next tell’s teacher training and certification package · competence-based knowledge space theory...
Post on 10-Sep-2020
1 Views
Preview:
TRANSCRIPT
Next-Tell’s Teacher Training and Certification
Package
2
About this teacher training package
This Teacher Training Package provides different learning courses – a training program with
the main purpose to prepare you to work independently with the advanced learning
technologies and applications developed and provided within the project Next-Tell. More
concretely, this training package contains training materials that prepare you to benefit from
ICT use especially in your teaching, your formative assessment practices and learning
experiences.
A special focus is on formative classroom assessment using the Competence-based
Knowledge Space Theory (CbKST) as an ICT-integrated assessment method. CbKST as
theoretical backbone in the context of the Next-Tell project allows for defining competences
of a domain and establishing relations between these competences based on prerequisites
and pedagogically meaningful learning trajectories. As this approach has been implemented
in a variety of tools and web-services elaborated in project’s lifetime, it is of crucial
importance that you get an idea and deeper understanding of this approach and its
application.
Thus, the here presented Teacher Training Package provides you the following learning
courses:
Course 1
Applying CbKST in
the classroom
In this course we will focus on preparing you in applying
the Competence-based Knowledge Space Theory, that
allows you for analyzing, defining and structuring the
subject matter of your teaching lesson(s) by identifying
and structuring underlying competencies. Topics
include: the fundamentals of CbKST, identifying
competencies, structuring learning and knowledge
domains, support tools and guidelines to help you
3
applying the CbKST for your purposes.
Course 1 &
Course 3
Intermediate and
Advanced course
on non-numerical
formative
assessment on the
basis of CbKST
In this course we will focus on giving you an overview
and introduction to the Knowledge Space Theory (KST)
and its competence-based extension, the Competence-
based Knowledge Space Theory.
Course 3 Advanced Course on CbKST is not part of this
book but available as online training course at
Course 4 Application of
myClass in the
classroom
In this course we will focus on giving you an overview
and introduction to the software application MyClass,
an activity tracking tool that supports you in both
capturing and generating data on behavior and sharing
the results with parents, administrators, or students.
Furthermore, we introduce to you the authoring
function of MyClass that supports you in compiling your
own classes, students, and activities.
Each course consists of main modules, which are divided in different units. The units are
designed in such a way that they can be studied independently dependent on user’s interest,
motivation and background. Each module starts with an overview of the content, while
single learning resources provide more in detail explanation.
4
How to work with this training package
Depending on your learning goal, your interest, motivation and (knowledge background),
you have the opportunity to sample a discrete learning units (e.g. courses or single course
modules) from a larger programme (our teacher training package). In that sense, you have
the opportunity to assemble your own course packages based on the collection of modules
provided by the teacher training and certification package.
Typical course packages could be for instance for:
1. Principals/decision makers:
Course 1 Applying CbKST in the classroom:
Module 1 (Theoretical Background)
Course 4: Application of myClass in the classroom
Module 1 (Introduction)
2. Interested teachers:
Course 1 Applying CbKST in the classroom:
Module 1 (Theoretical Background),
Module 2 (Constructing a learning course based on CbKST)
Course 2: Intermediate course on non-numerical formative assessment on the
basis of CbKST
Module 2 (Competence-based Knowledge Space Theory)
Course 4: Application of myClass in the classroom
Module 1 (Introduction),
Module 2 (Working with myClass)
3. Advanced teachers:
Course 1 Applying CbKST in the classroom:
all Modules
Course 2: Intermediate course on non-numerical formative assessment on the
basis of CbKST
all Modules
Course 3: Advanced course on non-numerical formative assessment on the
basis of CbKST
all Modules
Course 4: Application of myClass in the classroom
all Modules
5
Content
Course 1: Applying the CbKST in the classroom ................................................................. 7
Overview & Content of this course ............................................................................................ 8
1 Theoretical Background ..................................................................................................... 9
Competence-based Knowledge Space Theory: Overview and basic assumptions of 1.1
CbKST 10
CbKST-Terminology .................................................................................................. 10 1.2
Classification Systems of Learning Objects .............................................................. 14 1.3
Applying CbKST in the classroom ............................................................................. 17 1.4
2 Constructing a learning course based on the Competence-based Knowledge Space
Theory....................................................................................................................................... 19
Step 1: Identifying Competencies ............................................................................ 20 2.1
Step 2: Competence Assignment to Problems ......................................................... 23 2.2
Step 3: Deriving Prerequisite relations .................................................................... 23 2.3
3 Support tools .................................................................................................................... 27
Concept Maps........................................................................................................... 28 3.1
Flow Diagrams .......................................................................................................... 28 3.2
SkOwl ........................................................................................................................ 28 3.3
Course 2: Intermediate Course on CbKST ......................................................................... 29
Overview & Content of this course .......................................................................................... 30
1 Knowledge Space Theory ................................................................................................. 31
Knowledge Space Theory: Basic Assumption ........................................................... 32 1.1
Prerequisite Relation ................................................................................................ 33 1.2
Knowledge State....................................................................................................... 35 1.3
Knowledge Structure ................................................................................................ 36 1.4
Learning Path ............................................................................................................ 37 1.5
Adaptive Assessment ............................................................................................... 39 1.6
2 Competence-based Knowledge Space Theory ................................................................. 43
Competence-based Knowledge Space Theory: Basic Assumption .......................... 44 2.2
iClass Skill Definition ................................................................................................. 44 2.3
Prerequisite Relation on Skills .................................................................................. 45 2.4
Skill Assignments ...................................................................................................... 46 2.5
Competence Performance Approach ....................................................................... 47 2.6
6
CbKST and Self-Regulated Personalised Learning (SRPL) ......................................... 48 2.7
Course 4: Application of MyClass in the Classroom .......................................................... 51
Overview on Content of this Course ........................................................................................ 52
1 Introduction ...................................................................................................................... 53
2 Working with MyClass ...................................................................................................... 54
Opening myClass ...................................................................................................... 55 2.1
LogIn ......................................................................................................................... 56 2.2
Welcome window ..................................................................................................... 57 2.3
Capturing of activities in one subject with help of MyClass .................................... 59 2.4
Presentation of the activities at the class level ........................................................ 74 2.5
3 Authoring with MyCLass .................................................................................................. 90
Visit ........................................................................................................................... 92 3.2
Entry ......................................................................................................................... 92 3.3
Main page ................................................................................................................. 93 3.4
People Tab – Main Page ........................................................................................... 95 3.5
Classes Tab ............................................................................................................. 100 3.6
Subjects Tab ........................................................................................................... 103 3.7
Skills Tab ................................................................................................................. 106 3.8
Activities Tab .......................................................................................................... 109 3.9
Settings Tab ............................................................................................................ 111 3.10
7
Course 1: Applying the CbKST in
the classroom
8
Overview & Content of this course
In this course we will focus on preparing you in applying the Competence-based Knowledge
Space Theory, that allows you for analyzing, defining and structuring the subject matter of
your teaching lesson(s) by identifying and structuring underlying competencies. Topics
include: the fundamentals of CbKST, identifying competencies, structuring learning and
knowledge domains, support tools and guidelines to help you applying the CbKST for your
purposes.
