; Peter Senge: learning organization;


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Leonard-Barton: well-known case study of Chaparral Steel, a company having knowledge management strategy;

80's have brought new approaches of knowledge management, the knowledge being considered as an expression in professional competence and a competitive asset. Artificial intelligence and expert systems begun to be more and more in the center of the researches published during this decade. The number of books and articles published by various researchers has increased significantly (Liu et al, 2002).

Starting with 90’s and up to now, an important number of management consulting firms, such as: Ernst & Young, Arthur Andersen, and Booz-Allen & Hamilton, had implemented knowledge management programs. The term “knowledge management” has been introduced in the popular press. Fundamental work pieces of various researchers were published (i.e.: in 1995, Ikujiro Nonaka and Hirotaka Takeuchi published “The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation”). In 1994, the International Knowledge Management Network went online. The beginning of the 21st century brought the knowledge management in the attention of the large public like a concept and more and more specialized companies started to create a business from this concept.

2.2 Knowledge Types The knowledge management is one of the dominant features in today’s societies. If the knowledge is considered the basis for all that everyone is doing these days, then gaining an understanding of what types of knowledge exist within an organization may allow to foster internal social structures that will facilitate and support learning in all organizational domains as well as could able the higher educational institutes to concentrate their efforts in fulfilling the societies necessities (Shaw, 2001).

The types of knowledge suggested by Blackler (1995) are: embrained, embodied, encultured, embedded and encoded. It is important to note that these knowledge types could be indicative of any organization, not just those that are knowledge-based (Shaw, 2001). Below the author is reviewing briefly the knowledge types as defined by Blackler’s (1995):

Embrained knowledge is that which is dependent on conceptual skills and cognitive abilities. We could consider this to be practical, high-level knowledge, where objectives are met through perpetual recognition and revamping. Tacit knowledge may also be embrained, even though it is mainly subconscious.

Embodied knowledge is action oriented and consists of contextual practices. It is more of a social acquisition; as how individuals interact in and interpret their environment creates this non-explicit type of knowledge.

Encultured knowledge is the process of achieving shared understandings through socialization and acculturation. Language and negotiation become the discourse of this type of knowledge in an enterprise.

Embedded knowledge is explicit and resides within systematic routines. It relates to the relationships between roles, technologies, formal procedures and emergent routines within a complex system.

Encoded knowledge is information that is conveyed in signs and symbols (books, manuals, data bases, etc.) and decontextualized into codes of practice.


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Rather than being a specific type of knowledge, it deals more with the transmission, storage and interrogation of knowledge.

2.3 Knowledge Management Objectives The knowledge management is in fact a commitment assumed by certain roles part of an organization having the scope to improve the organization effectiveness. Davenport et al (1998) describes four broad objectives of knowledge management systems in practice:

Create knowledge repository; Improve knowledge assets; Enhance the knowledge environment; Manage knowledge as an asset. Transferring the above four major objectives into specific steps, can be concluded that

the knowledge management objectives should be in more detail as follows: Build a customer relationship management; Improve internal and external collaboration; Implement and share the best practices; Competitive intelligence; Enhance the use of projects management; Enhance the use of Web-based technologies; To enhance the supply chain management; To provide E-learning etc. Activities related to more detailed objectives should include: creating knowledge by

sharing networks that facilitate a corporate knowledge culture, developing leaders’ knowledge, optimizing intellectual capital by producing knowledge management solutions such as codification strategies and knowledge bases, and estimating revenue and efficiency gains resulting from knowledge management in terms of return on investment (IDC, 2009).

2.4 Knowledge transfer Argote & Ingram (2000) define knowledge transfer as “the process through which one unit (e.g., group, department, or division) is affected by the experience of another”. They further point out the transfer of organizational knowledge (i.e., routine or best practices) can be observed through changes in the knowledge or performance of recipient units. The transfer of organizational knowledge, such as best practices, can be quite difficult to achieve (Fan, 1998).

Three related concepts are knowledge utilization, research utilization and implementation which are used by researchers to describe the process of bringing a new idea, practice or technology into consistent and appropriate use (Greenhalgh et al., 2004).

In general, the researchers (Poulfelt et al, 2007), have suggested six principles which are governing the knowledge sharing, as follows: knowledge storing, knowledge distribution, knowledge exposure, knowledge transfer, knowledge exchange, knowledge collectivism. Knowledge transfer is about classic educational means such as courses, workshops and lectures. It is important for all organizations (educational institutes, companies etc.) to get and assimilate new knowledge. Knowledge transfer is a continuous


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process taking place between individuals, between individuals and organizations and between organizations.

The future development of the overall businesses stays with the higher education capabilities to transfer good quality and efficient knowledge but also stays within business organizations capability to understand the role of higher education in their business development as well as both parties should provide access to their resources. Such links between higher education and business organizations, in order to be successfully, should be highly interactive. E-learning systems could be considered today an efficient solution to achieve the scope, knowledge transfer.

The knowledge transfer is based on information and communication technologies (ICT). The ICT’s have changed the way the higher education is conducted, with the increase of ICT for instructional design and delivery, technology-supported learning models are, eroding the dominance of traditional classroom (physical presence of educators and learners) mode of higher education. The education environment inherits the discourse and debate of the traditional classroom, such as, communicate with an instructor, or carry on a discussion with fellow students, as well as the literary practices of academia, such as writing a term paper, or presenting / debating a written argument. Yet, with the move into the online (wired and wireless) environment, all conditions for learning change. This change is juxtaposing the complexity in the mobile age that as mediated human communication becomes more and more non-linear, decentralized, and rooted in multimedia, the distinction between orality and literacy becomes less evident and less important, resulting in redefining humanity (Lai, 2005).

3 Experimental E-learning System Model The remarkable progresses obtained by the top domains such as the computer science make possible a new approach of the higher education, an approach capable to improve the efficiency and quality of the educational act. E-learning was proved in the past years to be a reliable solution.

Figure 1 presents an experimental e-learning system model, with applicability in computer science at present but also having the capability to be applied on other disciplines as well. The proposed system can cover all main processes of the educational process in higher education, such as teaching, learning and assessment processes. The functions of the system could be carried out either by people either by equipments. From figure 1 can be observed that the proposed system is complex, multivariable one, with multiple direct and reverse connections.

The symbols used in figure 1 are the following: Si – trainee i (i=1,n) RSi – results (grades) obtained by the trainee Si at all disciplines (i=1,n) CDi – the amount of knowledge’s/skills to be learned belonging to discipline i

(i=1,m) PD1, PD2 ... PDm – the trained discipline i and trainers who train the discipline i

(i=1,m) CSiDj – knowledge accumulated by the trainee Si at discipline Dj (i=1,n; j=1,m) RSiDj – results (grades) obtained by the trainee Si at discipline Dj (i=1,n; j=1,m)


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RDi – results distribution for all trainees at discipline Di (i=1,m) ISiDj – training of trainee i at discipline j (i=1,n; j=1,m) ESiDj – trainee evaluation i at discipline j (i=1,n; j=1,m) RPG – average global result (grade) per full cycle and per sub-cycles BDS – data base associated to all trainees ABDS – updated data base associated to all trainees BDC – data base associated to trainers PD1, PD2 ... PDm and the knowledge

quantum to be assimilated at disciplines CD1, CD2 ... CDm BDA – archived data base PO – hourly activities schedule

Figure 1. Experimental E-learning System Model of the learning and assessment processes

The system presented in figure 1 is a system where can take place activities and

discrete events which can be unrolled either sequentially, either in parallel, in conformity with the preparation timing schedule in several phases, which can form the training cycle of a graduates series, with the repetition of same sequences for each graduating series. Students generally like to have a sense of belonging (Bender, 2003). Therefore, the author believes that the responsibility of the educational process must be shared with them! (Dumitrescu et al, 2009).


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4 Conclusions Starting with year 2008 the organizations from Romania started to invest more and more in E-learning, the percentage being over 10% from their budget, more than double comparing with year 2007, as per Intuitext company studies (Wall-Street Romania, 2008). These figures shows that also the Romanian organizations have understood the importance of assets like the intellectual capital and the benefits coming from corporate knowledge.

Today requirements in higher education teaching involve re-ordering the leap magnitude in the instructors’ ability to create, acquire, assimilate and share the knowledge to their students. The available information and communication technologies re-shape on daily basis the educational environment. In the next decade the knowledge sharing methods and techniques will be re-invented significantly.

The system presented by the author could be considered just another step in building an interactive link between higher education and business organizations having like an ultimate scope, to assist successfully the new globally networked society. Such system can be used for various disciplines and the author is looking for future developing of the experimental system based on the tests what will be performed during the current and next year.

REFERENCES Books: Bender, T. (2003): Discussion-Based Online Teaching to Enhance Student Learning. Stylus Publishing LLC,

Virginia. Liu, S., and Parmelee, M. (2002): From Information to Knowledge. UNC School of Information and Library

Science, North Carolina. Kalakota, E., and Whinston, A.B. (1996): Frontiers of Electronic Commerce. Reading MA Addison,

Massachusetts. Turban, E., Lee, J., King, D and Chung, H.M. (2000): Electronic Commerce: a managerial perspective.

Prentice-Hall, London. Journal Articles: Ackoff, R.L. (1989) From Data to Wisdom. Journal of Applied Systems Analysis, 16, 20-37. Blackler, F. (1995) Knowledge, Knowledge Work and Organizations: An Overview and Interpretation.

Organization Studies, 6, 1021-1046. Dublin, L. (2003) If You Only Look Under the Street Lamps … Or Nine e-Learning Myths. The eLearning

Developers’ Journal, 1-7. Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P. and Kyriakidou, O. (2004) Diffusion of Innovations in

Service Organizations: Systematic Review and Recommendations. Milbank Quarterly 82, 4, 581-629. Lissenburgh, S. (1999) Knowledge Links. New Economy 6, 1, 28-32. Oblinger, D.G. and Hawkins, B.L. (2005) The Myth about E-learning. EDUCAUSE review, 14-15. Owens, J.D. (2002) E-Quality: a knowledge management (KM) based framework for e-business-learning

(EBL) at higher educational business institutes (HEBI). Manufacturing Engineering Journal 84, 3, 196-200.

Owens, J.D. and Floyd, D. (2007) E-learning as a Tool for Knowledge Transfer through Traditional and Independent Study at Two United Kingdom Higher Educational Institutions: a case study. E-Learning 4, 2.

Shaw, M. (2001) Integrating Learning Technologies: The Social-Cultural, Pragmatic and Technology Design Contexts. Insights into Using Educational Technlogy, 6.

Shum, S.B. (1997) Negotiating the Construction and Reconstruction of Organisational Memories. Journal of Universal Computer Science 3, 8, 899-928.


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Conference Proceedings: Dumitrescu, S., and Dobre I. (2009): Systems for Training and Evaluation Assisted by Computer (STEAC)

from Tradition to Innovation. In Proceedings of 6th International Symposium on Process Control, Petroleum-Gas University of Ploiesti, Ploiesti, Bulletin Technical Series, LXI, 3, 147-152.

Lai, O-K. (2005): E-Learning, Knowledge Transfer and Intellectual Communication in the Mobile Age: Consequences of Information & Communication Technologies (ICT) Mediated Communication. In Proceedings of The Seeing, Understanding, Learning in the Mobile Age International Conference, Institute for Philosophical Reasearch of the Hungarian Academy of Sciences and T-Mobile Hungary Co. Ltd., Budapest, 226-232.

Technical Reports: Dearing, R. (1997): Higher Education in the Learning Society. Technical Report: National Committee of

Inquiry into Higher Education, Norwich: HMSO. Newspapers Or Magazines: Argote, L. et al. (2000): Knowledge Transfer in Organizations: Learning from the Experience of Others.

Organizational Behavior and Human decision Processes, 82(1) May, 1-8. Davenport, T.H., De Long, D.W. and Beers, M.C. (1998): Successful knowledge management projects. Sloan

Management Review, 39(2), 43-57. Fan, Y. (1998): The Transfer of Western Management to China: Context, Content and Cosntraints.

Management Learning, 29:2, 201-221. Internet Sources: Distance Education And Training Council (2009): http://www.detc.org/ New IDC Study on Implementing Customer Relationship Management (2009): http:// www.crm2day.com/content/ Nichols, M. (2008): http://akoaotearoa.ac.nz/sites/default/files/ng/group-661 Poulfelt, F. and Petersen, N.J. (2007) 6 Principles of Knowledge Sharing: http://www.providersedge.com/docs/km_articles Wall-Street, Online Journal (2008): http://www.wall-street.ro/articol/Companii/42670

E-literature in E-learning

Zlatko Nedelko1, Carmen Elena Cirnu2

(1) Faculty of Economics and Business, University of Maribor

Razlagova 14, 2000 Maribor, Slovenia E-mail: [email protected]

(2) Focsani Regional Distance Learning Centre Distance Learning Department Spiru Haret University Bucharest

Dimitrie Cantemir 14, 620094 Focsani, Romania E-mail: [email protected]

Abstract E-learning, which differs significantly from traditional classroom education, has become a widely acceptable and commonly used means for education nowadays (in any types of educational organizations). This paper will focus on e-literature as it is used in and for the e-learning process; e-literature is not exclusively used in e-learning process as it is also used to complement traditional literature (e.g., hard copy book) in the traditional education process. A great proportion of literature on e-literature mainly deals with issues about its preparation, content, and dissemination. However, an often-neglected view is the readiness of e-learning participants to use e-literature. As such, the current paper seeks to provide an insight into the issues related to participants’ readiness to use e-literature in e-learning process. To this end, the main objective of this paper is to specify and provide and insight into participant’s readiness to use e-literature in e-learning process. For the purpose of our paper we did a survey among undergraduate students involved in web-supported e-learning process (sample from Slovenia) and undergraduate students involved in fully-online e-learning process (sample from Romania). The paper also lays an important ground work for future research of participant’s attitudes towards using e-literature in the frame of e-learning. Keywords: E-literature, E-learning, Fully-online E-learning, Readiness for using e-literature, Web-supported e-learning.

1 Introduction Due to the development of information and communication technology (ICT), contemporary education paradigm has changed significantly (Latchman et al., 1999; Ponzurick et al, 2000). Yet distance education (DE)—in which participants are not collocated (i.e., same time/same place)—is not a new concept. Nowadays, a great proportion of DE is supported through ICT and has come to be known under a common term: e-learning (Lee et al, 2007; Bates, 1995). For the purpose of the discussion herein, from now on we use the term e-learning.

