adaptive collaborative unix meta-tutorial for computer science students

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Adaptive Collaborative Unix Meta-tutorial for computer science students Adaptive Hypermedia & Assistive Technologies

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Adaptive Hypermedia & Assistive Technologies. Adaptive Collaborative Unix Meta-tutorial for computer science students. Rosta Farzan, Masters Student Math & Computer Science Department California State University, Hayward [email protected]. Hilary J. Holz, Asst Professor - PowerPoint PPT Presentation

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Adaptive Collaborative Unix Meta-tutorial

for computer science students

Adaptive Hypermedia & Assistive Technologies

Rosta Farzan, Masters StudentMath & Computer Science DepartmentCalifornia State University, Hayward

[email protected]

Hilary J. Holz, Asst ProfessorMath & Computer Science DepartmentCalifornia State University, Hayward

[email protected]

Research Problem

Less exposure to informal education

Less experience in computing skills such as Unix

Lower retention rate of female students in computer science

Less Confidence & Interest in computer science

Percentage of CS/CE degrees Granted to Women

0%

5%

10%

15%

20%

25%

30%

1993/941994/951995/961996/971997/981998/991999/2000

2000/01

Academic Year

Taulbee BS

Taulbee MS

Taulbee Ph.D

[3]

Goals

• Help students – understand Unix concepts– make use of online resources

• Remove some barriers of equity in computer science program

Objectives

• Supporting collaboration through leaving traces

• Supporting adaptation through clustering

• Collect quantitative data– Within a small cohort of 10

students

• Collect qualitative data– Two cohorts of

50 students

Background

Research at Carnegie Mellon University

Percentage of Women Entering CS @ CMU

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

1995/96 1998/99 2000/01

Academic Year

“Organize Workshops to teach UNIX and questions that the women feel are stupid to ask [1]”

Main problems in bringing & retaining of female students

• Experience gap• Confidence doubts• Curriculum and pedagogy• Peer culture

[1]

Feminist Pedagogy

Research in Mathematics Education

• Subjective Knowers & connected Knowers– Acquire knowledge

• Listening to themselves• Accessing others’ experiences

• Female students gain more in collaborative environment

[4]

Exceptional program @ California State University, Hayward

High ratio of female and minority students

Percentage of female enrollment in BS/MS CS program @ CSUH vs Other

schools

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1994 1995 1996 1997 1998 1999 2000 2001

Academic Year

BS @ CUSH

Taulbee BS

MS @ CSUH

Taulbee MS

[2]

Research at California State University, Hayward

Traditional curriculum and classroom design does not meet female and minorities students’ need

One female ?!

Online courses

• Flexibility

• Learning at their own time and pace

No coherent approach to help students move from Windows to Unix

[6]

Approach

Adaptive Collaborative Online Unix Meta-Tutorial

Learn about Online Resources & Communities

Learning Unix Concepts

AdaptationIndividual Learning

Style

Individual Objectives

Individual Preferences

Student Modeling

Usability issues

Clusteringbased on interaction behavior

No questionnaireNo Username & Password

Collaboration - Social Navigation

– Closer to what happens in the traditional classroom

– Learners leave notes for themselves as well

as others

– Encouraging to write notes change the status of learners from passive to active

Footprints on the sand of time are not made by sitting down

Collaborate through following footprints of others

[7]

Online Tutorial

Perl Monk

Learn from online communities

Online Tutorial

• Just in Time Learning– Learning with efficiency– At student’s own pace– Anytime & any location

• Address non-traditional students’ need

Prerequisite for many computer science core courses

Most schools do not offer a traditional course to teach Unix skills

Not possible to teach Unix in formal classes

[6]

Meta-Tutorial

<name> File permission </name><language> English </language> <audience> <beneficiary> beginner </beneficiary> <level> hard </level></audience><relation> <IsDetailsOf>fileMgmnt</IsDetailsOf></relation><comment> useful information </comment>

• Metadata assigned to each section – Using XML– Dublin Core set [10]

– Gateway to Educational Material (GEM) set [14]

– Our own defined set

• Annotated & Categorized links to existing resources– Graphical (e.g. Color) &

text annotation

Research Methodology

Iterative & Participatory Design

Collecting data from learners

Design & Development

Revision

[5]

Initial Hypotheses

• Less use of online resources• Pages with graphics• Less use of communication tools• More reading of comments

• Follow the given order• Less details or depth• Less use of online resources• Less use of communication tools• Spend more time on introductory pages

Female

Beginner

First phase: Data Collection

• Early in the design process– Avoid extra cost &

complicationGoal: Cognitive

model of computer science students’ behavior

• Preliminary survey among 300-350 computer science students

• Task based interview– Tutorial with similar

characteristics

Description of Cohorts

• Interview subsequent cohort of 10 students– Female, Male,

different age group, various level of knowledge

• Preliminary Survey– Freshman

• Introduction to Computer Science and Programming Methods

– Sophomore • Programming Language Concepts,

and Data Structures and Algorithms

– Junior• Web Site Development, and

Introduction to Systems Programming

– Graduate level• Software Engineering of Web Based

System.

Summary

• Human subject involvement– First time in computer science

department @ CSUH • Departmental approval• Process of Institutional Review Board

approval

Summary

• Data collection - First formal phase– Collect finely structures data – Build the cognitive model of computer

science behavior

• Implementation– Build database (postgreSQL)– Implement the system (Perl)– Build metadata set

Sponsors

• California State University Hayward Foundation Inc.

• ACCLAIM– Alameda County Collaborative for Learning and Instruction in Mathematics

• CREW– Collaborative Research Experience for Women

References

8. Dove Chocolate9.http://www.clipart.com10. http://dublincore.org11.http://sourceforge.net

12. http://www.acm.org13.http://www.w3c.org14. http://www.geminfo.org15. http://www.perlmonks.org16. http://unix.org

1. Blum, L. (2001). Women in Computer Science: The Carnegie Mellon Experience2. California State University, Hayward. Institutional Research and Analysis.

3. CRA Taulbee Trends: Women Students & Faculty, (2002).

4. Jacobs, E. J., Becker R. J. Multicultural and Gender Equity. General Yearbook Editor, Boston College.

5. Kelly, E. A., Lesh A. R. (2002). Design Experiments in Mathematics Education. 6. Sawhney, H. and Farzan, R. (2002). Teaching Unix Skills to Undergraduate and

Graduate Students in Computer Science.7. Wexelblat, A. and Maes, P. (1999), Footprints: History-Rich Tools for Information

Foraging