This course has five chapters, listed below. To begin, click on one of these chapters, and
follow the navigation at the bottom of each page to proceed.
1 Theoretical
Background
In this chapter, we will introduce you to the required
theoretical background, the Competence-based Knowledge
Space Theory. Thus, we will provide information regarding
the essential elements and concepts of this theory,
especially for you using this theory for structuring your
teaching lesson.
2 Constructing a learning
course based on the
Competence-based
Knowledge Space
Theory
In this chapter, we will show you the single steps of how
you can apply the CbKST in order to analyse, define and
structure the subject matter of your teaching lesson.
First, you will learn about two methods that can be used to
identify competencies. You will learn about guidelines and
templates to help and support you in applying these
methods.
Second, we will provide you information regarding
structuring knowledge domains. You will learn about the
basic concepts and procedures.
3 Support tools In this chapter, we will introduce to you several tools that
support the identification of competences, the
establishment of prerequisite relations between them.
Target Audience:
Typical learning paths would be:
Teacher (basic & interested): 1,5
Teacher (advanced): 1,2,3,4,5
Decision Maker/schoolleader: 1, 5
Students/Parents: 5
9
1 Theoretical Background Competence-based Knowledge Space Theory: Overview and basic assumptions of 1.1
CbKST
………………………………………………………………………………………………………….…………………………….10
CbKST-Terminology .................................................................................................. 10 1.2
1.2.1 Competence/Competency/Skill ......................................................................... 10
Definition Skill .............................................................................................................. 11
Definition Competence/ Competency ......................................................................... 11
Skill-Competence-Competency .................................................................................... 12
1.2.2 Knowledge Domain, Knowledge/Competence State & Knowledge/Competence
Structure ........................................................................................................................... 13
1.2.3 Prerequisite Relation .......................................................................................... 13
Classification Systems of Learning Objects .............................................................. 14 1.3
1.3.1 Bloom's Taxonomy ............................................................................................. 14
Cognitive Processing Dimension .................................................................................. 15
Knowledge Dimension .................................................................................................. 16
ACT-R Theory: Overview .............................................................................................. 17
Applying CbKST in the classroom ............................................................................. 17 1.4
In this chapter, we will introduce you to the required theoretical background, the
Competence-based Knowledge Space Theory. Thus, we will provide information regarding
the essential elements and concepts of this theory, especially for you using this theory for
structuring your teaching lesson. We will define and discuss the terminology of CbKST such
as competence/competency/skill or prerequisite relation– what they are and why they
matter. As part of this discussion, we will address different classification systems of learning
objects.
Learning Goals
being able to describe the basic assumptions of the Competence-based
Knowledge Space Theory. You will have a deeper understanding of its basic
concepts and terms used in this theory.
being able to describe the basic idea of Anderson’s taxonomy of learning,
teaching and assessing. You will have a deeper understanding of its basic
concepts.
having a first idea of how to use CbKST for and in your teaching;
10
Competence-based Knowledge Space Theory: Overview and basic 1.1
assumptions of CbKST
Competence-based Knowledge Space Theory (CbKST) provides a set-theoretic framework for
analyzing and modelling domain and learner knowledge.
The basic assumption of this approach is the existence of a set of latent skills representing a
knowledge domain and that provide fine-grained description of learners’ underlying
cognitive abilities. This set of latent skills are not only required to solve certain problems
but can also be referred to learning objects and assessment problems.
CbKST-Terminology 1.2
1.2.1 Competence/Competency/Skill
In the field of e-learning, several different terms are usually used to describe the variable
knowledge or ability, such as competence, competency, or skill. Actually, there is no
consistent terminology regarding the “underlying abilities” which enables a person to solve a
certain problem.
In the context of CbKST, Klaus Korossy (1997) introduced the term elementary competency
to describe latent abilities and knowledge underlying certain performance. This definition
attempts to describe small, atomic entities of knowledge or ability that enable a person to
solve a problem. Kickmeier-Rust (2007) also suggests the term “competence” in terms of
CbKST.
Other authors (e.g., Gediga & Düntsch, 2003; Heller, Steiner, Hockemeyer, & Albert, 2006;
Kickmeier-Rust & Steiner, 2007) used the term skill to describe such atomic cognitive
abilities. More exact, the term skill was introduced by these authors to describe a fine level
of granularity of knowledge or ability replacing the term (elementary) competency.
In the following pages, we will further define these three concepts.
11
First the term skill; a variant similar to above mentioned terminology came from
UNIDO (2002, p. 8), which defines a competency as
“a set of skills, related knowledge and attributes that allow an individual to
perform a task or an activity within a specific function or job”.
Thus, skill means the ability to apply knowledge and use know-how to complete tasks and
solve problems.
Cognitive psychology has mainly concentrated on the learning of skills through training, in
which goal accomplishment is dependent upon the level of declarative and procedural
knowledge required to perform satisfactorily (Ackerman, 1992). Adams (1987) attempted to
establish a working definition in a review of human motor skills research. He proposed three
defining characteristics: (1) skills are a wide behavioral domain in which behaviors are
assumed to be complex, (2) skills are gradually learned through training, and (3) attaining a
goal is dependent upon motor behavior and processes.
A further definition of skill came from Heller, Steiner, Hockemeyer, & Albert (2006), who
argued that a skill is defined by a set of concepts (in the sense of concept maps) and an
action verb (cf. Anderson, Krathwohl, Airasian, Cruikshank, et al., 2001; Bloom, 1956). This
definition consists basically of a declarative knowledge part (the concept) and this part is
linked with a specific verb identifying the level of cognitive processing (according to
Anderson et al., 2001). While the declarative part is quite straight-forward, the cognitive
complexity part must be analyzed more in-depth. As an example for a skill consider “apply
the Pythagorean Theorem” which consists of the concept “Pythagorean Theorem” and the
action verb “apply”.
Anderson (1982) uses the term skill to describe a broad and performance-related construct
of ability, for example computer programming. Such skill might include 500 rules (Anderson,
1996, p. 356). In ACT theory, knowledge is represented by declarative knowledge and
procedural knowledge. The atomic parts of declarative knowledge (in some sense the factual
knowledge) are represented in terms of chunks (cf. Servan-Schreiber, 1991). These chunks
are defined by propositional networks similar to concept maps. Procedural knowledge is
represented in terms of production and production rules. These, in turn, can only apply
when the relevant knowledge is satisfied by available declarative memory.
Second, the terms competence and competency; often, both terms have
been used synonymously. A definition of competence came from Cheetam
and Chivers (2005), who argued that a competence is the
“effective performance within a domain/context at different levels of proficiency”.
Nussbaumer et al. (2007) stated that competences are cognitive constructs that learners are
assumed to possess if related problems have been solved. Competences can be assigned to
learners but also to learning objects.