The current discussion focuses on several selected issues related to e-literature, which is used to replace and/or complement traditional literature in e-learning. The term e-


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literature has multiple definitions (Aarseth, 1997; Koskimaa, 2003); it not only refers to books in PDF format posted on the Internet, but also serves as more than a mechanism of dissemination of literature over the Internet and World Wide Web by opening publication to everyone. For the purpose of our work, we adopt the definition of e-literature as traditional printed literature that has been converted to the e-literature (Koskimaa, 2003).

Indeed, e-literature must be more comprehensive as large-scale social and cultural changes are emerging thanks to the spread of the digital culture (Aarseth, 1997; Beeghly, 2005). The literature on e-literature focuses primarily on issues related to its preparation and dissemination (see: Landow, 1993; Aarseth, 1997; Tabbi, 2007).

Based on literature review, for the purpose of our paper, we did not found any evidence that some discussions explicitly address the use of e-literature in the frame of e-learning, and what is more participants’ readiness to use e-literature in e-learning. Therefore, the main purpose of this paper is to highlight participants’ readiness to use e-literature in e-learning. For the purpose of this discussion, we conducted a survey among Slovenian and Romanian undergraduate students at university.

This paper provides insight into students’ readiness to use e-literature in web-supported e-learning (sample from Slovenia) and in fully-online e-learning (sample from Romania). The paper is organized as follows. First we introduce e-literature in the frame of e-learning, following by methodology, propositions and some results. The paper concludes with discussion and implications for future research.

2 Electronic Literature: What Is It? Any form and/or type of education should provide adequate materials to its students. These are usually hard copy books, lecturer’s notices, students’ lecture notes, exercise books, journal articles, and other materials. Just as the history of print literature is linked to the evolution of book technology, the history of e-literature is based on ICT and the Internet (Hayles, 2008, 2).

With the emergence of e-literature several important questions have emerged (see: Hayles, 2008, 2): Is e-literature really literature? Will open access through the Web result in a flood of drivel? What social and cultural changes are bound up with spread of e-literature? Is e-literature demonstrably inferior to print literature? Will the emergence of e-literature affect the future of writing?

The discussions of e-literature must consider its multiple definitions (see: Koskimaa, 2003; McGann, 2001; Tabbi, 2007; Vileno, 2007; Eliterature, 2008; Landow, 1993). Hayles (2008, 3) defines e-literature as “digital born,” since a first-generation digital object is created and meant to be read on a computer. According to Eliterature (2008), the term e-literature refers to “work with important literary aspects that take advantage of the capabilities and contexts provided by the stand-alone or networked computer.”

In the creation of e-literature, must be considered that readers come to digital work with expectations formed by 500 hundred years of print literature (and even older manuscript and oral traditions), like extensive and deep tacit knowledge of letter forms, print conventions, and print literary modes. Therefore e-literature must be built on these expectations, but it must also modify and transform these expectations since in the digital


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era a great proportion of e-literature consists of different elements (different from those of traditional literature) (Hayles, 2008, 3-4).

We define e-literature as traditional literature that has been converted to e-literature (i.e. an electronic format) (Koskimaa, 2003). Such e-literature is often used in education when traditional literature is converted into e-literature through its packaging and distribution. Since the preparation of e-literature could be time-consuming, educational institutions often convert hard copy books into the electronic PDF format.

The most important benefits of e-literature are the search function, the use of automatic bookmarks, the ability to browse page by page at the touch of a key, scrolling, the creation of page notes and print excerpts, and the ability to store several books on a personal computer (Pack, 1994). The most useful of the tools provided by e-literature are digital libraries (see: Beeghly, 2005). It should also be emphasized that e-literature is more than a means of disseminating literature over the Internet and World Wide Web (Aarseth, 1997).

Nevertheless, e-literature also has some significant disadvantages. The main problem is related to copyright: how can authors control the dissemination and use of unauthorized copies of their work? How can plagiarism be prevented? Such questions have emerged with the growth of e-literature. Information has to be freely accessible to anyone with an Internet-enabled computer. The free access to information is a goal that will be achieved, but what about the rest? How can we limit the use of the information that is not free to the authorized user? How can we distinguish free information from information that requires a fee for use? (Pack, 1994). For the purpose of our discussion we add readiness of participants to use e-literature, which has been a neglected topic in discussions among academics and practitioners.

Based on these assumptions and our educational experiences, we can classify literature used in the e-learning process as (1) traditional print literature and (2) e-literature. The former consists mainly of hard copy books, peer notices, and lecturer’s notices. Traditional print literature has had a leading role in traditional classroom education, while e-literature is widely especially in e-learning process. Based on our experiences, we contend that a large proportion of hard copy books that are used in colleges and universities have been converted to the PDF format (see also: Koksimaa, 2003).

Based on these ideas, the literature reviewed, and experiences from education practice, we can conclude that important differences exist between traditional print literature and e-literature (Based on: Wang and Liu, 2003): (1) design of literature; (2) capability for distribution; (3) creation; (4) storage format; and (5) additional functions (e.g., searching).

Regardless where the e-literature is used, an important consideration is the readiness of students to use e-literature. According to the purpose of our paper, we examined users’ attitudes towards using e-literature in web-supported and fully-online e-learning process.

3 E-literature in the frame of e-learning A perceived lack of literature exists that deals with issues related to the usage of e-literature in context of e-learning, and especially studies about the readiness of e-learning participants to use e-literature in the e-learning. For the purpose of the discussion we will emphasize important concepts related to e-learning and define a variety of e-learning formats.


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Several different typologies/classifications of e-learning are following (Bates, 1995; Gonc, 2007; Ponzurick et al., 2000): (1) Web supported—an e-learning format that complements the traditional (face-to-face) learning process, where all participants are collocated (class sessions are held in the same place and at the same time); a Web site (i.e., portal for distance education) for the class contains course materials, assignments, goals, exercises, and short tests; (2) Blended or mixed-mode e-learning—this course is structured so that part of the class sessions are held in a traditional (face-to-face) setting and part are held with usage of modern ICT over internet. The mixture of face-to-face mode (traditional learning) and distance mode (e-learning) has become very popular in current educational processes. In face-to-face learning, the participant (i.e., student) establishes a rapport with the educator and gets clear instructions on how to study in the distance mode (e.g., submitting assignments). Many universities rely on the mixed-mode of education (few class sessions, assignments are done and submitted via e-learning); and (3) Fully online e-learning format—every class session is held in the distance mode, making face-to-face mode complementary to distance mode.

Based on selected e-learning formats, we can conclude that differences emerge regarding the use of e-literature in each of mentioned formats. In Web-supported e-learning, the main body of literature is still traditional literature. Often in educational practice this type of e-literature is understood in a broader sense and includes books and notes converted to PDF format as well—which are not (usually) considered true e-literature. Therefore, the usage of e-literature in Web-supported e-learning is not mandatory as students have easy access to traditional literature (e.g., university library). On the other hand, participants in the fully online e-learning format use mainly e-literature due to the nature of the learning format (e.g., learning at a distance, library is not close).

These cognitions present starting points for our research and future discussion, focusing on participants’ readiness toward usage of e-literature. To this end, we conducted a survey among undergraduate students.

4 Results from the research The primary aim of our survey was to determine students’ willingness and readiness toward the usage of e-literature in the e-learning. The survey on e-literature in e-learning was part of a study in which we assessed participants’ readiness for incorporation in the e-learning process. We used data from research about e-learning, which was conducted with Slovenian and Romanian undergraduate students. Herein we focus only on data dealing with e-literature issues in e-learning. In the frame of the selected problem, according to the concepts presented earlier and our experiences in educational practice, we defined several hypotheses for the purpose of our discussion.

The research included 155 Slovenian and 151 Romanian participants. The Slovenian participants were second- and third-year undergraduate students in the bologna process of study, with an average age of 21.6 years; 58.1 percent of them were females. Meanwhile, Romanian participants were mainly first- and second-year students in an undergraduate program, with an average age of 27.52 years; 55 percent of them were females. According to our findings about information literacy, we can conclude that an average


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participant in the study is relatively well prepared for working with modern ICT and computers and has a sufficient level of skills to work with computers. Skills were assessed on a 5-point Likert scale; the average value for Slovenian students was 3.66 and for Romanian 3.46 (for details, see: Nedelko, 2008).

Romanian students have already participated in fully online e-learning, while Slovenian students are involved in highly developed Web-supported e-learning. Thus, Slovenian students, besides traditional face-to-face lectures, use a portal for e-learning through which they submit homework assignments, download lectures, etc. As such, it can be presumed that Slovenian students also use a reasonable amount of e-literature (i.e. broad definition - books in PDF format are also considered e-literature). According to this presumption, we can ensure the comparability of results from the research with Slovenian and Romanian students in regards to e-literature in e-learning. To test our hypothesis, we use chi-square tests since our data are categorical (for details, see: Cramer, 1998). We test all hypotheses at alpha level of 0.05. All our hypotheses are in an alternative form (in statistics, they are commonly addressed with the expression H1). In this contribution only some results from the SPSS outputs are presented in text, due to the limited length of a paper.

Proposition 1 stated that significant differences exist in students’ attitudes towards using e-literature as a complement to traditional print literature (i.e. print hard copy books) in education process among Slovenian and Romanian students. In that context is e-literature considered only as a complement to traditional print literature. Findings are summarized in Figure 1.

Figure 1: Cross tabulation table for e-literature as a complement to traditional print

literature in education process by nationality. Nationality

Slovenian Romanian Total

Count 153 136 289 % within Nationality 98,7% 90,1% 94,4% Yes Adjusted Residual 3.3 -3.3 Count 2 15 17 % within Nationality 1,3% 9,9% 5,6%

Do you like to use e-literature as a complement to traditional print literature (i.e. print hard copy books) in education process?

No Adjusted Residual -3.3 3.3 Count 155 151 306

Total % within Nationality 100,0% 100,0% 100,0%

Perceived difference among Slovenian and Romanian students in their attitudes

towards using e-literature as a complement to traditional print literature in education process, are statistically significant (Chi-square = 10.891, significance level = 0.001). There also exists a very weak association between student’s attitudes towards using e-literature as a complement to print literature in education process and nationality of students (Cramer’s V test is 0.189). Therefore Proposition 1 is supported. A closer examination (see Figure 1) provides more detailed information on these results.


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Proposition 2 stated that significant differences exist in student’s attitudes towards replacement of traditional print literature (i.e. hard copy books, lecturer’s notes) with e-literature in education process among Slovenian and Romanian students. Therefore students were asked if adequate prepared and designed e-literature could replace traditional print literature (i.e. hard copy books, lecturer’s notes) in education process. Results are summarized in Figure 2.

Figure 2: Cross tabulation table for replacement of traditional print literature with

e-literature by nationality. Nationality

Slovenian Romanian Total

Count 118 92 210 % within Nationality 76,1% 60,9% 68,6% Yes Adjusted Residual 2.9 -2.9 Count 37 59 96 % within Nationality 23,9% 39,1% 31,4%

Adequate prepared and designed e-literature could replace traditional literature (e.g. hard copy books, notices) No

Adjusted Residual -2.9 2.9 Count 155 151 306

Total % within Nationality 100,0% 100,0% 100,0%

Perceived difference among Slovenian and Romanian students in their attitudes

towards replacement of traditional print literature with e-literature, are statistically significant (Chi-square = 8.210, significance level = 0.004). There also exists a very weak association between student’s attitudes towards replacement of traditional print literature with e-literature and nationality of students (Cramer’s V test is 0.164). Therefore Proposition 2 is supported. A closer examination of the individual cells in the cross-tabulation table (see Figure 2) provides more detailed information on these results.

Proposition 3 stated that significant differences exist in student’s attitudes regards the proportion of e-literature used in e-learning process (in general) among Slovenian and Romanian students. Results are summarized in Figure 3.

Figure 3: Cross tabulation table for desired proportion of e-literature used in traditional classroom education process by nationality.

Nationality Slovenian Romanian

Total

Count 141 121 262 % within Nationality 91.0% 80.1% 85.6% Yes Adjusted Residual 2.7 -2.7 Count 14 30 44 % within Nationality 9.0% 19.9% 14.4%

Would you like to use e-literature in greater extent as until now?

No Adjusted Residual -2.7 2.7 Count 155 151 306 Total

% within Nationality 100.0% 100.0% 100.0%


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The Chi-square result demonstrates that significant association exists between students’ preferences about the proportion of e-literature usage in education process and students’ nationality (Chi-square = 7.294, significance level = 0.007). The Cramer’s V 0.154, is indicating a fairly weak association between student’s preference about the proportion of e-literature usage in education process and students’ nationality. Hypothesis 3 is supported. Figure 3 provides detailed information on these results.

5 Discussion and conclusions Based on our hypotheses and experiences from educational practice we made some tentative conclusions. According to the Proposition 1 we can see that Slovenian students involved in web-based e-learning has more favorable attitudes about using e-literature as a complement to traditional print literature in education process on the other hand Romanian students involved in fully online e-learning process has lees favorable attitudes about using e-literature as a complement to traditional print literature in education process. Based on the results of Proposition 1 we can conclude that type of education (i.e. web-based e-learning and fully online e-learning) importantly influence students attitudes about using e-literature as a complement to traditional print literature in education process. Based on these results about proposition 2, we can conclude that a significant association exists between the type of e-learning process (in which student is involved) and the student’s perceptions about the replacement of traditional print literature (e.g., hard copy books, lecture notes) with e-literature. Participants in web-supported e-learning (i.e. Slovenian participants) have more favorable perceptions about the e-literature as an adequate replacement for traditional print literature than their counterparts in Romania, involved in fully online e-learning education.

Therefore we propose that the differences observed between Slovenian and Romanian students concerning different issues (emphasized in paper) could have their roots in the cultural differences among the two countries. This statement represents an important starting point for future examination.

An important limitation is that we neglected possible impact of culture differences on students’ attitudes towards selected issues. Some possible areas of future research could be participants’ attitudes toward e-learning, students’ personal values, motivation for study, thinking and problem-solving skills, readiness and/or capability for accepting the new type of literature (i.e., e-literature), and cultural differences among selected countries.

REFERENCES

Aarseth, E. (1997): Cybertext: Perspectives on Ergodic Literature. Johns Hopkins University Press, Baltimore.