From a psycho-pedagogical perspective, competence may also be defined as
Definition Skill
Definition Competence/ Competency
12
„die bei Individuen verfügbaren oder durch sie erlernbaren kognitiven Fähigkeiten und
Fertigkeiten, um bestimmte Probleme zu lösen, sowie die damit verbundenen
motivationalen, volitionalen und sozialen Bereitschaften und Fähigkeiten, um die
Problemlösungen in variablen Situationen erfolgreich und verantwortungsvoll nutzen zu
können“
[„the available cognitive abilities and skills of an individual or those which are learnable by an
individual to solve problems as well as the related motivational, volitional, and social
willingness and abilities to use these problem solutions successfully and responsibly in
variable situations”] (Weinert, 2001).
This definition encompasses a wider perspective on competence, referring particularly to an
application of a large set of knowledge and abilities in “real world” problem situations. Thus,
competence can be described as the proven ability to use knowledge and skills in work or
study situations and in professional and personal development.
In order to find a way through the thicket of different definitions (and only a
snapshot of existing approaches is outlined here), well-established English
language dictionaries may help.
Skill Competence/Competency
Ability to use one’s knowledge effectively and
readily in execution or performance, the
dexterity or coordination especially in the
execution of learned physical tasks, or a
learned power of doing something
competently; a developed aptitude or ability
(e.g., language skills).1
The quality or state of being competent
(having requisite or adequate ability or
qualities)1
The proficiency, facility, or dexterity that is
acquired or developed through training or
experience, in art, trade, or technique ,
particularly one requiring use of the hands or
body, or a developed talent or ability (e.g.,
writing skills).2
The state or quality of being adequately or
well qualified; ability, a specific range of a
skill, knowledge, or ability, or the knowledge
that enables one to produce or comprehend
language.2
Relying on these two of the most established English language dictionaries, both terms, skill
and competence, seem to be closely related; the terms competence and competency are
1 Merriam Webster Online (www.m-w.con) 2 The American Heritage Dictionary of English Language (www.bartleby.com/am)
Skill-Competence-Competency
13
used synonymously. However, a distinction is made regarding performance and underlying
ability or knowledge, particularly in the Merriam Webster dictionary.
While skill is related to performance and observable behavior, competence rather refers to
an underlying ability or knowledge, which does not necessarily and directly lead to a certain
performance.
Exactly this distinction of latent competence and observable behavior is key to CbKST; and
the appropriate term of describing a latent and abstract ability or knowledge, which may
lead to a certain performance, apparently is competence.
1.2.2 Knowledge Domain, Knowledge/Competence State & Knowledge/Competence
Structure
A knowledge domain is characterized by a set of problems and the knowledge state of an
individual is identified with the subset of problems he/she is capable of solving or answering
correctly. A competence state as contrasted with knowledge state is defined as the subset of
competences a person has at his/her disposal.
Due to psychological dependencies (e.g. prerequisite relationships) between problems, not
all potential knowledge states exists. The collection of all possible knowledge states induced
by prerequisite relations is called a knowledge structure. A competence structure consists of
a collection of competencies applicable to the occurring prerequisite relations.
1.2.3 Prerequisite Relation
A prerequisite is an item that is required to be possessed before the next associated item is
addressed. In terms of competencies, it provides abilities required to learn the next
competence.
The basic assumption here is, that single competencies are not independent from each other
meaning that there exists (logical, psychological, or curricular) dependencies among them
that are captured by so-called prerequisite relations. The idea behind is that acquiring a
specific competence requires having another competence. To give an example, to
understand the concept of magnetic force requires (necessarily) to know what metals are. In
addition to the very strict assumption of necessary and logical prerequisites, somewhat less
strict relations can be utilized, for example “is generally learned before”. Such relations are
established between all competences of a domain. In CbKST, prerequisite relations are not
exclusively linear hierarchies but are allowing competences being in no relation, meaning
that neither of two competences is the prerequisite for another one. Any prerequisite
relation can be illustrated as a so-called Hasse-Diagram, where relations are depicted by
ascending sequences of line segments. According to the prerequisite relation presented in
Figure 1a for example, a is prerequisite to c, and e, whereas b is prerequisite to c,d, and e.
14
On this basis, CbKST allows a number of possible learning paths, that is, sequences of
acquiring the competences of a domain (Figure 1b as an example).
Figure 1: Prerequisite realtion on a knowledge domain (a) and corresponding knowledge structure (b) with the dashed arrows representing a possible learning path.
Classification Systems of Learning Objects 1.3
1.3.1 Bloom's Taxonomy
Benjamin Bloom (1956) and his colleagues developed a means of classifying and sequencing
into a hierarchy types of learning and learning objectives in the cognitive domain. Since then,
Bloom's Taxonomy has undergone multiple revisions, with one of the more popular revisions
being from Anderson & Krathwohl (2001). Below we present the classic version of Bloom's
Taxonomy, followed by the Revised Bloom's Taxonomy.
Bloom’s Taxonomy3
Bloom’s Taxonomy can be understood as a classification of levels of intellectual behaviour
important in learning. The major idea of the taxonomy is that what educators want students
to know can be arranged in a hierarchy from less to more complex. The levels are
understood to be successive, so that one level must be mastered before the next level can
be reached.
Revised Bloom’s Taxonomy
3 Alford, G., Herbert, P., & Frangenheim, E. (2006). Bloom’s Taxonomy Overview. Innovative Teachers Companion , 176 –
224. ITC Publications.
15
Anderson and Kratwohl (2001) revised Bloom’s taxonomy of learning objectives to derive
their comprehensive framework of Learning, Teaching, and Assessing (see Table 2). This
framework takes into account not only the type of cognitive process in which students
engage (as did Bloom’s taxonomy) but also the type of knowledge being addressed.
Table 1: Revised Bloom’s taxonomy (Anderson & Kratwohl, 2001)
Cognitive Process dimension
Remember Understand Apply Analyse Evaluate Create
Kn
ow
led
ge D
imen
sio
n
Factual
Knowledge
Conceptual
Knowledge
Procedural
Knowledge
Meta-cognitive
Knowledge
The six categories of cognitive processing dimensions are specified in a
hierarchical order (i.e., remember, understand, apply, analyze, evaluate, and
create) and are related to the type of mental activity that the students
underdakes. The six levels can be essentially summarized as follows:
Remember: retrieving relevant knowledge from long-term memory
o Recognizing, identifying, recalling, retrieving,…
Understand: constructing meaning from instructional (oral, written, and/or visual)
messages
o Interpreting, exemplifying, instantiating, classifying, categorizing, subsuming,
inferring, concluding, predicting, comparing, matching, contrasting,…
Apply: carrying out or using a procedure in a given situation
o Analyzing, planning, making analogies, connecting,…
Analyze: breaking material into its constituent parts and determining how the parts
relate to one another and to an overall structure or purpose
o Differentiating, distinguishing, organizing, selecting structuring, attributing,
deconstructing,…
Evaluate: making judgments based on criteria or standards
o Checking, coordinating, monitoring, testing, critiquing, judging,…
Cognitive Processing Dimension
16
Create: putting elements together to form or coherent or functional whole;
reorganizing elements into an original pattern or structure
o Generating, hypothesizing, planning, designing, constructing,…
The second pillar of Anderson et al.’s (2001) taxonomy is the knowledge
dimension. The authors distinguish four types of knowledge related to the
nature of subject matter being learnt (see Figure 2):
factual knowledge: knowledge about facts, terminology, details, and elements,
conceptual knowledge: knowledge about relationships, principles, theories, models,
and structures,
procedural knowledge: knowledge about techniques, methods, and strategies, and
meta-cognitive knowledge: knowledge about one’s own knowledge/cognition,
strategic and tactic knowledge, and self-knowledge.