Bates, A.W. (1995): Technology, open learning and distance education. Routhledge, London. Beeghly, D. (2005): It’s about time: Using electronic literature discussion groups with adult learners. Journal

of Adolescent and Adult Literacy 49, 1, 12-21. Cramer, D. (1998): Fundamental statistics for social research. Routhledge, London. Eliterature (2008): http:www.eliterature.org [15.04.2008].


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Hayles, N.K. (2002): Writing Machines. The MIT Press, Cambridge, MA and London. Koskimaa, R. (2003): http://www.brown.edu/Research/ dichtung-digital/2003/4-koskimaa.htm [12.08.2009]. Landow, G.P. (1993): Hypertext. The Convergence of Contemporary Critical Theory and Technology. Johns

Hopkins University Press, Baltimore. Latchman, H.A., Salzman, C, Gillet, D. and Bouzekri, H. (1999): Information Technology Enhanced

Learning in Distance and Conventional Education. IEEE Transactions on Education 42, 4, 247-254. Lee, Y., Tseng, S. and Liu, F. (2007): Antecedents of Learner Satisfaction toward E-learning. The Journal of

American Academy of Business 11, 2, 161-168. McGann, J. (2001): Radiant Textuality: Literature after the World Wide Web. Palgrave, New York. Nedelko, Z. (2008): E-learning – a case study. In Proceedings of 4th International Scientific Conference

“Elearning and software for education, Carol I National Defense University, Bucharest, Romania, 43-49. Pack, T. (1994): Electronic books: A new spin on the Great American Novel. Wilton 7, 2, 54-56. Ponzurick, T.G., Russo France, K. and Logar, C.M. (2000): Delivering Graduate Marketing Education – An

Analysis of Face-to-Face versus Distance Education. Journal of Management Education 22, 3, 180-187. Tabbi, J. (2007): http://eliterature.org/pad/slw.html [25.05.2008]. Vileno, L. (2007): From paper to electronic, the evolution of pathfinders: a review of the literature’.

Reference Services Review 35, 3, 434-451. Wang, C. and Liu, Z. (2003): Distance education - basic resource guide. Collection Building 22, 3, 120-130.

Discovering green energy @ portal.moisil.ro

Mihaela Garabet1,2, Ion Neacşu1

(1) Theoretical High School “Grigore Moisil” 33, Timişoara Bvd, Bucharest, Romania

(2) University of Bucharest, Faculty of Physics E-mail: [email protected]

Abstract We have started from a pedagogical research concerning the opportunity of the introduction of studying the photo devices like photovoltaic cells, photo resistors, photodiodes, phototransistors, etc, in the Romanian Curriculum for Physics in high school. So, we have started a group project, with students from the 10-th grade, from Grigore Moisil High School, Bucharest, the teachers, the parents of the students and the local community. At the beginning we intended to familiarize the students with such devices and their applications in order to perform the theoretical study. During this stage of the research the students helped by the teachers and parents made some simple applications like solar house, solar lift, solar power station for toy car chargers. A new problem appears: the photovoltaic cells have to be moved under maximum solar illumination for reaching a great efficiency. How? By recycling some servomotors from the old printers of the school, then innovate a way of coupling them with the PV cell. The next step is to use some sensors of light (photo resistors coupled with a data acquisition board and a computer) for decide when to change the incline of the PV cells and then to develop the software for analyzing the sensors indications, make the decision and move the servomotor. The great challenge will be to construct a solar gusher fountain which will be held in the yard of the school. The aspects from the activities on http://portal.moisil.ro/ playenergy/ Documents/Forms/With%20File%20Size%20Column.aspx Username: vizitator Password: vizitator. Keywords: green energy, photovoltaic cells, data acquisition experiments, AeL lessons.

1 Introduction Today, the mankind efforts are being made to obtain more and more renewable energy in order to reduce our dependency on the fossil fuels and the pollution created by them The world’s population uses 14 TW of power today and we will need ~ 30 TW of power in 2050. But, much of the extra 16 TW must be provided without releasing carbon dioxide into the atmosphere. An imperative problem is to improve the use of green energy. The term green energy is used for the energy provided by the environmentally friendly sources. They are also non-polluting because they have lower carbon emissions. We can include here the solar energy, the wind energy, hydro energy and geothermal energy.

We will describe a group project which has the goal to meet the students from the 10th grade with the appropriate uses of the solar energy. Everyday the Sun gives us light


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(visible radiation) and heat (infrared radiation). We are using both form of the Sun radiation, sometimes converted in other forms of energy. The light could be converted in electric energy by using photovoltaic cells (PVC). This kind of solar devices is very present in the human activity.

Moreover, the global policies referring to the world preserving, in December 2009, the UN will hold the COP15 climate conference in Copenhagen, Denmark. This is the most significant international gathering on climate change since Kyoto in 1997 - 18.000 visitors are expected in Copenhagen, including governments, corporations, NGOs and journalists from all over the world (Climate Mystery).

In connection with these arguments, we are considering that the students must be familiarized with devices that use green energy, in order to use them in their future life.

2 The photovoltaic’s study in the Romanian high schools First of all we have to mention that the actual Romanian Physics Curriculum contains the fundamentals of semiconductors in the 12th grade, with no reference to the PV cell. Twenty years ago, the photovoltaic elements were studied in the 12th grade, but the approach was theoretical and the students had many difficulties in their understanding.

Today, our students are familiar with the PV cell used in most calculators, in the solar lamps for the gardens or in the solar heaters for water.

The first step in introduction of the photovoltaic’s study was made by the electronic lessons from the AeL (Electronic assistant for high schools), as you can observe in the Figure 1. The lesson is treating the Power and the efficiency of the home appliances. And we have considered that we already have solar home appliances as recharges, solar cookers.

Figure 1.Print screen from the AeL lesson


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The pedagogical approach starts from the everyday experience of the student, continues with the experimental study and ends with the scientific explanation of what’s happening inside the PV cell. The scenario and the video clips which present the experimental activities have been made in the Physics Laboratory of the Theoretical High School “Grigore Moisil” from Bucharest. The testing of these lessons was made with the students from the 10th grade, same school. We have to mention that these activities were developed in an extracurricular manner, after school. Practically, the students were implied in an AeL session of the lesson. They performed all the activities we have proposed in the lesson (virtual experiments, simulations, video clips, data processing and evaluation activities). During the virtual experimental study, the students will represent the voltamperic characteristic of the PV cell and they will calculate the generated power. This was the starting point of the group project we will describe for this point forward.

3 The learning model Our project has started from a pedagogical research concerning the opportunity of the introduction of studying the solar cells in high school. It offers a way to develop the general competences prefigured in the Romanian curricular standards like: understanding and explain natural phenomenon and technological processes in everyday life, applying of scientific investigation in Physics (Garabet and Neacsu, 2008).

We have considered that our educational activity is best handled with a blending of several methods, from simple self-review and self-study, to collaboration and interaction among students and instructors connected via the Internet.

The learning model we have used is a 4-Tier Learning Model including: learn from information, learn from interaction, learn from collaboration and learn from collocation.

Tier 1- Learn from information was the first level, when the students read the tutorial about the green energy concepts.

Tier 2- Learn from interaction was accomplish by using the AeL lesson we have described. In this level the student the student can interact with the information provided by the electronic lesson and practice as well. Here, the student will find, in a virtual way, how to perform an experiment with solar cells.

Tier 3- Learn from collaboration is the level when our students are bringing together, online with other students. This happened when our school, particularly this group of students, has participated in the international competition Play Energy which has the main goal the discovering of the way we can produce energy. You can see the aspects (Figure.5) from the activities we have developed on the URL, http://portal.moisil.ro/ playenergy/Documents/Forms/With%20File%20Size%20Column.aspx

Username: vizitator Password: vizitator. Here you will find the materials we have developed in our project. We have a motto, a

short description of our team. We have to mention that every member of the team has his own site.

Portal.moisil.ro is a Microsoft Learning Gateway application for educational use, in order to facilitate the communication between all the educational actors: students, teachers, managers, parents, local community.


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Figure 2. Aspects from portal.moisil.ro The Microsoft Learning Gateway is a secure education portal that provides

information and collaboration services for teachers, students and parents. It reduces administration overheads and gives teachers more time to teach.

The Learning Gateway provides a framework for blending e-learning solutions into one fully managed environment, placing the student at the centre of the education experience. A single, secure log-in to the Learning Gateway home page supplies a convenient snapshot of all work assigned. The portal's centralised environment then provides access to all current assignments and resources from any location (Microsoft).

The portal was used for sharing our results with the Liceo Scientifico Amedeo Avogadro from Vercelli, Italy. The students have shared the materials they have prepared during the study of the methods for generate the energy we need.

Tier 4- Learn from collocation is the step when the students were incited to find some appropriate using for the solar cells. We know that the learning process is enhanced when it is situated in authentic problem-solving activities. This approach of our project is founded on the principles of learning by doing and experiencing. In this case the students are faced with authentic situations and scenarios which are very motivating because they have to act like the adults in the real world (Naidu, 2003).


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That’s why we have considered they have to learn by doing themselves. So, they have received some PV cells buy from a specialized store. In order to find some opportunities of using them, the students have to study them first.

One of the most important roles in the human learning is motivation followed by long-lasting interest and engagement. The students are very enthusiastic when the teacher uses ICT during the classes, not because of its novelty effect registered ten years ago, but because of the opportunities ICT is bringing. That’s why have propose a real experiment using a data acquisition system for registering the current and the potential (Vernier; National Instruments) of the PVC extracted from a batteries charger, under illumination. The students have to find the deliverable current of the PVC, the maximum Power Point and even the efficiency of the cell. The experimental data were processed with Microsoft Excel and were published on the portal. You can see some aspects during the experimental study of the cells in the figure 3.

Figure 3. The experimental set-up The student’s conclusion was that the PV cell has special volt-ampere characteristic

and weird power dependence vs. voltage (Figure 4).

Figure 4. Experimental results


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At this moment we can try to explain what the photovoltaic cell is: simply a diode of large aria forward bias with a photo voltage. The photo voltage is created from the dissociation of electron-hole pairs created by incident photons within the built-in field of the junction (Lasnier et al, 1990). The field assure the separation of the charge carriers which are released by light. Under illumination, the incident photons interact with the atoms of the cell and the electron-hole pairs are produced. When the metal contacts of the cell are connected with a consumer we can obtain a direct current (Messenger and Ventre 2003).

4 Results -The students ideas After the experimental study, the students helped by the teachers and parents made some simple applications like solar house, solar lift, solar power station for toy car chargers. You can see them on the indicated URL. We will point some images in the next figures.

Figure 5. Solar elevator and a solar illumination system

Figure 6. Recharge station for electric cars and the eco-house

5 Present and future plans A new problem appears: the photovoltaic cells have to be moved under maximum

solar illumination for reaching a great efficiency. How? By recycling some servomotors


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from the old printers of the school, then innovate a way of coupling them with the PV cell. The next step is to use some sensors of light (photo resistors coupled with a data acquisition board and a computer) for decide when to change the incline of the PV cells and then to develop the software for analyzing the sensors indications, make the decision and move the servomotor. The great challenge will be to construct a solar gusher fountain which will be held in the yard of the school.

Figure 8. We are learning together how to recycle everything we can...

6 Conclusions We have presented a group project developed in a Romanian high school where we have tried another kind of learning, based on the principles of constructivism and situated cognition. We can say that it is efficient and effective and the visible results we have registered are:

- the students intrinsically motivation and interest for learning; - the learning objects (McGreal, 2004) as a result of the students’ interaction with the

materials we gave them. The next generations of students will use these learning objects as learning resources. We are referring to the physical objects like the solar elevator, which will be use in our lab and also to the digital objects hosted on the portal.

REFERENCES

Garabet, M. and Neacsu, I. (2008): Science e-learning @ portal.moisil.ro. In Proceedings of The 3rd International Conference on Virtual Learning, Constanta, 423-430.

Lasnier, F. and Ang, TG. (1990): Photovoltaic Engineering Handbook, IOP Publishing Ltd., Bristol. Messenger, R. A and Ventre J. (2003): Photovoltaic systems engineering, CRC Press, Florida, USA. McGreal, R. (2004): Online education using learning objects, RoutledgeFalmer, Oxon. Naidu, S. (2003): e-learning. A Guidebook of Principles, Procedures and Practice, CEMCA. Internet Sources: www.theclimatemystery.com http://www.microsoft.com/uk/education/schools/products/learning-gateway/default.aspx http://www.ni.com http://www.vernier.com

Toward A Comprehensive E-Learning Style (CELS)

Ahmad A. Kardan1, Seyedeh Fatemeh Noorani2

(1) Advanced E-Learning Technology Laboratory,

Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran.

Email: [email protected] (2) Department of Computer Engineering and Information Technology,

Payme Nour University, Tehran, Iran. Email: [email protected]

Abstract Learners have different learning approaches for learning, known as learning styles. There are various learning styles used in the traditional education up to now, but none of them have adequately covered all learning aspects in e-learning environment. Statistics reveal that considering students’ learning style is a significant factor that improves learning performance in web-based learning (e-learning). Meanwhile, classic learning models are short of important considerations regarding new technological aspects of learning based on information and media. Therefore, a dedicated learning style for e-learning is strongly essential. This paper introduces a new learning style model for e-learning. We would outline a complete set of learning styles’ parameters suitable for e-learning and explain how these parameters can be acquired in an e-learning environment. The proposed learning style named as Comprehensive E-Learning Style (CELS) includes main characteristics of the existing models, and some important and new parameters have been introduced in this work. We believe that a dedicated learning style for e-learning environment could serve as an important factor for better adaptation and personalization in e-learning. In this work, we also classify the tools and implicit or explicit techniques necessary for measurement of the related parameters in the learning environment. Finally, this work clarifies the main domains of applicability of our proposed learning style, and our future works to verify the CELS model. Keywords: Learning Style, Personalization, E-learning style, Adaptation.

1. Introduction Characteristic and habitual manner of obtaining knowledge, skills, or approaches through learn or experience is named Learning Style.

Statistics reveal that considering students’ learning style is a significant factor that improves learning performance in web-based learning or e-learning (Manochehr, 2006). Meanwhile, classic learning models are short of important considerations regarding new technological aspects of learning based on information and media. Therefore, a dedicated learning style for e-learning is strongly essential.