Figure 2: Knowledge Dimensions
Knowledge Dimension
17
Further reading:
This interactive tool from the Iowa State University provides some cross-disciplinary
examples of what Anderson and Krathwohl's taxonomy means in practice (Iowa State
University, n.d.).
ACT-R is a theory about human cognition works developed by John Anderson
and colleagues (http://act-r.psy.cmu.edu/).
In ACT theory, knowledge is represented by declarative knowledge and
procedural knowledge. The atomic parts of declarative knowledge (in some sense the factual
knowledge) are represented in terms of chunks (cf. Servan-Schreiber, 1991). These chunks
are defined by propositional networks similar to concept maps. Procedural knowledge is
represented in terms of production and production rules. These, in turn, can only apply when
the relevant knowledge is satisfied by available declarative memory.
Applying CbKST in the classroom 1.4
Applying CbKST allows you for analysing, defining and structuring the subject matter of any
teaching lesson(s) by identifying and structuring underlying competencies. In further
consequence, you are able to use CbKST as a framework for building (e-)learning courses.
There are several steps in order to effectively use and apply CbKST in the classroom (see
Figure). First, the knowledge domain and specific topics of your lesson(s) have to be
determined. Next, appropriate learning objects (LO) are needed. One option is to create new
learning objects which is a time consuming and cost intensive task. Thus, another more
efficient alternative is to search for or to reuse existing resources. For each learning object
the respective competencies they convey have to be identified and assigned. These are such
competencies that are required for understanding the learning object as well that are taught
by them.
ACT-R Theory: Overview
18
Figure 3: Basic steps in applying CbKST for your classroom activities
19
2 Constructing a learning course based on the Competence-
based Knowledge Space Theory
2.1 Step 1: Identifying Competencies .............................................................................. 20
2.1.1 Curriculum Analysis ............................................................................................ 20
2.1.2 Task Analysis ....................................................................................................... 22
2.2 Step 2: Competence Assignment to Problems .......................................................... 23
2.3 Step 3: Deriving Prerequisite relations ...................................................................... 23
2.3.1 Curriculum Analysis ............................................................................................ 23
Example ........................................................................................................................ 23
2.3.2 Semantic Analysis ............................................................................................... 24
Example ........................................................................................................................ 25
2.3.3 The set inclusion principle .................................................................................. 25
Example ........................................................................................................................ 25
Step 1: Identifying Competencies ............................................................................ 20 2.1
2.1.1 Curriculum Analysis ............................................................................................ 20
2.1.2 Task Analysis ....................................................................................................... 22
Step 2: Competence Assignment to Problems ......................................................... 23 2.2
Step 3: Deriving Prerequisite relations .................................................................... 23 2.3
2.3.1 Curriculum Analysis ............................................................................................ 23
Example ........................................................................................................................ 23
2.3.2 Semantic Analysis ............................................................................................... 24
Example ........................................................................................................................ 25
2.3.3 The set inclusion principle .................................................................................. 25
Example ........................................................................................................................ 25
In this chapter, we will show you the single steps of how you can apply the CbKST in order to
analyse, define and structure the subject matter of your teaching lesson.
First, you will learn about two methods that can be used to identify competencies. You will
learn about guidelines and templates to help and support you in applying these methods.
Second, we will provide you information regarding structuring knowledge domains. You will
learn about the basic concepts and procedures.
20
Learning Goals
know the process of how to identify competencies and to derive prerequisite
relations using different methods
being able
to identify competencies
to match competencies and problems
to derive prerequisite relations
Step 1: Identifying Competencies 2.1
Competences are the very basis and nature of CbKST and other theories and applications
related to e-learning. Thus, an appropriate identification of competences is crucial for
scientific and practical applications. Because competences are latent constructs, which must
be extracted and specified on the basis of a number of different sources, the identification
process is most often a tricky process requiring a certain amount of expertise regarding the
envisaged domain as well as regarding the desired application and their requirements.
In terms of identification, specification, and application, the granularity of the single
competences has to be considered. The required granularity depends on the Learning
Objects. If Learning Objects are not really detailed, the single competences have not to be
fine-grained either. An appropriate level of granularity is strongly depending on the targeted
application. In a context of life long learning, a rough level of granularity is advisable because
otherwise the number of involved competences is getting hardly comprehensible and
unmanageable. Finally, the level of granularity depends on the possibilities of assessing
competences in a certain application or context. For example, it is meaningless to define a
large number of competences, when the available assessment procedures are not capable of
assessing and differentiating the competences.
To find an appropriate balance between level of granularity and requirements and
restrictions of the targeted application is in the responsibility of the designer / educator. This
task is not trivial and requires expertise and experience.
In the following sections two different sources of competence identification are described in
more detail.
2.1.1 Curriculum Analysis
The first step in defining competences is to specify and circumscribe the envisaged domain
of knowledge. While curricula generally are rather rough descriptions of learning objectives
21
and included subject matter, they are the primary basis to specify a domain of knowledge
(see Table 2 for an example). In addition, curricula facilitate the selection of appropriate
sources for identifying competences. If curricula are not available for specific educational
objectives, a list of well-described learning goals and objectives must be developed.
Table 2: Example curriculum (extract).
US High School Physics1
Goal 6 - Energy: The learner will develop an understanding of energy as the ability
to cause change.
Investigate and analyze energy storage and transfer mechanisms: gravitational
potential energy, elastic potential energy, thermal energy and kinetic energy.
Analyze, evaluate, and apply the principle of conservation of energy.
Analyze, evaluate, and measure the transfer of energy by a force including work
and power.
Objective 3: Analyze, evaluate, and measure the transfer of energy by a force
including work and power.
Design and conduct investigations of mechanical energy and power.
As a first step and based on the envisaged educational objectives, a list of learning goals and
learning objectives must be established. This can be accomplished by using an existing
(probably authorized national) curriculum or subsets of them. On this basis, in a next step
appropriate learning material (e.g., school books, existing electronic learning objects, or
scientific literature; see Table 3 for an example) must be selected and linked to the goals and
objectives of the curriculum.
Table 3: Example for a school book paragraph utilized for identifying competences.