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At present, several learning style models exist in the literature; Coffield et al. count 71 models (Coffield et al, 2004). Each model suggests different classifications of learning types. These include the models by Kolb (1984), Honey and Mumford (1982), Felder and Silverman (1988) and etc (Graf, 2008).

As we have just seen, within the context of today's learning, the issue of the learning styles identification was tested by important research. However, within the specific framework of e-learning, research on learning styles is still at the preliminary and exploratory stage; no learning style model was proposed as yet to inform us about the way in which learners study in e-learning environment (Bousbia et al, 2008).

In this paper, the learning style theory and its accomplishment in EHS (Educational Hypermedia Systems) are described in section 2. Afterward, two related works are illustrated in section 3. Then, in section 4, Comprehensive E-Learning Style (CELS) will be explained.

2. Learning Style Learning styles refer to the way learner prefers to advance his/her new information. Each person learns and processes information in his/her own special ways, though he/she shares some learning patterns, preferences, and approaches. Knowing learner style also can help learner to realize that other people may approach the same situation in a different way from his/her own.

By understanding learning style, learner can develop his/her natural approaches for learning and develop the capacity to learn in the manner that may require more effort. On the other hand instructors can understand the differences in learning process being noticed in the learners and develop a range of educational strategies to engage individuals' strengths.

The learning styles are not the expression of a rigid typology claiming to classify individuals in strict categories. In this way, various theories of learning styles were developed with an increasing frequency during the last decades based on the Curry’s ‘onion’ model (Bousbia, 2008). Curry’s “Onion Model” categorizes learning styles into four layers: Personality Models, Information Processing Models, Social Interaction Models and Instructional Preference Models.

2.1 Learning Style Detection Approaches There are two different detection ways for getting information about learner: automatic and collaborative. In the former, the process of distinguishing the learner style is done automatically, based on the action of the learner when he/she is using the e-learning system for learning. The main problem with this approach is to get enough reliable information to build a robust student style. According to (Brusilovsky, 2007) a solution to this problem might be the use of additional, more reliable sources, such as the results of tests, in the learner style detection process. On the other hand, in collaborative approach, the learner provides explicit feedback, which can be used to distinguish his/her learner style. For instance, the learner can provide data for the detection learner style mechanism such as stating explicitly whether a page was relevant for his/her learning goal. Another option is to let the learner do the adaptation by himself/herself and therefore show


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directly what he/she expects from the system. For example, the order of links on a page can be changed by the learner, showing the preferred order to the system (Graf, 2008).

2.2 Adaptation Nowadays, the main concern in e-learning is improving the learning process and many research papers indicate that this is possibly done through an adaptive system.

Hanan (2005) states that "There are many attempts to improve the adaptive system by using different methods and artificial intelligence techniques for extracting user model and overcoming the difficulties. However, such system lacks the ability in building student personality by motivation, increasing self-confidence, or reducing shyness. Therefore, most of the researches focus on the student modeling and how the system can automatically deal with dissimilar students. In traditional classroom system, a teacher can monitor and react accordingly based on what he/she sees of his/her students’ action. However, an e-learning environment requires student to be more independent. As such the system should be able to adapt to the preferred learning style of each student".

In brief, Learner’s Learning Style, Learner’s Knowledge Level and Learner’s

Behavior need for adaptation. Different possibilities exist for adapting a course based on the information of the learner model. The most often approach is to match the instructions to the preferences or abilities of the learners, and teach according to the learners’ strengths. The whole view of an adaptive system is shown in figure 1.

2.3 Learning Style Models within EHS Inside the particular context of e-learning, study on learning styles is still at its beginning and its examining phase (Brusilovsky, 2007); no learning style model was proposed as yet to inform us about the way in which learners study with digital resources. Therefore, few Educational Hypermedia Systems (EHS) have been used to implement this theory in spite of its strong influence on learning. Table 1 gathers some EHS. It also consists of their learning style model, the detection method and adaptation model (Brown et al, 2005; Alexandra, 2005). Each system uses one of the learning styles models, which can induce a lack of homogeneity in the results within this e-learning specific framework.

Figure 12. Architecture of Adaptive Learning System

1. Learner Data

Gathering

Learner

Model

Learning Style

Knowledge Level

Learner's Behavior

2. Updating

Learner Model 3. Adaptation

Adaptation Process

Based on

Learner Model

Make Use for


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3. Related Works: The authors of (Popescu et al, 2007) proposed the use of a unified learning style model, which integrates the most relevant characteristics from several models. They summarized learning preferences related to: Environment, Reasoning Pacing, Organizing information, Social aspects, etc. They claim this model integrates the most relevant characteristics from several models and it includes e-learning specific aspects and is stored as a set of learning characteristics, not as a stereotyping model.

Table 1. EHS Implementing Learning Styles And Their Adaptation Model

EHS Learning Style Model Explicit/Implicit Detection Adaptation Model

CS383 (Carver, 1999)

Felder-Silverman (sensing/intuitive, visual/verbal, sequential/global)

Explicit (questionnaire) At the Presentation level (Sorting fragments technique)

AES-CS (Triantafillou, 2003)

Witkin (field dependence/field independence)

Explicit (questionnaire) At the instructional strategies

INSPIRE (Papanikolaou, 2003)

Honey and Mumford Explicit (questionnaire) Student's self-diagnosis

At the Navigation Level

EDUCE (Kelly, 2006)

Gardner's theory of multiple intelligences

Implicit (Analyzing the learner's interaction with MI differentiated material and using a naive Bays classification algorithm) Statically (Shearer's MI inventory)

At the Presentation level & Navigation level

iWeaver (Wolf, 2003)

Dunn & Dunn Explicit

Adaptation techniques including :link sorting, link hiding.

In the work done by (Hanan, 2005) learning styles suitable for e-learning were

outlined. The authors discussed learning approaches that focused on e-learning environment. As final point the authors presented the e-learning style model through a matrix (16*5). The columns of matrix are learning approaches. The rows in table of the mention matrix represent what is/are the types of the person’s e-learning style. The weakness of this model is lack of e-learning features like media preferences or desired interaction with others.

4. Comprehensive E-Learning Styles (CELS) The results of research revealed that students’ learning styles were statistically significant for knowledge performance. This conclusion is consistent with earlier findings on the importance of learning style. For the instructor-based learning class, the learning style was irrelevant, but for the web-based learning class, learning style was significantly


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important. The Kolb’s learning style model is considered. The results showed that students with Assimilator and Converger learning styles do better with the e-learning method. In addition, students with Accommodator and Diverger learning styles received better results with traditional learning (Manochehr, 2006).

As for main aim of considering learning style to improving learning progress, this paper introduces a Comprehensive E-Learning Style named CELS. The CELS category is based on excitability on e-learning environment.

The core of CELS is Felder-Silverman model with some modifications. It has been selected because (1) its author has an engineering background and this model has a focus on that same field, (2) there are some relationships between this model and other models. For example, the active/reflexive dimension in Felder model corresponds to the “Active Experimentation”/”Observation and Reflection” in Kolb model and also is relates to the Extravert/Introvert scale of Myers-Briggs model (Gomes et al, 2007).

As shown in figure 2, the CELS has three layers: Central Layer: The first layer of CELS is Preparing Layer. It is clear that learning can't

improve if environment hasn't suitable situation. Thus in first layer the environmental factors like noise, light, temperature and time of study, are being noticed.

Middle Layer: the second layer consists of four factors of learner preferences: Media Preferences: In the web environment, there are a slew of materials, such as

slides, white-board contents, etc associated with the audio and video streams of the courses taught. Understanding learner's media preferences and content adapting, will improve learning.

Tools Preferences: Obviously, learners prefer some tools to other tools. For example which input tools does learner prefer? using mouse or keyboard? or which output hardware does learner like more? computer monitor or cell monitor?

Online /Offline Interaction: The degree of interaction between learner and other persons (teacher or other learners) is important; it not only improves learner motivation and serious effort, but also creates a live environment. Then learner can choices online interaction like chat, voice based discussion and virtual class or he/she can chose offline interaction like email and discussion boards.

Social aspects: this depends on the person's character and is one of the most important subjects in learning style. In several models such as Dunn and Dunn learning style model (Dunn, 2003) this topic has been considered. The main aim of the CELS is applicability;

Figure 2. The CELS's Layers

Preparing


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therefore the detail of Dunn and Dunn Model is ignored. In the CELS two features are considered: Individual/Team work and Competitive/Collaborative work. When each learner works on assignment, prefers being alone or in a group? Or he/she prefers to be a collaborative or competitive person?

External layer: the third layer is focused on learning. The foundation is based on the Curry’s ‘onion’ model and the Felder-Silverman learning style model. This layer has four components.

Perceiving: When learner gathers require information necessary for learning, he/she can employ all his/her input channel (Visual, Auditory, Reading, Kinaesthetic). He/she can also use conceptual, theories or innovative aspects.

Receiving: Which channel does learner prefer for receiving information? To see the information or to listen to it?

Processing: Learner will have a natural preference for how to learn and how to prefer receiving the facts. The CELS considers two features for processing: (active/reflective) and (sequential/holistic/mind maps).

Solving: what is the learner's preference to solve a problem: Problem Based learning, Inquiry Based Learning, or Gaming? 7-

The classification of parameters and implicit or explicit techniques necessary for measurement of the related parameters in the learning environment is shown in Table2.

Table 2. The CELS's Layers Parameters And Their Measurment Approach Measurement Approach

Layer Factors Parameters explicit implicit

Noise sensor ---

Light sensor ---

Temperature sensor --- Internal Layer

Preparing:

Time of day Time zone of

learner ---

Media Preferences

Text/image/ voice/ video/animation

Questioner Using Rate

Tools Preferences

Mouse/Keyboard/ Light Pen/ Microphone

--- Using Rate

Online/Offline Interaction

Online (Chat, Virtual Class, Tel) Offline (Note, Email)

--- Using Rate

Individual/ team work Questioner ---

Middle Layer

Social aspects Competitive/ Collaborative Questioner ---

Perceiving Sensing/intuitive Questioner ---

Receiving Visual (text/images)/Verbal Questioner ---

Processing Active / Reflective Serial / Holistic/ Mind Maps

Questioner Lerner behavior (Bousbia, 2008)

External Layer

Solving Problem Based Learning Inquiry Based Learning Gaming

Questioner Learner result in each approach


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The learning style detection mostly is being used for adaptation. Regarding the adaptation process, there are several approaches described in (Brusilovsky, 2004): Navigation Level Adaptation, Content Level Adaptation, Presentation Level Adaptation, Collaboration Level Adaptation.

An appropriate environment should be provided by user. The second and the third layers Table 3 shows which adaptation method can be done to match the learners with suitable content based on the learning style. For example in processing learner with serial way, contents must be navigated step by step. Holistic learners should have a content overview and then they can forward to see details. This could be done by navigation level adaptation. The leaning content for an active learner must be more practical, and for a reflective learner learning content should be more conceptual.

Table3. The CELS Adaptation

Layer Components Details Adaptation

Type Media Preferences

Text/image/ voice/ video/animation Content level

Tools Preferences

Mouse/Keyboard/ Light Pen/ Microphone

Content level

Online/Offline Interaction

Online (Chat, Virtual Class (Sound, Image), Tel) Offline (Note, Email)

Collaboration Level & Presentation Level

Individual/ team work

Second Layer

Social aspects Competitive/ Collaborative

Collaboration Level

Perceiving Sensing/intuitive Content Level Receiving Visual (text/images)/Verbal Content Level

Processing Active / Reflective Serial / Holistic/ Mind Maps

Content Level & Navigation Level

Third Layer

Solving Problem Based Learning Inquiry Based Learning Gaming

Presentation Level & Content Level

5. Conclusion Learning style represents an important concept in educational psychology, having significant effect on the learning process. Most of the educational hypermedia systems that deal with this issue are based on traditional learning style models. The traditional learning style models are short of important considerations regarding new technological aspects of the learning based on multimedia, information and internet. Therefore, a dedicated learning style for e-learning is strongly essential. This paper suggests Comprehensive E-Learning Style (CELS), which is a three-layer model and exhibit the properties such as e-learning aspects, and e-learning environment. The proposed model


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could measure the parameters related to each layer and adapt the learning process with the learner preferences.

As future work, we design an architecture based on CELS. We are going to implement a decision making system based on CELS's output. We will publish the result of implementation of our architecture.

REFERENCES

Alexandra, C. (2005): Learning Styles in Adaptive Hypermedia. http://wwwis.win.tue.nl/~acristea/ USI/USI8.ppt.

Bousbia, N., Labat, J.M. and Balla, A. (2008): Detection of Learning Styles from Learner’s Browsing Behavior During E-Learning Activities. Springer Berlin, Heidelberg, 5091, 740-742.

Brown, E., Cristea, A., Stewart, C., Brailsford and T.J. (2005): Patterns in Authoring of Adaptive Educational Hypermedia: A Taxonomy of Learning Styles. Journal of Educational Technology and Society 8, 3, 77- 90.

Brusilovsky, P. (2004): Adaptive navigation support: from adaptive hypermedia to the adaptive Web and beyond. Psychology journal 2, 1, 7-23.

Brusilovsky, P. and Millán, E. (2007): User models for adaptive hypermedia and adaptive educational systems. In P. Brusilovsky, A. Kobsa and W. Neidl (Eds.): The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, Vol. 4321, 3--53. Berlin Heidelberg New York: Springer-Verlag.

Carver, C.A., Howard, R. A. and Lane. W. D. (1999): Enhancing student learning through hypermedia courseware and incorporation of student learning styles. IEEE Transactions on Education 42, 1, 33-38.

Coffield, F. and Moseley, D. and Hall, E. and Ecclestone, K. (2004): Learning Styles and Pedagogy in post-16 learning: A systematic and critical review, Technical report: Learning & Skills research center. http://www.lsda.org.uk/files/pdf/1543.pdf.

Dunn and Dunn learning style model. (2003): learning style network. http://www.learningstyles.net. Gomes, A., Santos, Á., Carmo, L. and Mendes, A.J., (2007): Learning styles in an e-learning tool. In

Proceedings of The International Conference on Engineering Education, Coimbra, Portugal. Graf, S., & Kinshuk. (2008). Learner Modelling Through Analyzing Cognitive Skills and Learning Styles. In

H. Heimo, Adelsberger, Kinshuk, J. M. Pawlowski & D. G. Sampson (Eds.), Handbook on Information Technologies for Education and Training. Springer Berlin Heidelberg.