Kinetic and Potential Energy1
Energy is defined as the ability to do work. When the work is actually being done,
we term the energy “kinetic.” When the work is waiting to be done, or when there
22
is the potential for work to be performed, we term the energy “potential.” Kinetic
energy is the energy of motion, potential energy comes from work having been
done on an object which was then stored. For example, a rubber band zinged from
your finger has kinetic energy. While it was stretched, waiting for you to release it,
it had potential energy. The rubber band was stationary, but work had been done
on it to move it to its present position.
Once the domain and the relevant learning materials are specified, the latter can be
analyzed regarding relevant competences comprised within. This process occurs on a
sentence-by-sentence level. The competences - on the finest level of granularity - comprise
the relevant conceptual knowledge and procedures contained in each sentence. Considering
the required level of granularity, these finest entities must/can be combined to specific
competences. This step requires a certain level of expertise in the given domain because in
addition to the desired level of granularity also prerequisite relations between those
elements and logical and semantic properties play a distinct role in establishing
competences.
2.1.2 Task Analysis
Although the analysis of competences involved in certain problem situations (PrS) or tasks is
not in the foreground, a comprehensive and global identification of competences also
requires such analysis. The reason why a task analysis cannot be the first step of competence
identification is that a set of competences - as a formal definition of learning objectives -
ideally builds the basis for designing learning situations (LeS) or PrS. However, even if a well-
defined set of competences is the basis for PrS design, a PrS likely involves competences
beyond the actual learning objective. For example, a PrS dealing with the “straight
propagation of light” may include also competences of “2D modeling” or the knowledge
about occurring objects (e.g., a torch). Task analyses includes following steps:
A listing of all objects involved in a given PrS and their properties. The properties
include, for example, in which way they are presented to the learner, in which way
the can be manipulated by the learner, and to what extent they can be manipulated.
The specification of the initial state(s) of all objects as well as the target state(s),
including properties such as location or alignment.
Based on steps 1 and 2 and also based on the learning objective(s), a listing of
appropriate problem solving steps. This listing includes all steps or manipulations
that are necessary to reach to PrS’s goal. Likely there are several sequences to
accomplish the PrS.
The competences - on the finest level of granularity - comprise the conceptual
knowledge about each object or element and their properties. In addition, the
competences include knowledge about each possible manipulation or problem
23
solving step. Considering the required level of granularity, these finest entities
must/can be combined to specific competences. This step requires a certain level of
expertise in the given domain because in addition to the desired level of granularity
also prerequisite relations between those elements and logical and semantic
properties play a distinct role in establishing competences.
Step 2: Competence Assignment to Problems 2.2
After identifying the respective skills and based on the resulting list, to each learning object
or problem the required skills for understanding them on the one hand, and the skills that
are taught (“new skills to be learnt”) by a learning object on the other hand were assigned.
This can be done by consulting experts.
Step 3: Deriving Prerequisite relations 2.3
In CbKST, the single competences are not independent from each other. That means that
person demonstrating a particular competence might also be competent in the use of
certain other competences. The idea is that acquiring a specific competence requires having
another competence. To give an example, to understand the concept of magnetic force
requires (necessarily) to know what metals are. In addition to the very strict assumption of
necessary and logical prerequisites, somewhat less strict relations can be utilized, for
example “is generally learned before”. Such relations are established between all
competences of a domain. In CbKST, prerequisite relations are not exclusively linear
hierarchies (as for example in Item Response Theory) but are allowing competences being in
no relation, meaning that neither of two competences is the prerequisite for another one.
On this basis, CbKST allows a number of possible learning paths, that is, sequences of
acquiring the competences of a domain.
2.3.1 Curriculum Analysis
As for identifying competences, curricula for a given domain and related textbooks offer a
good starting point for establishing prerequisite relations. These sources provide a rough
sequence of what subject matter is taught when. Prerequisite relations can be established
by assigning each competence of a given set of competences to the sequence specified in
curricula and textbooks. The following example demonstrates such procedure.
Given a set of five competences Q = {adding numbers, subtracting numbers,
multiplying numbers, dividing numbers, and solving simple linear equations}, we
can use the related curriculum to establish a first draft for a prerequisite
Example
24
relation. In this example we rely on the Austrian curriculum for first grade secondary
education (at the age of ten). Table 4 shows an excerpt of the curriculum. In a next step each
of the competences are assigned to the statements of the curriculum (Table 4). Due to the
fact that the curriculum offers a didactically sound sequence of teaching, the assignments
results in a rough prerequisite relation between the competences (shown in Figure 4). The
established relation can be refined with other methods.
Table 4: Curriculum for mathematics (extract) and related competences.
Figure 4: Prerequisite relation resulting from thecompetence assignment of Table 1.
2.3.2 Semantic Analysis
Most often, competences are described in terms of propositions or textual descriptions.
When applying semantic analysis, those descriptions are analysed regarding the involved
concepts (nouns) and procedures (verbs). If the concepts or procedures equal another
competence of a given set, this competence can be considered to be a prerequisite of the
25
current one. In addition, generic terms or subsumable concepts must be considered.
Generally, a generic term is a prerequisite for a (more specific) subsumable concept. Using
this procedure establishes a fine-grained but - most likely - incomplete prerequisite relation
between competences.
Given a set of competences Q = {knowledge that a magnet attracts metals but
not other materials such as wood or plastic; a metal is an element from a well-
defined group of chemical elements, knowledge that iron is a metal; knowledge
that wood is not a metal}, we can analyze each of them on a semantic level. The
first competence “knowledge that a magnet attracts metals but not other materials such as
wood or plastic” includes the concepts {magnet, metal, material, wood, plastic} and the
procedure {attract}. The second competence “a metal is an element from a well-defined
group of chemical elements” defines the concept “metal”. Therefore, the second
competence can be considered as a prerequisite for the first competence. The third
competence “knowledge that iron is a metal” states that “iron” is a subsumable of “metal”.
Therefore, the second competence is also a prerequisite for the third one.
Given a set of competences Q = {knowledge that a magnet attracts metals but not other
materials such as wood or plastic; a metal is an element from a well-defined group of
chemical elements, knowledge that iron is a metal; knowledge that wood is not a metal}, we
can analyze each of them on a semantic level. The first competence “knowledge that a
magnet attracts metals but not other materials such as wood or plastic” includes the
concepts {magnet, metal, material, wood, plastic} and the procedure {attract}. The second
competence “a metal is an element from a well-defined group of chemical elements” defines
the concept “metal”. Therefore, the second competence can be considered as a prerequisite
for the first competence. The third competence “knowledge that iron is a metal” states that
“iron” is a subsumable of “metal”. Therefore, the second competence is also a prerequisite
for the third one.
2.3.3 The set inclusion principle
As mentioned, competences are often defined by a set of propositions and procedures
(particularly when following the working definition of competences introduced in previous
sections). Basically, the set inclusion principle states that when the set of propositions (and
procedures) defining a first competence is a subset of the set of propositions (and
procedures) defining a second one, the first competence can be considered to be a
prerequisite for the second one (for a more detailed description see Steiner & Albert, 2007).
Using this procedure establishes a fine-grained but - most likely - incomplete prerequisite
relation between competences.
Let us assume two competences, “knowledge that the heart pumps blood
through the vessels”, and “knowledge that the blood flows from veins to
arteries over capillaries” (Figure 5). The propositions defining the second
competence are a subset of the propositions defining the first one. Therefore,
Example
Example
26
the second competence is a prerequisite of the first one.
Figure 5: Propositional network for describing a domain.
3 Support tools Concept Maps ........................................................................................................... 28 3.1
Flow Diagrams .......................................................................................................... 28 3.2
SkOwl ........................................................................................................................ 28 3.3
3.1 Concept Maps ............................................................................................................ 28
3.2 Flow Diagrams ........................................................................................................... 28
3.3 SkOwl ......................................................................................................................... 28
There is a variety of software tools that support the identification of competences as well as
the establishment of prerequisite relations between them. In this chapter we will introduce
to you several of these tools.
Learning Goals
know different software tools that support the process of identifying
competencies
having an understanding of concept maps
having an understanding of flow diagrams
knowing the software tool SkOwl
Concept Maps 3.1
Concept maps are a natural way of representing knowledge. Concept maps generally
represent declarative knowledge, that is, knowledge about facts in form of conceptual
information (Anderson, 2000). Concept maps consist of graphical node-link representations
with the nodes representing the concepts and the links (arcs) representing relationships
among those concepts (Novak, 1998). Two concepts of a concept map and the link relating
them constitute a proposition. Therefore, concept map can also be represented in form of
proposition lists. A concept map may describe a knowledge domain at different levels of
granularity. On the one hand, it may provide a very fine-grained representation of a domain
of knowledge, as it is for example necessary for a detailed characterization of learning
content. On the other hand, a less granular concept map, as it may for instance result from
curriculum or content analysis, depicts more general concepts and therefore provides a
representation of the respective knowledge domain on a higher level of abstraction (Steiner
& Albert, 2007).
Particularly when competence definitions are based on propositions, concepts maps are an
ideal tool for identifying the competences in a given domain and even to find prerequisite
relations between them. A freely available software tool for the creation of concept maps is
cmap tools (http://cmap.ihmc.us/).
Flow Diagrams 3.2
Equally to concept maps, flow charts may support the process of identifying competences
and establishing prerequisite relations between them. Particularly the procedural part of
competences and tasks can be formalized and visualized with such software. A freely
available (trial version) tool is, for example FlowBreeze (http://www.rff.com/).
SkOwl 3.3
SkOwl is a software tool offering semi-automatic support of transforming OWL domain
ontologies, concept maps, or proposition files to the format of the ELEKTRA ontology model
(Kickmeier-Rust & Albert, 2007). Moreover, SkOwl supports and easy definition of skills on
the basis of propositions and action verbs and it allows semi-automatically generating
prerequisite relations between skills on the basis of the set inclusion principle, action verbs,
and manual work-ups. As special feature, SkOwl allows graphically manipulating prerequisite
relations. SkOwl is available from the authors.
Course 2: Intermediate Course on
CbKST
Overview & Content of this course
In this course we will focus on giving you an overview and introduction to the Knowledge
Space Theory (KST) and its competence-based extension, the Competence-based Knowledge
Space Theory.
This course is based on an existing online learning course about Competence-based
Knowledge Space Theory that has been developed by TUG in 2007 in the context of the
ELeGI research project and updated in 2008 in the context of the iClass research project. The
learning objects of the original course have been reduces to those learning objects that
explain the basics and most important concepts of this theory. As a result, 23 learning
objects have been chosen from the original course that can be divided into two sections, first
the section on KST, and second the section on CbKST.
To begin, click on one of these chapters, and follow the navigation at the bottom of each
page to proceed.
1 Knowledge Space
Theory
In this chapter, we will introduce you to the required
theoretical background, the Knowledge Space Theory.
Thus, we will provide information regarding the essential
elements and concepts of this theory.
2 Competence-based
Knowledge Space
Theory
In this chapter, we will introduce you to the required
theoretical background, the Competence-based Knowledge
Space Theory. Thus, we will provide information regarding
the essential elements and concepts of this theory.
1 Knowledge Space Theory
1.1 Knowledge Space Theory: Basic Assumption ............................................................ 32
1.1.1 Knowledge Domain ............................................................................................ 32
1.2 Prerequisite Relation ................................................................................................. 33
1.2.1 Graphical Representation of prerequisite relations .......................................... 34
Hasse Diagram .............................................................................................................. 34
Matrix Representation ................................................................................................. 35
1.3 Knowledge State ........................................................................................................ 35
1.4 Knowledge Structure ................................................................................................. 36
1.5 Learning Path ............................................................................................................. 37
1.6 Adaptive Assessment ................................................................................................. 39
1.6.1 Deterministic assessment: ................................................................................. 40
1.6.2 Non-deterministic assessment ........................................................................... 40
1.6.3 Probabilistic assessment .................................................................................... 41
1.6.4 Problem-based skill assessment......................................................................... 41
In this chapter, we will introduce you to the Knowledge Space Theory (KST). Thus, we will
provide information regarding the essential elements and concepts of this theory, especially
for you using this theory for structuring your teaching lesson. We will define and discuss the
basic assumptions of KST and will give some background information on the mostly used
terms of KST.
Learning Goals
being able to describe the basic assumptions of the Knowledge Space Theory.
having a deeper understanding of basic concepts and terms used in this theory.
Knowledge Space Theory: Basic Assumption 1.1
Knowledge Space Theory is a well-elaborated, mathematical psychological framework based
on set-theory for representing the conceptual organisation of a knowledge domain, which is
characterised by a set of problems of the respective domain. Moreover, this theory allows
representing and efficiently assessing the knowledge state of an individual learner. To
structure and represent domain and learner knowledge Knowledge Space Theory uses
prerequisite relationships among knowledge elements.
1.1.1 Knowledge Domain
A knowledge domain in Knowlede Space Theory is characterised by a set Q of problems (or,
more generally, items). These problems may be posed to an individual learner, and typically,
the problems in a knowledge domain Q are assumed to be dichotomous. Thus, the answer to
each of these problems can be judged to be either correct, or incorrect. Since these
problems are used to diagnose the knowledge of a learner in the respective domain, the
problems are also referred to as assessment problems.
Example:
Consider the following example of a knowledge domain. A knowledge domain Q in
arithmetic might be represented by problems a, b, c, d, and e shown below. Thereby,
between problems (or problem types) and problem instances is differentiated.
Prerequisite Relation 1.2
From a psychological point of view it is reasonable to assume dependencies regarding the
solving of the problems that represent a specific knowledge domain. This means that some
problems will be solvable by an individual only if some other problems have already been
mastered by this person. This may be because some prerequisites are required to master a
problem, but may also be due to historical or other circumstances. For example, in a certain
curriculum some concepts may be always taught in a particular order, even though there
may be no logical or pedagogical reason to do so.