Hanan, E. D. and Khairuddin, H. (2005): Online learning style and e-learning approaches. http://www.lsum.net/dageez2.pdf. Kelly, D. and Tangney, B. (2006): Adapting to intelligence profile in an adaptive educational system. Interacting with Computers. Elsevier, 18, 385-409. Manochehr, N. (2006): The Influence of Learning Styles on Learners in E-Learning Environments: An

Empirical Study. Computers in Higher Education Economics Review, 18, issue 1, 10-14. Papanikolaou, K.A., Grigoriadou, M., Kornilkis, H. and Magoulas, G.D. (2003): Personalizing the interaction

in a Web-based educational hypermedia system: the case of INSPIRE. User Modeling and User-Adapted Interaction, 13, 213-267. Popescu, E. and Trigano, P. and Badica, C. (2007): Towards a Unified Learning Style Model in Adaptive

Educational Systems. International Conference on Advanced Learning Technologies. Niigata, Japan. Triantafillou, E., Pomportsis, A. and Demetriadis, S. (2003): The design and the formative evaluation of and

adaptive educational system based on cognitive styles. Computer & Education, 41, 87-103. Wolf, C. (2003): iWeaver: Towards .Learning Style.-based e-learning in Computer Science Education. In

Proceedings of the Fifth Australasian Computing Education, Adelaide, Australia, 273-279.

Social Network Analysis for e-assessment: reliability of formal and informal social reticles


PhD student in e-Learning & Knowledge Management

University of Macerata (Italy) E-mail: [email protected]

Abstract The growing importance of assessment through technology in virtual learning environments puts in evidence the role of Social Network Analysis in offering an interesting toolset for educators. Extracting participation data from the virtual environment (such as from forum, e-portfolio or other communitarian tools for information and document sharing), it is possible to construct a social reticle of interpersonal relationships among e-learners. The analysis of the reticle's features helps the teacher to understand the evolution of the virtual classroom and the development of relationships among students in formal settings. Although in formal settings all activities are recorded in the environment and are represented by social reticle, informal learning activities, which happens outside the virtual environment, can be analyzed only in a partial way, in function of the opening degree of the environment and on the basis of the quantity and quality of elements present and recorded in the same environment. The reliability of a social reticle in formal virtual setting is therefore questionable, because the presence of a tutor or a teacher can significatively influence the nature and the development of the reticle itself, which can be characterized by relationships that do not match with those that learners can realistically activate outside the virtual environment. Informal setting instead allows the forming and the development of a social reticle more representative of the effective relationships among learners both inside and outside the virtual environment. An interesting solution can be represented by the continue monitoring of a hybrid environment, in which the presence of tutor/teacher is limited and the social reticle is under observation, in order to highlight the stability or instability of relationships as indicator of community's production self-efficacy. This paper deals with the results deducted from a study about social networks of e-learners, both in formal and in informal settings, about parameters that can be considered significant for informal processes assessment. It puts in evidence the degree of reliability of formal social reticles in respect to informal ones, suggesting actions that teachers can do in order to monitor and assure a better performance for their virtual classrooms.. Keywords: e-assessment, formal learning, informal learning, social network analysis

1 The role of informal dynamics in learning activities and its impact on e-assessment According to directions indicated by UE about contemporary educational systems, European schools must open their curricula to informal and non-formal modalities of


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learning, through the evaluation of something tangible that learners make outside school’s boundaries. So, it is necessary to implement assessment methods based on the possibility to take and include informal learning processes and products.

Wenger’s theory (1998), about communities of practice, suggests that formal and informal learning cannot be separated, as implicit and explicit knowledge: given that informal learning represents the part of the whole learning activity (which is invisible and concerning with the reciprocal relationships among learners in a natural, spontaneous context outside school) the educator must identify some processes through which informal learning dynamics can be evidenced, and assessed.

Wenger also suggests that informal learning is at the same time a process and a product which derives from a continuous and dual interaction between to specific activities, which are participation and reification: participation is considered as mere reciprocal acknowledgement among learners; reification is considered as tangible product made by learners (such as a raw or complete product).

If the reification aspect of informal processes regards the subjectivity of educator’s evaluation, on the basis of several parameters which can respond to various competencies, the participation responds better to objective measurement that can be made by the introduction of ICT tools included, for example, in a virtual learning environment. Extrapolating the existent relationships within the social reticle of learners from the VLE, it is possible to build a sociometric matrix (Knoke & Yang, 2008) on which educators can make operations in order to evidence significant parameters about the evolution and stability of the e-learners’s reticle and can, in some cases, distinguish the role of each member, so that educators can adopt adequate actions to enhance participation level and the quality of interactions in the reticle itself.

The extrapolation method is based on a convention we designed properly according to which all learners who open a new discussion (thread) in the forum are senders towards all the reticle; then, proceeding from the bottom of the structure of each conversation line to the top, each post which responds to a previous one with a lower degree of indentation, represents a new interaction. For each new interaction, according to the its direction, it is added a unit to the previous correspondent value in the correspondent cell of sociometric matrix. Part of this method is similar to the approach described by D. Wiley about his D Crude degree in depth parameter (which is published at (http://opencontent.org/docs/discussion09.pdf, link verified on 28.07.09; see also Rossi, Giannandrea, Magnoler, 2007, pp.31-46); our convention is applied to all the threads present in the forum and not only to a chosen one (as in the case of Wiley’s parameter) and besides it differs from the treatment of threads’ openers. Our method is included in a software called “Sociomatrix Finder v.1.5”, of which the author is the owner. The software is released under Creative Commons License: the software makes automatically all the operations in the respect of the described method and the matrixes (and consequently all the reticles) resulting from the elaboration process are considered all weighed and directed networks according to the known definitions of Social Network Analysis. Although the e-assessment must be conducted by the integrated viewpoints of participative and reificative results, it is important to monitor the participative aspects in informal settings.


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This paper deals with the differences and similarities between learners’ groups which stand in different contexts: it will explore the evolution of density, of cohesion and sociometric status and their variance. It deals finally with possible actions educators can adopt in order to maintain the best social conditions in social reticles.

1.1 The creation and structure of the sample From a population of 127 teachers attending a Master Course in University of Cassino, it was selected a representative group of 30 individuals who showed an enough knowledge about informatics and the use of web 2 applications. Through a random process, the beginning group was split into two groups of 14 members. A group, called A, had a tutor who followed all members’ actions, while the B group had not a tutor (owing to the renounce of a member, B group has finally 13 components). More precisely, the tutor in B groups has the only task to clarify the final exspectation from learners, without explaining the modality and the materials that all members can use for the task. So, the tutor had no influences on the B group and the data confirmed this.

Both the groups were invited to create individual multimedia artifacts which demonstrate an enough practice in the use of web 2.0 applications. All members of each group were able to interact via online forum and an e-portfolio: a group could not view and interact with the other one. So, after twenty days, using Sociomatrix Finder software, we extrapolated several matrixes for both the groups, dividing the process into four different observation periods of five days. From the acquired matrixes, using AGNA™ software, we obtained all the necessary parameters, known in Social Network Analysis, in order to define and describe the features and their evolution for each kind of group. So, the A group is called also “formal group”, because it knew a structure, a process sequence and an internal hierarchy based on the constant presence of a tutor, fixed by an external authority; the second group, B group, is called “informal group” (Speltini & Palmonari, 1998) because it did not know any external imposed leader neither other tutor or organization’s individual as constant reference for the final task.

1.2 Density evolution in formal and informal groups The table and the graph below (table 1, graph 1) show the different values of weighed density for both the groups. Density is the ratio between the sum of all ties values and the maximum possible number of such edges. Therefore, density is representative of the capacity of making high number of interconnections among learners.

The A group has always higher values of density than the B group. The evolution of density is significantly different: while formal group increases its density in a very rapid way (I-II periods), the informal one knows a little increment, but it remains substantially constant for the major part of its life. It is easy also to notice that the formal group has an evolution more coherent with the traditional evolution of little psychological group, the models of which (Licciardello, 2001; Piave, ed, 2007) put in evidence several stages in the life of group, called “forming”, “storming”, “norming”, “performing” and “adjourning”. Given that the best period for group performances is - obviously - the performing stage; it implies that the level of interactions in this stage will be the highest: so the density parameter, which represents a sort of interdependence indicator, must be higher where the group makes its best performance. So, in the second period, formal group has its


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performing stage: in fact, the following periods show a constant decrement in density, representative of adjourning stage.

Evolution of weighed density during the four observation periods for both

the groups

A Group B Group

I 0,7619048 0,3956044

II 2,3380952 0,51648355

III 1,4714285 0,26373628

IV 0,41904762 0

Average 1,247619 0,293956

ρ 0,762512

Table 1 Graph 1 Owing to the relative restricted time (20 days) and the imminence of individual tasks,

the stages of forming, storming and norming were not dealt with the real importance by learners and this fact would be dangerous for the group’s stability. The informal group seems to have not a significant density variation: so, it appears as an equal group in which roles’ distribution is absent and the performing stage is persistent without substantial socialization needs at the beginning of its life. However, both the groups have a similar (in relative terms) evolution curve, as shown by Pearson’s coefficient (ρ).

1.3 Cohesion evolution in formal and informal groups

The table and the graph below (table 2, graph 2) show the evolution of cohesion index in both the groups. Cohesion index represents the ratio between the number of reciprocal ties and the maximum number of such ties: therefore, the cohesion represents the degree of reciprocity among learners. An high level of cohesion means an high level of scaffolding and peering activities.

Cohesion is a parameter used for binary directed networks. In this case it is applied to a weighed network, in order to evidence some possible non-reciprocal relationships (in which, for example, a learner does not send any message to a colleague who instead sent a message to him before). Maximum level of cohesion is 1.

The index increases from the first to the second period, but in the third one, while the formal group maintains its cohesion, the informal group decrements it. So, formal group has more stability in its cohesion.

Given that for both the groups the variation of cohesion index is very low, we can assume that both formal and informal groups maintain their level of cohesion during their life with the exception present at the beginning and the ending of their life in correspondence of the increment or decrement of weighed density.


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Evolution of cohesion during the four observation periods for both the

groups

A Group B Group

I 0,14285715 0,043956045

II 0,23809524 0,054945055

III 0,23809524 0,032967035

IV 0,0952381 0

Average 0,178571 0,032967

ρ 0,720082

Table 2 Graph 2

1.4 Role of members and SNA parameters The table and the graph below (table 2, graph 3) show the evolution of sociometric status’ variances in both the groups, obtained calculating the variance among all sociometric status values of the groups. Sociometric status is a parameter resulting from the sum of other two parameters, which are in-degree and out-degree. The in-degree index of a node represents the ratio between the sum of all values relative to those edges which incident to it and the total number of the nodes within the network. The out-degree index of a node instead represents the ratio between the sum of all values relative to those edges which incident from it and the total number of the nodes within the network.

So, sociometric status (SS) has an importance to determine the role of each learner within the network: learners who have higher sociometric status show in general a high level of participation; learners who have high SS with higher in-degree than out-degree show their expertise (in fact, who receives more messages than how much he sends, probably is called as consultant for suggestion); learners who have high SS

with out-degree higher than in-degree, probably show a scarce competence as beginners (in fact who sends more messages than how much he receives, is usually a person who asks for several clarifications as a newcomer).

In order to analyze better the social reticle of this group, it can be useful to create an ideal watershed between learners who have a considerable level of participation and the other learners who do not participate or have a low level of participation: so, it is necessary to calculate the average of SS: learners who have a SS higher or equal to that value, are called “followers”, while the other are considered “disinterested learners”.

In presence of an enough variance among SS values of the group, the role distribution implies that among followers it is possible to identify the leader, the expert, the beginner and the common followers, according to the previous observations (table 4).

Evolution of variance in sociometric status for both the groups

VAR(SS_A) VAR(SS_B)

I 1,876579147 0,877040101

II 13,63037026 0,850900601

III 6,551166537 0,495090689

IV 1,37497572 0

Table 3


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Graph 3 We fixed as discriminating condition the relation between the average among SS

values and their variance: if the variance value is bigger than the double of SS average, there is a role distribution, so it is possible to proceed in the analysis of roles; otherwise the group is equal and there are not leaders or experts or beginners. A typical little psychological group knows the roles’ distribution in order to face a common purpose/task.

First passage: calculate sociometric status average and define a generic

role

Second passage: if the variance of SS in the group is bigger than the double of SS average…

Role Sociometric Status

Average Role In-degree Oudegree

Follower if SS >or = SS average Leader maximum of SS

Expert higher

Beginner higher

Follower otherwise

Disinterested otherwise (in presence of SS variance = or > double SS average)

Table 4

In absence of this kind of distribution, there is an equal group. According to the data,

while formal group has a great variance in its sociometric status values, the informal one has not. The evolution of variances demonstrates that the nature of each group remains the same for the whole period of observation: in fact the formal group, according to its nature, feels to make roles since the beginning, with the maximum of role definition in the second period; then it follows the diminishing functionality of the group and roles’ distribution assume less importance towards the end of the group’s life. In the case of informal group the role’ distribution is absent from the beginning and all members have the some importance in the life of group.


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More precisely, both the groups were introduced by a tutor who explained the individual task, but the tutor, while in the A group took a beginning role of leader according to the natural evolution of formal group, leaving as soon as possible this role to members, in the informal group the tutor took a participatory level which is, in practice, insignificant in mathematical terms taking in count of every single member’s level.

2 An assessing approach for e-learners’ activity based on social reticles evolution The nature of the groups analyzed is abnormal, in the sense that they have not a common task, a common purpose, because the artifacts production is individual and each member knows that he will be evaluated on the basis of his own work; in wider terms, we can assume that the common purpose of both the groups was the scaffolding, the reciprocal help in order to make better personal performances. According to the features of Community of Practices, the necessity to share, debate and offer reciprocal helps about several themes of common interest and the contemporary absence of a specific and concrete collective task (with the exception of considering the scaffolding itself a sort of common task), means that informal knowledge (and therefore informal learning) will be probably more in equal/informal groups than in formal ones.