In Knowledge Space Theory, to capture such mutual dependencies between problems of a
knowledge domain, the notion of a prerequisite relation was introduced.
Formally, a prerequisite relation is a binary relation on the problem domain Q. A
prerequisite relation is reflexive (each problem is related to itself, thus, each problem is a
prerequisite for mastering this problem) and transitive (if problem a is a prerequisite for
problem b, and problem b is a prerequisite for problem c, then also a is a prerequisite for c).
The prerequisite relation restricts the number of expectable answer patterns (knowledge
states) and forms a quasi-order on the knowledge domain. In this way, the prerequisite
relation gives rise to the knowledge structure, which is the collection of possible knowledge
state corresponding to the prerequisite relation.
Any prerequisite relation can be illustrated by a so-called Hasse diagram, where ascending
line segments represent a prerequisite relation. More precisely, every node of such a graph
is an element of the underlying knowledge domain Q, and every edge (a, b) represents the
prerequisite relation, a b. In Hasse diagrams, the mutual relationships between the
elements of the set (i.e. problems) are depicted in an economical way. This means that
redundant information, which can be inferred from the requirements of a partial order, are
omitted. Recalling the requirement of transitivity, only the edge between a problem and its
immediate predecessor or prerequisite problem, respectively, has to be drawn.
Example:
Assume a knowledge domain Q = {a, b, c, d, e} that is represented by the following five
problems:
a 378 x 605 = ?
b 58.7 * 0.94 = ?
c 1/2 * 5/6 = ?
d What is 30% of 34?
e Gwendolyn is 3/4 as old as Rebecca.
Rebecca is 2/5 as old as Edwin.
Edwin is 20 years old. How old is
Gwendolyn?
Referring to knowledge domain Q, for instance, it would be meaningful to assume that a
learner who is capable of solving problem b (which is 58.7 x 0.94 = ?) would also be able to
solve problem a (which is 378 x 605 = ?). According to the above introduced formal notation
this can be expressed by a b or, meaning that the solving of problem a is a prerequisite to
the mastery of problem b. In other words, the mastery of problem b implies that of problem
a. Keep in mind that the reversal is not valid. The mastery of problem a does not entail the
mastery of problem b.
1.2.1 Graphical Representation of prerequisite relations
The figure shown below illustrates a graphical representation of a prerequisite relation
defined on the problem set presented above.
A relation p q is depicted by an ascending line segment from p to q . For example,
according to the diagram shown below problems a and b are prerequisite problems to
problems d and e, problem c is also a prerequisite to problem e. In other words, the solving
of problem e implies correct answers to problems a, b, and c, the mastery of problem d
implies correct answers to problems a and b. There exist no ascending lines to problems a
and c, thus, from a correct solution to either problem c or problem a no inferences regarding
the solution of further problems can be made.
Hasse Diagram
Figure 1: Prerequisite relation on the knowledge domain Q.
Any prerequisite relation can also be represented in form of a square
matrix, where the number of rows (resp. columns) is equal to the number
of problems in the domain Q. In other words, the problems are
represented by the row indices (resp. the column indices) of the matrix.
a b c d e
a 1 1 0 1 1
b 0 1 0 1 1
c 0 0 1 0 1
d 0 0 0 1 0
e 0 0 0 0 1
Knowledge State 1.3
The knowledge state of an individual is identified with the subset of problems of the
knowledge domain Q that this individual is capable of solving. This means that for a
knowledge domain of n problems there exist no less than 2n potential knowledge states.
Due to the mutual dependencies between the problems, which are captured by a
prerequisite relation, however, not each of the subsets of the set Q is a plausible knowledge
state. If a correct solution to a certain problem can be inferred given another problem is
mastered, then each knowledge state will contain the first problem whenever it contains the
second one (i.e. the first problem may be considered a prerequisite to the second). From this
it becomes obvious, that the mutual dependencies covered by a prerequisite relation reduce
the number of actually feasible knowledge states.
Matrix Representation
Figure 2: Prerequisite relation.
Example:
For the prerequisite relation illustrated in Figure 2 the set {a, b, c}
is a possible knowledge state, while the subset {b, c, d} is not a
possible knowledge state (b is in {b, c, d}, and we have a b, but
a is not in {b, c, d}). The list of knowledge states that can be
deduced from the shown prerequisite relation reads as follows:
{ }, {a}, {c}, {a, c}, {a, b}, {a, b, c}, {a, b, d}, {a, b, c, e}, {a, b, c, d}, Q .
According to a knowledge domain that consists of 5 problems, 32
potential states would exist (25). It can be seen that the
prerequisite relation illustrated in Figure 1, reduces the number
from 32 to only 10 feasible knowledge states.
Knowledge Structure 1.4
The notion of a knowledge state directly yields to the concept of a knowledge structure. A
collection K of knowledge states of a given knowledge domain Q is called a knowledge
structure, whenever it contains the empty set { } and the set Q. The knowledge structure K
consisting of the knowledge states induced by the below prerequisite relation depicted in
Figure 1 is given by the following colelction of knowledge states:
K = { { } , {a}, {c}, {a, c}, {a, b}, {a, b, c}, {a, b, d}, {a, b, c, e}, {a, b, c, d}, Q }.
Set inclusion induces a natural ordering on the collection of knowledge states. An illustration
of the resulting ordering for the knowledge states presented above can be seen in Figure 3.
Figure 3: Knowledge structure induced by the prerequisite relation shown in Figure 2.
For practical applications, on the one hand, a knowledge structure can realise the
pedagogical objective of providing personalised learning paths, and on the other hand, a
knowledge structure can build the basis for an efficient adaptive procedure for knowledge
assessment. It allows for uniquely determining the knowledge state by presenting the
learner with only a subset of the problems of a knowledge domain.
Learning Path 1.5
Given a knowledge structure, there are various possible learning paths for moving from the
naive knowledge state (empty set) to the knowledge state of full mastery (set Q). An
adaptive learning system can harness these different paths for fulfilling the pedagogical
objective to present a learner with learning material (e.g. learning objects) that takes into
account his or her state of knowledge.
Example:
Figure 4: Knowledge structure (the dashed arrows represent one possible learning path).
In Figure 4 one of the possible learning paths is indicated by the upwards-directed arrows
describing the possible steps of a learning process. According to the given knowledge
structure, initially, material related to problem a (or, equivalently, c) should be presented,
followed by material related to problems b or c (a, respectively), and so on. It is not a viable
alternative to start with, for example, learning content related to problem b, because b has
problem a as a prerequisite. Generally, this means that dependent on the current knowledge
state the next content or material is to be selected accordingly.