According to found data, informal group are more real, more reliable than formal ones: in fact, in absence of a collective task, it is normal a certain degree of leveling within a group: the roles’ distribution is a proof of a perception of being observed and evaluated during the process, during the interactions. The necessity to evidence the own position towards the observer (educator) must alter the real nature of the task, of the interactions and, as consequence, of the reticle itself. Instead, the informal group works better and maintains a certain rate of egoism, which is acceptable for the individual nature of the task and represents a proof of a natural disposition to scaffolding in contraposition to roles taking activity.

So, educators must look at informal groups as an ideal configuration to assure better learning, which includes also informal learning. In presence of a roles’ distribution (and in other words, in absence of an informal group), the educator, maintaining a high level of participation, can adopt precise actions in order to reduce significantly the variance of sociometric status among learners and transforming the beginning formal group into an informal one. These are some possible actions:

– reducing his presence in the learning process in order to leave learners in the perception of being alone and responsible of their own learning goals;

– making more responsible the leader and the expert in the reticles of their usefulness for disinterested learners and making conscious them about the importance of their roles to enhance the participation level of all members;

– helping beginners to enhance their performances and reach a sociometric status similar to that of the leader or the expert.

This considerations can be adopted in presence of individual task. Besides, it is necessary to remember that the quality and the existence itself of informal learning are connected with the dual presence of participation and reification: so, a high level of participation can imply a good level of reification, but this consequence is not automatic and can be subjected to exceptions. The necessity to assign an individual task without the


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pressure of educator’s presence is very important to grant and informal setting for the learners’ group: therefore, the evaluation of learning must take in count of processes which happen outside school’s boundaries and for this reason all the learning processes must be open to external resources and occasions of scaffolding and interactions possibly traceable in part by e-learning platform.

3 Conclusion Through the use of Social Network Analysis toolset is possible to monitor the evolution of learning process within Virtual Learning Environment, without renouncing to the complex nature of informal learning. It is also possible to identify solutions and take adequate actions in order to promote and maintain an enough level of engaging among learners which can assure, in probabilistic terms, better performances.

4 Acknowledgments The author thanks Prof. Giuseppe Refrigeri, Full Professor of Didactics in University of Cassino (Italy) for his disposability in putting him in condition to operate within the Master Course “La Professionalità del docente e del dirigente” from which illustrated data were collected. The author also thanks all teachers of Master Course, as members of the sample, who gave their availability for this study

REFERENCES

All trademarks belong to their legitimate owners. Knoke D., Yang S. (2008), Social Network Analysis, Thousand Oaks: CA, Sage Publications Licciardello O. (2001). Il piccolo gruppo psicologico, Milano, Franco Angeli Piave N.A. (2007), (ed.). La classe virtuale, Manduria (TA), Barbieri Rossi P.G., Giannandrea L., Magnoler P.(2007), Tempi e spazi per la formazione: un modello per l’on line,

QWERTY, 1, pp.31-46 Speltini G., Palmonari A. (1998). I gruppi sociali, Bologna, Il Mulino ed Wenger E. (1998). Communities of Practice. Learning, Meaning, Identità. Cambridge University Press The AGNA™ software is available for download at http://www.freewebz.com/benta/agna/download.htm

(verified on 28.07.09). Sociomatrix Finder is a software in the property of Nicolò A. Piave, released under Creative Commons

License.

Using of Suitable Software for Students Education in Clothing Technology

Magdalena Pavlova

Technical University of Sofia, College of Sliven, Bulgaria

e-mail: [email protected]

Abstract The object of this paper is the offer of suitable software, which be used in education in the subject of Clothing Technology. The main purpose is making of possibility for students self-depend work, with which the lecturer will examine their knowledge and skills. The students’ observations and logical thinking can be developed and students’ creativity can be stimulated by using of this software. This way offers. The paper presents a possibility for development of varied as contents and as purposes problems. This way realizes varied modes for progress and stimulation of the students studying, knowledge and skills in the process of their education. Keywords: education, knowledge, skills, software, clothing technology.

1 Introduction This paper offers different possibilities for using of the graphic tools in CorelDRAW X3 in the process of teaching and students education in the subject of Clothing Technology. The methods, presented in the article, have the aim to realize different ways by problems setting in the subject. The students’ knowledge, observations and graphical skills are improved, their logical thinking is developed and students’ creativity is stimulated by deciding of the problems.

2 Clothing Technology Structural and Axonometric Schemes Drawn with CorelDRAW X3

The graphical software can be the most useful in the teaching by optimal using of their drawing and modification tools (Kazlacheva, 2005; and Pavlova, Kazlacheva, 1999). Almost all drawing and modification tools are used for constructing and design of structural and axonometric schemes in clothing technology. This activity is very specific and entirely different from other kinds of design and requires different using of the graphic software tools. Each graphical software offer different and sometimes very specific ways for creating of the same geometrical objects, their basic work elements are relative to geometric primitives as point, line, segment, circle, curve, arc, rectangle etc. The most used drawing tool in CorelDRAW X3 in depending of geometric kind of scheme are (3, 4): Basic lines: constructional elements – vertical and horizontal straight lines, vertical and horizontal segments; measuring of distances – vertical and horizontal


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segments, circles; Virtual borders of the details, contours, sections: constructional elements – B-splines (in particular NURBS), horizontal and vertical segments, perpendicular lines; subsidiary elements – horizontal and vertical segments, bisectors, tangents; measuring of distances – vertical and horizontal segments, circles; Seams: constructional elements – vertical and horizontal straight lines, vertical and horizontal segments, perpendicular lines, circles, arcs, parallel lines; subsidiary elements – circles, rotation, mirror; measuring of distances – circles; Overlay pads: constructional elements – vertical and horizontal straight lines, vertical and horizontal segments, circles, arcs, parallel lines, parallel segments B-splines (in particular NURBS); subsidiary elements – horizontal and vertical segments, tangents circles, rotation; measuring of distances – horizontal and vertical segments, circles; Linings: constructional elements – touch lines, touch segments – subsidiary elements – bisectors, tangents, rotation, mirror; measuring of distances – circles; Hems: constructional elements – parallel segments, arcs, segments; subsidiary elements and modifications – mirror, rotation; measuring of distances – horizontal and vertical segments, circles;

3 Creativity, Studies and Control of Knowledge and Skills in Clothing Technology with CorelDRAW X3 Varied problems with the main purpose provoking different spheres of knowledge can be set in the educational process in the subject of Clothing Technology. Figure 1 presents an axonometric scheme of two-piece pocket. The problem is development of varied model variants on the base, shown on figure 1. By this way the students can demonstrate big knowledge volume for short time. This problem gives a possibility for stimulating creativity on the base of logical thinking and starting knowledge volume. One of the possible right solutions is presented on figure 2, where the basic variant is marked with number 1 and other five possible variants are offered. Previously drawn symbols can be uses for facilitation for quick drawing in the realization of the work – Table 1.

Fig. 1. Axonometric scheme of two-piece pocket


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Fig. 2. Axonometric schemes of model variants of two-piece pocket

Table 1. Exemplary group of previously drawn symbols

Group symbols Use of symbols

1 Seams

2 Bordering of the details /prepared segment and details/

.... ........ Others

13 Overlay details

14 Hems and bends

15

Linings

16 Detail virtual border

For students with suggestive thinking and good creativity the following aim is

suitable: Offering modeling variants of detail, different from the model on figure 1. The solution is presented on figure 3. In this case six variants of one-piece pocket are presented.


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Fig. 3. Axonometric schemes of model variants of one-piece pockets

Figure 4 presents sketch of lady’s skirt and axonometric scheme of skirt section with one-piece waist-band. The aim is development of two new axonometric sections in the same technology, but with two-piece waist-band with different variants of overlay. The possible solution is presented on figure 5.

More complicated mode of the problem from figure 4 is presented on figure 6. The

purpose is the project of technology only on base of a scheme and offering of model variants for two-piece waist-band. Two possible solutions are presented on figure 7.

Fig. 4. Axonometric scheme of lady’s skirt section with one-piece waist-

band

Fig. 5. Axonometric scheme of lady’s skirt section with two-piece waist-band


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An interesting problem is shown on figure 8. There is a part of technology for making of

a free band and by this incomplete plan, the students must develop the other technological stages and band working pattern. The solution of this problem is presented on figure 9.

Fig.8. Band scheme Fig.9. Band technology scheme

Figure 10 presents a variant of the work, which requires only repetition of the gained knowledge and skills, concentration and observation. In this case there is only one right decision, in difference with the last presented problems. The right solution is shown on figure 11. This work can be set in the opposite order in dependence on the aim of studying.

The problem, presented on figure 12, requires student must find out made mistakes and errors in the draft. The problem can be set by two ways. In the first way the students must mark the made mistakes, but in the second way they must correct them. The two ways are presented on figure 13 and figure 14.

Fig.10. Structural schemes of seams

Fig.11. Axometric schemes of the seams, presented on figure 10

Fig. 6. Lady’s skirt sketch Fig. 7. Axonometric scheme of lady’s skirt section

with two-piece waist-band


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Fig.12. Axonometric

scheme of multilayered decorative element

Fig. 13. Marking of mistakes in the scheme on

fig. 12

Fig. 14. Correction of mistakes in the scheme on

fig. 12

The final problem, presented in this paper is offered on figure 15. It is connected with the adding of additional detail to ready technological element. The work requires excellent knowing of technology for making, excellent drawing skills and creativity. These kinds of problems give possibility for different solutions. One possible decision is shown on figure 16.

4 Conclusions Multi model virtual card-index with inter replaced details can be developed for optimization and solutions of presented problems. This data base will give possibilities for student for biggest volume of work. In this way the students’ knowledge can be grown and skill can be improved. Students’ creativity can be stimulated. Examination tests for control of stages in education in Clothing Technology can be developed on the base of presented problems in the paper. Interactive algorithms, useful for virtual education for students or distant study can be developed on the same base.

REFERENCES Kazlacheva Zl., (2005) Optimum Use of Drawing Tools in CAD Systems in Automated Apparel Design.

Trakia Journal of Sciences, Vol. 3, 2005, No 7, p. 20-23. 2005. Pavlova М., Zl. Kazlacheva, (1999): The Use of Software of Stardraw in Students Education in Clothing

Technology. Sofia, “Textile Conference –99”. http://www.clubic.com/actualite-coreldraw-graphics-suite-x3.html http://www.corel.com/servlet/Satellite/fr/Content.html

Fig. 15. Axonometric scheme of

decorative element Fig. 16. Axonometric scheme of multilayered decorative element

An Approach to the Study of Science for Young Learners

Daniela Popescu1, Flavius Popescu2

(1) Constantin Brancusi University in Tg-Jiu,

Faculty of Letters and Social Sciences 1, Grivitei Street, Tg-Jiu, Romania

E-mail: [email protected] (2) University of Edinburgh, School of Informatics

10 Crichton Street, Edinburgh, EH8 9AB, United Kingdom

Abstract In the past years there has been noticed a certain decrease in the number of students that choose science as their subject of study for a university degree. One of the main reasons generating this climate is the extent in which this subject is made accessible to children at an early age. As long as school curricula restrict the pupil's time and opportunity to study preferred subjects more in-depth, developing a field of interest is a difficult step. Some schools have taken action in this perspective and got involved in a number of activities on different topics or have completely reconfigured their curricula to allow time for the introduction of a set of optional courses. Moreover, pupils at schools which have not implemented such programmes have the opportunity to subscribe for a summer course. That is what stimulated us to organise a summer activity in the form of a computer science and engineering course, which promised to deliver a unique blend of skills including computer programming, robotics, numeracy, teamwork, communication and practice of the English language.This document will explain the structure of a robotics course designed for young learners. Potential content for the course is revealed and points on how to deliver the activity are provided. Keywords: Programming, Robotics, Training, Young Learners

1. Introduction The main challenge of the classroom of tomorrow is to develop new types of courses meant to prepare students who pursue a scientific career. The first issue is that of the trainers being able to teach courses that can best serve students’ interest in science. How to develop such a course, how to deploy the right education environment, what can be done about students’ poor motivation, how to make use of skills like critical thinking, problem solving, collaboration or self-direction are questions that could be an obstacle for many. Therefore we thought of sharing our experience in designing a computer science and robotics course. The following guide offers a detailed picture of the structure of the course, providing any trainer with a stream of ideas and how to implement them in order to help students make the most out of this experience.


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2. Course characteristics As this course is not based on previous programming experience, it is important to take some time, on the relevant class, and explain the idea behind an algorithm and its fundamental control structures. Associations and real-life examples can be given so as to aid the understanding of the relevant concepts.

The ability to work in a team is an important skill that this course greatly relies on. Students will form teams of 2-4 members. Whether one team will effectively complete all the tasks throughout the course or not depends on how well the members will organise and divide tasks among themselves.

For the length of the course, each team will be provided with a LEGO® Mindstorms® robotics set, along with building instructions, and a computer which includes special software that can be used to program the robot. All aspects of the programming part will be thoroughly explained. It will be a good opportunity for all team members, whether they have met any of the notions before or not, to get hold of a theoretical basis and immediately visualise the effects of applying it in practice.

The students are not required to bring any materials from home. If the course is organised as a summer activity, this fact will greatly help the instructors to easily put an accent on the entertainment element of the course, while children will not feel like they are part of the traditional school environment. However, as there is an educational side as well, one way of combining the two is to offer students personalised notebooks and pens. They should be encouraged to use them and write down what they consider to be important.

Another important aspect of organising the course is feedback. This can be used by instructors to improve the activity and try to meet students' expectations and it should be requested from them at the end of each day. A quick and easy solution that can be implemented even from the first day is to place three bowls at the exit. One of them should be of different colour and will be empty. Each of the other two will contain labels with a happy face and a sad one, respectively. When the students finish their activity and prepare to leave they are asked to choose a label from one of the two bowls and place it in the third one, according to their impression on the course. This way it is easy to see how well the students get along with the course structure and the instructors will often be able to tell what went well and what did not. Alternatively, another bowl with a neutral face can be added. This type of feedback can be easily collected and allows an immediate analysis of the day.

After the first few days of the course, the students will have a better idea of how it is working, how much they understand from its content and what is not properly organised. At this point, more detailed feedback can be collected in the form of a questionnaire or a small sheet of paper that allows them to express their honest opinion. A good way to get the most out of the feedback, especially since children are the ones who provide it, is to ensure a private space where they can write their ideas. In most cases, they will think about more aspects if they are not distracted by their curious team mates.

3. Course description The course content is organised in five days, as follows.


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3.1. Day 1: Welcome! Let’s build a robot together! The instructors welcome the students. They first introduce themselves and then the course, briefly pointing out its main stages. Having a short discussion on how the students should approach the trainers and behave during the course helps create a better working environment.

The introduction must not take a lot of time. However, the students should understand that the success of their team depends on individual effort and that they must be patient and listen to what the ones around them have to say. Creativity and the ability to sustain ideas will ultimately prove to be some of the main factors that make the difference between being able to fulfil a task or not.

Colour-coded teams with equal number of members (if possible) are randomly formed. Team members then have the chance to meet each other and choose a name and logo for themselves.

The teams are now ready to begin their first task, which is to follow a set of given instructions in order to build a vehicle robot. The instructions will graphically reveal, step by step, how to attach the given LEGO pieces together. At each step, there is a drawing with all the pieces that should be assembled during that step. Each team is also provided with a 1:1 diagram depicting measurements for variable-length parts such as axles, bricks, etc. Three-dimensional views of the growing construction are shown in order to help the students check proportions between individual pieces. The teams should take account of that and carefully select from the kit the correct parts that must be assembled.

Once all teams finish building their robot, they have the opportunity to learn about navigation through the intelligent brick's system of menus and watch the robot perform some demo programs which can be found in the memory of the NXT brick. These programs are meant to give students a preview of the types of programming that follow in the next few days.

3.2. Day 2: The MINDSTORMS NXT programming environment. Basic movement and sensor usage Programs for the NXT can be created using the MINDSTORMS NXT drag-and-drop programming environment, which is included in the robot set. It is based on programming blocks which serve different purposes and it is easy to understand and use. The blocks can be dragged onto a program “brick” which determines the flow of the program. Simple programs which involve basic movement and sensor usage can be quickly created. For more complex programs, many more blocks must be dragged into the program and connected between themselves, which can be sometimes cumbersome and requires a lot of space on the screen. A programming language usually serves the development of larger applications, but for most programs encountered in this course, the drag-and-drop environment can be efficiently used.

In the programming environment, the blocks are sorted into categories, or palettes: common, complete and custom. The common palette contains all the blocks which can be used for basic movement and sensing, including some extra features such as playing sounds or displaying text.

Throughout the day, the common blocks will be explained i.e. how they can be used to achieve desired results, what options control which type of robot behaviour. The


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instructors will aim to gradually introduce students to programming, while altering between a theoretical explanation and a practical exercise. By assuming this approach, the students will be able to understand the notions better and even more importantly, they will have the ability to ask questions after observing the behaviour of the robot during each experiment.

3.3. Day 3: Revision. Advanced blocks By the end of this day, students should be able to create programs which use all sensors. They should also have all the necessary training that will allow them to explore their creativity and come up with working solutions to problems raised in the following days.

In order to learn some more programming techniques, the students can attempt to solve more exercises. These are meant to challenge them and allow each team to plan and develop solutions, with help from the trainers. Exercises can be similar, but are not limited, to the following examples:

1. Make the robot move in a square pattern: how would you alter the length of the square side?

2. Make the robot move in a circle pattern: how do you control the length of the circle radius?

3. Your robot has a claw mechanism for grabbing things: how would you use it to pick up a ball?

4. Navigate to the nearest object! Several items will be placed around your robot, at various distances; your robot should detect the one that is closest, move towards it and stop in front of it.

5. Create a program to make the robot sound-sensitive with regards to its speed. If there is a lot of ambient noise, speed should be close to maximum; if there is complete silence, its speed should be close to 0.

6. Transform your robot into a fearless navigator! Use any sensors that you find necessary and create a program that, once run, will allow the robot to go through a random obstacle course. See how far it gets, and if it gets stuck, think about what you have to do to make it go even further.

3.4. Day 4: Preparations for the competition Throughout this day, teams have the opportunity to see the competition mat, and think about solutions to its challenges. The rules are thoroughly explained and students are allowed to ask questions.

The purpose of the competition is to stimulate students' creativity and challenge their minds, while evaluating their ability to work with their team-mates and come up with efficient solutions to the missions, all under the pressure of time.

The competition mat contains several items, some of which can be obstacles or they can be related to one or more of the missions. Somewhere on the mat, a base area can also be found. This is the 'launching pad' for the robot.

The teams must carefully choose the missions they want to solve. It is not necessary to successfully complete all missions. Teams should select from the ones that they feel they can approach better. The goal is to collect as many points as possible and sometimes, solving many of the easier missions will be worth more than the result of all the hard-


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work that was put in for a few difficult missions. The competition is timed, and once a team is ready, their robot will only have a certain amount of time (usually less than a few minutes) to run the programs.

The base area acts as a 'pit-stop' while the timer is running, so the robot, after completing one or more missions, can be programmed to return to the base. One of the team members can then quickly change to the next program and send the robot in its attempt to solve the next mission(s).

If the robot is touched outside the base, it should be immediately taken to the base and the team will be given a penalty, in form of points deduction, warnings, etc. Several touch-penalties could lead to the round being stopped (timer set to 0).

The teams are allowed to modify their robot (arms, parts, etc.) if they find necessary. However, they should take into account that, while an additional arm will do the job for one of the missions, dragging it around the mat for the other missions which do not require its help can slow the robot down, or even stall it. A solution to this problem is to group the missions accordingly and take advantage of the robot entering the base for a program change. A team member can then quickly remove the no-longer needed arm from the robot.

3.5. Day 5: Competition time! The teams are now ready and the competition can start. Each team is given a chance to send their robot and acquire as many points as possible in one round. There is more than one round, and the one that is marked highest is the final score for that team.

When the timer stops, a referee assesses the situation and awards points for the missions that are successfully completed at the end of the round. Note that if the robot completes a mission but then, while attempting a different mission or otherwise, it accidentally interferes with it (e.g. moves an item away from its location after it has already been placed there as part of the task) the mission is not considered successful. In order to be so, it must last to the end of the round. If, however, after the timer ends, the robot program keeps running and then it interferes with any of the missions, no points are lost. The robot should be immediately picked up, once the timer reaches zero, and any damage done to the objects on the mat must be taken account of.

Here is a sample sheet containing rules and scoring for a competition. Notice that the mat used in this competition was designed with three base areas, each with its own timer. The teams are allowed to choose which base(s) they want to compete in and for each of those, they are given two chances to score as many points as possible. - Base I - basic movement and sensor usage

Countdown: 1 minute Missions: Knock down the cuboids: yellow, green and red cuboids are worth 5, 2 and 10 points

respectively. Hit the checkpoints: checkpoint 1 is worth 20 points, checkpoint 2 is worth 25 points. Cross the finish line! Have the robot placed at Checkpoint 2 before the timer ends. (15

points) Bonuses: Time Attack: complete all tasks in less than 25 seconds. (10 points)


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Nice and clean: complete all tasks with no penalties. (15 points) - Base II - construction & creativity

Items from the base area used in missions: 4 cuboids (2 blue, 2 green) Countdown: 50 seconds Missions: Special delivery: move the two blue cuboids to Checkpoint 3 (worth 20 points if both

are partially touching the checkpoint area and 25 points if they are completely placed inside the area). Move the two green cuboids to Checkpoint 4 (worth 30 points if both are partially touching the checkpoint area and 35 points if they are completely placed inside the area).

Return to base: have the robot placed back at Base II before the timer ends. (5 points) Bonuses: Time Attack: complete all tasks in less than 30 seconds. (10 points) Nice and clean: complete all tasks with no penalties. (10 points)

- Base III - advanced sensor usage Countdown: 45 seconds Mission: reach Checkpoint 5. (40 points) Bonuses: Time Attack: complete the mission in less than 30 seconds. (15 points) Nice and clean: complete the tasks with no penalties. (10 points) Penalties for all bases: Displacing any of the standing orange cuboids from their original location results in a

deduction of 15 points per cuboid displaced. Touching the robot while it is outside the base results in a deduction of 5 points. In

addition it counts as a warning, with the third warning setting the countdown timer to 0 minutes 0 seconds and thus ending the round.

Crossing the dotted red lines with all wheels forces the team members to touch the robot and bring it back to base.

Displacing the aiding obstacles will result in a deduction of 10 points.

REFERENCES Books: Dasgupta, S., Papadimitriou, C. and Vazirani, U. (2006): Algorithms. McGraw-Hill Science/Engineering/

Maths. Deitel, P. J. and Deitel, H. M. (2007): C++ How to Program, 6th edition. Prentice Hall. Ferrari, M. and Ferrari, G. (2002): Building Robots with LEGO® MINDSTORMS. Syngress Publishing, Inc.,

Rockland. Russell, S. and Norvig, P. (2002): Artificial Intelligence: A Modern Approach, 2nd Edition. Prentice Hall. Sierra, K. and Bates, B. (2005): Head First Java, Second Edition. O'Reilly Media, Inc., Sebastopol. Willis, J. (1996): A Framework for Task-Based Learning. Harlow, Essex: Longman. Internet Sources: LEGO Mindstorms website http://mindstorms.lego.com

News and Events

ICVL 2009 Web site: www.icvl.eu/2009 September 14, 2009

• Review Process - Accepted papers: M&M - 3, 4, 5, 9, 16, 29, 31, 32, 45, 52, 53, 54,

57, 59, 61, 64, 66, 68; TECH - 21, 24, 55, 56, 58, 67, 70, 80, 88, 89; SOFT - 25, 26, 27, 38, 41, 46, 62, 75, 76; IntelEDU - 1, 2, 19, 30, 33, 36, 37, 39, 40, 42, 71, 72, 73, 74, 79 (Total = 52 from 103 received) | LINK

• LOCATION OF THE CONFERENCE - The Conference (The Conference has no Fee) will be held in the Technical University "Gheorghe Asachi" of Iaşi, Faculty of Electrical Engineering, Bd. Professor Dimitrie Mangeron, nr. 51- 53, 700050 IASI, ROMÂNIA Tel : 0040-232-278683; Fax: 0040-232-237627 E-mail: dandorin[at]tex.tuiasi.ro (Prof. Dan Dorin) and decanat[at]ee.tuiasi.ro | Webpage: www.tuiasi.ro/facultati/eth/ | LINK | The ICVL 2009 will be held in conjunction with The 7th National Conference on Virtual Learning (CNIV 2009)

• Proceedings of ICVL 2009 - The Conference Proceedings is in preparation and will be sent for printing, Bucharest University Press (ISSN 1844 - 8933)

• ICVL 2009 SCHEDULE - "Gheorghe Asachi" Technical University of Iaşi, ROMANIA; Information and Contact: Prof. DAN DORIN, E-mail: dandorin[at]tex. tuiasi.ro / Prof. G. Albeanu, galbeanu[at]gmail.com / Prof. M. Vlada, vlada[at]fmi. unibuc.ro | Please inform us about your participation not later than October 15, 2009.

FRIDAY, October 30, 2009 15:00-19:30 Registration 19:30 Welcome Reception (Cocktail) SATURDAY, October 31, 2009 8:30-9:00 a.m. - Registration Desk 9:00- 12:00 - Conference opening and Plenary Session 12:00-13:00 Coffee Break 13:00-16:30 Full Papers SUNDAY, November 1, 2009 8:30- 12:00 - Full Papers 12:00-13:00 Coffee Break

September 2, 2009

• BrusselsAgenda.eu - ICVL 2009 published on BrusselsAgenda.eu;

BrusselsAgenda.eu is a new portal dedicated exclusively to European Affairs events that take place in Brussels, in Europe and in the world | http://www.brusselsagenda.eu/


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• Christiaan Huygens 2009 - Christiaan Huygens Science Award 2009 goes to Raluca Marin-Perianu; On Wednesday, 7 October 2009, the Netherlands’ Education Minister Ronald Plasterk will present Dr Raluca Marin-Perianu with the Christiaan Huygens Science Award for Information and Communication Technology; Raluca Marin-Perianu was born in 1978 in the Romanian capital Bucharest | http://www.utwente.nl/ | http://www.christiaanhuygensprijs.nl/

• Chemical structure - The detailed chemical structure of a single molecule has been imaged for the first time (Single molecule's stunning image By Jason Palmer): http://news.bbc.co.uk/ | IBM Research - Zurich's photostream: http://virtuallearning.ning.com/

• MT Europe - The MacTutor History of Mathematics, Created by John J O'Connor and Edmund F Robertson: http://www-history.mcs.st-and.ac.uk/ | Birthplace Maps | Romania

• TEC - Technology Evaluation Centers (TEC): http://www.technologyevaluation.com/ | http://virtuallearning.ning.com/

August 22, 2009

• Neorons & Stars - 1011 = The number of neurons in the Human Brain = The number

of stars in the Galaxy; Source: The Picower Institute for Learning and Memory at Massachusetts Institute of Technology (MIT), Cambridge, USA | http://web.mit.edu/picower/

• Molecular Computer - A molecular computer is formed by ... (United States Patent 6430511; University of South Carolina, Columbia, SC) | http://www.freepatentsonline.com/6430511.html | Theory and Construction

• Hubblesite - Material credited to Space Telescope Science Institute (STScI) on this site was created, authored, and/or prepared for NASA under Contract NAS5-26555: http://hubblesite.org | News Center | Saturn

• EdNET 2009 - Educational Networking Conference, September 13-15, 2009, Chicogo, Illinois, USA | http://www.ednetconference.com/

July 29, 2009

• Announcement - Registration and messages received after July 31 2009 will receive

a reply after AUGUST 17 2009 • MIT News - July 29, 2009: Why we learn more from our successes than our failures.

MIT study sheds light on the brain's ability to change in response to learning (Earl K. Miller, the Picower Professor of Neuroscience, and MIT colleagues Mark Histed and Anitha Pasupathy) - http://www.mit.edu/ | "Learning from our successes not our failures" - http://virtuallearning.ning.com/

• MIT - Massachusetts Institute of Technology - http://www.mit.edu/ | Stellar - MIT Course Management System - http://stellar.mit.edu/courseguide/ | Teaching Scientific Writing by MIT - http://virtuallearning.ning.com/

• Yuri Gagarin - Yuri Alekseyevich Gagarin (1934-1968), On 12 April 1961, Gagarin became the first human to travel into space, launching to orbit aboard the Vostok 3KA-2 (Vostok 1) | http://en.wikipedia.org/wiki/Yuri_Gagarin; unfortunately, not caught in time in 1969 when Armstrong walked on the moon

• Neil Armstrong - July 21, 1969 at 2:56 UTC - Neil Alden Armstrong, First Moon walk (Apollo 11) | http://en.wikipedia.org/wiki/Neil_Armstrong | http://virtuallearning.ning.com


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• Aurel Vlaicu - Aurel Vlaicu (1882 – 1913) was a Romanian engineer, inventor, airplane constructor and early pilot | http://en.wikipedia.org/wiki/Aurel_Vlaicu | http://www.earlyaviators.com/evlaicu.htm; That's why in 1913, he started to build a new plane, the Vlaicu 3. It was planned to be built entirely of metal, the idea itself being remarkable for the time. The first all metal planes only appeared much later. During that project, he learned that a foreign pilot intended to make the same flight.

July 20, 2009

• Cambridge:800 and Darwin:200 - University of Cambridge - The 800th

Anniversary (1209 - 2009); Source: http://www.800.cam.ac.uk/ | Charles Darwin - 200 years since his birth; http//www.800.cam.ac.uk/ | http://virtuallearning.ning.com

• Blogger and Twitter - E-Learning and Educational Technology: Peter Jones, Steve Wheeler, James Clay, Tom Kuhlmann ... (UK) | http://virtuallearning.ning.com

• H2CM - 'H2CM' = Hodges' Health Career Model (Hodges model: Integrative conceptual framework for creativity and reflection); Peter Jones (UK): http://www.p-jones.demon.co.uk/, http://hodges-model.blogspot.com/ | http://icvl4all.ning.com/

• ALT - The Association for Learning Technology (ALT) | http://www.alt.ac.uk/index.html | ALT 2009 | ALT 2008-2101 Strategy (.pdf)

• OnLine Info - Learning Online Info; Blog for E-Learning and Educational Technology News and Resources | http://learningonlineinfo.org/ | U.S. - Study 2009 | JISC Report 2009

July 10, 2009

• Imagine Cup 2009 - Imagine Cup Student Competition 2009 - First place: Romania,

Faculty of Computer Science, "Al. I. Cuza" University, Iasi | http://imaginecup.com | http://virtuallearning.ning.com/

• Submission - Address [email protected] no longer available. Addresses are available for registration: vlada[at]fmi.unibuc.ro or marinvlada[at]gmail.com. Please check your registration receipt if you registered online.

June 16, 2009

• Elsevier - Elsevier serves more than 30 million scientists, students, and health and

information professionals worldwid: Science & Technology and Health Sciences (2333 Journals) - http://www.elsevier.com/ | ALL JOURNALS (Prospective authors should send their manuscript(s) in Microsoft Word or PDF format to elsevier[at]live.co.uk a)

• Springer Link - SpringerLink is one of the world's leading interactive databases for high-quality STM journals, book series, books, reference works and the Online Archives Collection: http://www.springerlink.com/ | ALL JOURNALS

• Academy Publisher - Academy Publisher is an independent publisher specializing in the publication of high-impact journals, proceedings and books, in both printed and online versions, across all areas of science and technology: http://www.academypublisher.com


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• ICEL 2009 - The 4th International Conference on e-Learning, University of Toronto, Canada, 16-17 July | http://academic-conferences.org/icel/icel2009/

• ICGIP 2009 - The International Conference on Graphic and Image Processing, Kota Kinabalu, Malaysia, Nov. 13-15 | http://www.iacsit.org/icgip/

• ICDCS 2009 - TheInternational Conference on Distributed Computing System, 4 December to 6 December 2009 Frankfort, Germany | http://www.icdcs.org/

• eCASE 2010 - 2010 International Conference on e-Commerce, e-Administration, e-Society, e-Education, and e-Technology 25-27 January 2010 Macau, China | http://www.e-case.org/2010

• PLAT 2010 - The 5th Psychology Learning and Teaching conference, 30 June 2010 Edinburgh United Kingdom | http://www.psychology.heacademy.ac.uk/plat2010/

May 30, 2009

• Intel ISEF 2009, Reno, Nevada, SUA - Intel International Science and Engineering

Fair. A program of Society for Science & the Public - www.intel.com/education/ISEF/ | Winners | Intel ISEF 2008 (Video) - Videos Posted by Intel International Science and Engineering Fair | Intel ISEF 2010

• ICT results - the ICT results on INTUITION project: http://cordis.europa.eu/ - http://cordis.europa.eu/ictresults | "Virtual reality looks exotic to the general public." Dr. Angelos Amditis, Institute of Communication and Computer Systems in Athens, http://www.intuition-eunetwork.org/

• IST World - Find partners, technologies, competencies and trends (FP5,FP6,FP7): The IST World portal offers information about experts, research groups, centers and companies involved in creating the technologies for the growing information society. Focus of the service is the expertise and experience of relevant players in European countries. | www.ist-world.org/

• ICL 2009 - 12th International Conference on Interactive Computer aided Learning Villach, Austria 23-25 September 2009 | www.icl-conference.org

• ICERI 2009 - The International Conference of Education, Research and Innovation, Madrid (Spain) on the 16th, 17th and 18th of November | http://www.iated.org/iceri2009/

• John von Neumann - The John von Neumann Architecture of Computer Systems: http://virtuallearning.ning.com/ | More

April 22, 2009

• New - The ICVL 2009 is held under the auspices of the EYCI - the European Year of

Creativity and Innovation 2009 - http://create2009.europa.eu/ • 2009 European Year - 2009 European Year of Creativity and Innovation: "Europe

needs to boost its capacity for creativity and innovation for both social and economic reasons. That is why the Commission has adopted a proposal to declare 2009 the European Year of Creativity and Innovation" - http://create2009.europa.eu/ | http://www.creativity-innovation.eu | http://www.lets-create.eu/

• WDL - The World Digital Library (WDL) makes available on the Internet, free of charge and in multilingual format, significant primary materials from countries and cultures around the world - http://www.wdl.org | Mission


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• CiteSeerX - Scientific Literature Digital Library and Search Engine: Documents, Citations, Authors, Venue Impact Ratings - http://citeseerx.ist.psu.edu | The Pennsylvania State University | The College of Information Sciences and Technology

• AuthorMapper - AuthorMapper searches journal articles and plots the location of the authors on a map - http://www.authormapper.com/ | http://icvl4all.ning.com

• Invitation - Invitation to the study: Infusing 21st Century Thinking Skills Into the T&L Environment - http://icvl4all.ning.com

April 4, 2009

• NetLogo - NetLogo is a programmable modeling environment for simulating natural

and social phenomena. It was authored by Uri Wilensky in 1999 and is in continuous development at the Center for Connected Learning and Computer-Based Modeling - http://ccl.northwestern.edu/netlogo/ | The NetLogo environment enables exploration of emergent phenomena. It comes with an extensive models library including models in a variety of domains such as economics, biology, physics, chemistry, psychology and many other natural and social sciences - LINK

• MathsNet - MathsNet.net is an independent educational website providing free mathematics resources to the education community. Its aim is to offer truly interactive resources that are both wide and deep in terms of their applicability and usefulness - www.mathsnet.net/index.html | Logo the TURTLE - interactive

• Scribd - Scribd is the place where you publish, discover and discuss original writings and documents. More than 50 million people each month are finding or sharing fun, functional or fantastical writings and documents on Scribd.com and tens of thousands of other websites that have embedded Scribd's document reader - http://www.scribd.com/ | TRENDS OF ELEARNING: LEARNING - KNOWLEDGE - DEVELOPMENT (M. Vlada, A. Adascalitei, R. Jugureanu - eLSE 2009) Learning-Adventures (Zaid Ali Alsaoff)

• YouTube/Edu - Videos and channels from college and university partners - http://www.youtube.com/edu

• Visiblebody - The Visible Body is produced by Argosy Publishing. Its diverse groups make Argosy Publishing an award-winning provider of content and technology to the medical, pharmaceutical, scientific, consumer products, television, and educational communities - http://www.visiblebody.com/ | The Heart - DEMO

March 12, 2009

• GESS - GEF - The Global Education Forum, 2009, the only conference for education

professionals in the United Arab Emirates(UAE) and the GCC states, 10-12 MARCH 2009 AIRPORT EXPO, DUBAI, UAE | http://www.gulfeducation.info/

• ISTE - ISTE is a not-for-profit organization dedicated to supporting the use of information technology to aid in learning, teaching of K-12 students and teachers | www.iste.org | 2009 Global Forum on Innovation and Technology in Teaching and Leading - www.iste.org | Global Forum on ICT in Dubai, April 15-18, 2009


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• BIEE 2009 - Beijing International Education Expo is the sixth edition of the event. This is the three day event which will take place at China International Exhibition Center (CIEC) on dated 13-15 June 2009 - www.edufair.com.cn/ | LINK

• Futurelab.org - Futurelab is passionate about transforming the way people learn. Tapping into the huge potential offered by digital and other technologies, we develop innovative resources and practices that support new approaches to learning for the 21st century | www.futurelab.org.uk

• EdTechTalk - Collaborative Open Webcasting Community - www.edtechtalk.com | ICVL 2009 | LINK

• EduLearn09 - The International Conference on Education and New Learning Technologies will be held in Barcelona (Spain), on the 6th, 7th and 8th of July, 2009. - http://www.iated.org/edulearn09/

• ECKM 2009 - 10th European Conference on Knowledge Management Università Degli Studi Di Padova, Vicenza, Italy 3-4 September 2009 - http://www.academic-conferences.org

March 06, 2009

• Intel Strengthens Commitment to Education in Romania - BUCHAREST,

Romania, March 4, 2009 – Intel Corporation Chairman Craig Barrett today made an impassioned speech on education to Romanian university students, telling them that education and technology are key to creating an innovation economy; In related events, University Politehnica of Bucharest (UPB) bestowed the honorary title of Doctor Honoris Causa on Barrett today during a special ceremony at the university | http://www.intel.com/ | Video-The Money Channel

• 1959, Invention of the integrated circuit - Intel Celebrates 50th Anniversary of Integrated Circuit; Intel CTO Makes Technology Predictions in Honor of Inventor’s Day; In 1959, inventor Robert Noyce, who later became one of the founders of Intel, created the first planar integrated circuit made from silicon. Noyce’s invention consisted of a complete electronic circuit inside a small silicon chip and helped revolutionize Silicon Valley’s semiconductor industry. Virtually all integrated circuits made today use some form of Noyce’s manufacturing technique. http://blogs.intel.com/technology/2009/02/whats_your_favorite_invention.php

• 1971, Invention of the Microprocessor - Fascinating facts about the invention of the Microprocessor by M.E. "Ted" Hoff in 1968; In November, 1971, a company called Intel publicly introduced the world's first single chip microprocessor, the Intel 4004 (U.S. Patent #3,821,715), invented by Intel engineers Federico Faggin, Ted Hoff, and Stan Mazor. | www.thocp.net/biographies/hoff_ted.html |

February 16, 2009

• ICVL Project - ICVL 2009 (www.icvl.eu) | The ICVL site have been actualised

(www.icvl.eu/2009/) | Location: "Gh. Asachi" Technical University of Iasi, Faculty of Electrical Engineering , JASSY, ROMANIA. Europe

• First Call for Papers - ICVL 2009 | http://atlas-conferences.com | http://www.conferencealerts.com | | http://www.ad-astra.ro/ | Link

• E-learning - Conferences Worldwide 2009 | http://www.conferencealerts.com/

Authors Index Abbaspour Solmaz, 300, 308 Albeanu Grigore, 52 Aldea Costel, 106 Allegra Mario, 91, 257, 349, 357, Antohe Ştefan, 364 Beldiman Liviu, 189 Biswas Pradipta, 203 Blaga Mirela, 134 Bordeianu C. Cristian, 112 Bostan Carmen-Gabriela, 364 Bragaru Tudor, 164 Canepa Dorin, 189 Chircu Florentina Alina, 322 Cirnu Carmen Elena, 393 Codreş Alexandru, 223 Codreş Bogdan, 223 Conte Massimo, 40 Craciun Ion, 164 DăneŃ Nicolae, 276 Dineva Snejana, 231, 239 Dobre Iuliana, 385 Ducheva Zlatoeli, 239 Feraru Silvia Monica, 119 Florea Ion, 106 Fulantelli Giovanni, 91, 257, 349, 357 Garabet Mihaela, 401 Garakani Mehdi, 316 Gentile Manuel, 91, 257, 349, 357 Ghosh Sharmistha K., 203 Hamilton Peter, 331 Harlock Simon, 134 Hendijanifard Fatemeh, 300, 308 Ionita Liviu, 380 Istrate Olimpius, 25, 341 Jugureanu Radu, 25 Kardan Ahmad A., 142, 151, 300, 308, 316, 408 La Guardia Dario, 91 Landau H. Rubin, 112 Maxim Ioan, 172 Mihai Aura, 214 Modaberi Somayeh, 142, 316 Neacşu Ion, 401

Nedelko Zlatko, 393 Nedeva V., 231 Noorani Seyedeh Fatemeh, 408 O’Duffy Eileen, 331 Oprea Mihaela, 265 Paez J. Manuel, 112 Paliokas Ioannis, 83 Pastina M., 214 Patrick Wessa, 60 Pavlova Magdalena, 424 Pehlivanova Margarita, 239 Perera Indika, 98 Petre Elia, 265 Piave Nicolò Antonio, 247, 416 Popescu Daniela, 430 Popescu Flavius, 430 Popescu Virgil, 78 Pristavu Ioana, 158 Puşcaşu Gheorghe, 223 Rădescu Radu, 284, 292 Radu Cătălin, 195 Roceanu Ion, 78, 195 Ronsivalle Gaetano Bruno, 40 Sahin Mehmet, 214 Savin Irina-Isabella, 158 Scheiber Ernest , 181 Şişu Adrian, 292 Socaciu-Lendvai Tiberiu, 172 Speily Omid R. B., 142 Stancu Alexandru, 223 Stănescu Ioana, 195 Ştefan Antoniu, 195 Ştefan Veronica, 195 Şuşnea Elena, 371, 376 Taibi Davide, 91, 257, 349, 357 Teodorescu Horia-Nicolai, 119 Ticheler Nathalie, 127 Tudor Irina, 380 Tudor Raul, 284, 292 VelŃan Radu, 284 Vlada Marin, 25, 40 Yaldiz Süleyman, 214 Zahmatkesh Shima, 151

Tiparul s-a executat sub c-da nr. 2470/2009 la Tipografia Editurii UniversităŃii din Bucureşti