Similarly as described above, a competence structure may serve for realizing personalized
learning paths on the skill level. Given a competence state, the skills that should be acquired
next can easily be identified, as these skills correspond to the so-called outer fringe of the
competence state. The outer fringe of a competence state is given by the set of skills s such
that adding s forms another competence state. This means, the next step of the learning
path on the skill level will refer to a skill such that additionally acquiring it leads to passing
over to a next, superordinate (neighbour) competence state in the structure. Accordingly,
proceeding in the learning process and going about to acquire the next skill in the learning
path, suitable learning objects are selected to be recommended/presented next that are
characterized by skills (i.e. assigned skill that are taught by the respective learning object)
corresponding to this next step.
Adaptive Assessment 1.6
In general, the main idea of an efficient, adaptive assessment is to start with a problem of
medium difficulty and then to move on to other problems depending on the respective
answer. In case of a correct answer, the next problem will be more difficult than the first
problem. If the learner fails to answer the first question correctly, easier problems will be
selected. This querying ends whenever sufficient information concerning the student’s
knowledge state has been gathered.
Obviously, such an adaptive procedure has the advantage that the assessment is shortened
and more efficient, because it avoids to present the learner with a large number of
problems. A teacher's adaptive assessment of a student's knowledge can be mimicked by
using algorithms for the assessment of knowledge that are based on prerequisite relations
between different problems in terms of Knowledge Space Theory and dichotomous
information on students' mastery of these problems (i.e. correct, incorrect).
In the frame of an adaptive questioning based on Knowledge Space Theory, the selection of
the problem to be asked next during an assessment phase is based on the previous answers
of the learner as well as on the dependenices between the problems that are captured by
the prerequisite relation and the knowledge structure, respectively.
Basically, the assessment procedure is an iterative process which is controlled through three
factors, a questioning rule, an updating rule, and a stopping rule (see Figure 1).
The questioning rule determines how to decide on the next problem to be posed to
the learner. I.e., generally, the next problem type is selected and one instance (one
problem) of the selected problem type is posed to the learner.
The updating rule specifies how to update the system’s knowledge about the learner
based on the system’s previous assessment and the learner’s current response.
Finally, the stopping rule determines whether enough evidence has been gathered to
pin down the learner’s knowledge state. If this is not the case, the next iteration
starts with applying the questioning rule.
Once the knowledge state of a learner has been determined it may serve several purposes.
For example, based on the learner’s current state the learning material to be presented next
can be selected according to the learning paths inherit from the respective knowledge
structure.
Figure 5: General transitions in an assessment procedure.
Generally, in the frame of KST, we distinguish between deterministic, non-deterministic, and
probabilistic assessment procedures.
Example:
Considering the knowledge structure given in Figure 3 for a knowledge domain of five
problems Q = {a, b, c, d, e}, in the beginning of an assessment phase all states of the
structure may correspond to the knowledge state of an individual learner. According to a
deterministic procedure, the assessment starts by selecting a problem that is contained
approximately in half of the states of this structure and by posing this problem to the
learner. Dependent on the learner’s answer, the next problem will be selected. If the learner
is capable of solving problem b, for example, then only the knowledge states containing
problem b are still feasible. If subsequently problem e is solved, states {a, b, c, e} and {a, b, c,
d, e} remain. The learner’s knowledge state is uniquely identified after presenting problem d.
For instance, state {a, b, c, e} results if problem d cannot be solved by this learner. Thus, for a
set of five assessment problems, the presentation of only three problems allows for
identifying the knowledge state of a learner.
1.6.1 Deterministic assessment:
A deterministic assessment procedure is based on the assumption that a learner’s answer to
a test problem is determined by his or her knowledge only. Thus, it is assumed that there are
no careless errors or lucky guesses. The assessment starts by selecting a problem that is
contained in approximately half of the states of the respective knowledge structure and by
posing this problem to the learner. Dependent on the learner’s previously given answers, the
next problem will be selected.
1.6.2 Non-deterministic assessment
In contrast to a deterministic assessment, a non-deterministic assessment takes into account
that a learner may sometimes guess the correct answer or may be careless in answering
certain problems. This means, according to a non-deterministic point of view a learner’s
behaviour is determined by his or her knowledge state plus some noise (e.g. lucky guesses,
careless errors).
When assessing the knowledge state of an individual in the frame of a non-deterministic
procedure, the assessment starts with a deterministic questioning. The identified knowledge
state is then assumed to be nearby the correct state of the learner. In the next step
problems belonging to the neighbourhood of the current state are posed to the learner.
1.6.3 Probabilistic assessment
An adaptive assessment procedure may also be embedded into a probabilistic framework. In
doing this it is possible to account for situations in which a learner is careless in answering a
problem, or guesses the correct answer. Moreover, the fact that different knowledge states
will be observed with different probability within a population can be modelled. The
assessment then starts from the assumption that there is an a-priori likelihood function (e.g.
probability distribution) on the knowledge states that characterises their current plausibility.
This initial likelihood may depend, for example, on the age, or the grade of the learner.
During the assessment process the next question is chosen according to a probabilistic
questioning rule, and the likelihood is updated in correspondence with the given answers
(updating rule). The questioning continues until there is a pronounced peak in the likelihood
function that suggests a unique knowledge state for an individual learner. The transitions
between different phases in a probabilistic assessment procedure are shown in Figure 6:
Figure 6: Transitions of a probabilistic assessment
Example:
If the student solves problem a, the likelihoods of all states that contain problem a increase,
while the likelihoods of all the states that do not contain problem a decrease. If the student
fails in mastering problem a, the likelihoods of all the states not containing item a increase,
while the likelihoods of all the states containing item a decrease. The questioning continues
until a probability peak for one state is found.
1.6.4 Problem-based skill assessment
Problem-based skill assessment proceeds in two steps. First, the knowledge state of a
learner, which refers to the observable behaviour, is adaptively assessed. After identifying a
learner’s knowledge state, the knowledge state can be mapped to the corresponding
competence state using the skill assignments in a second step. This means that, given a
knowledge state, we are looking for the subset of skills that are sufficient for solving the
problems contained in the knowledge state.
2 Competence-based Knowledge Space Theory
2.1 Competence-based Knowledge Space Theory: Basic Assumption ............................ 44
2.2 iClass Skill Definition .................................................................................................. 44
2.3 Prerequisite Relation on Skills ................................................................................... 45
2.4 Skill Assignments ....................................................................................................... 46
2.4.1 Assigning skills to assessment problems ............................................................ 46
2.4.2 Assigning skills to learning objects ..................................................................... 47
2.5 Competence Performance Approach ........................................................................ 47
2.5.1 Competence Structure ....................................................................................... 47
2.6 CbKST and Self-Regulated Personalised Learning (SRPL) .......................................... 48
2.6.1 Supporting self-regulated learning paths by CbKST ........................................... 48
In this chapter, we will introduce you to the Competence-based Knowledge Space Theory
(CbKST). Thus, we will provide information regarding the essential elements and concepts of
this theory, especially for you using this theory for structuring your teaching lesson. We will
define and discuss the basic assumptions of CbKST and will give some background
information on its mostly used terms.
Learning Goals
being able to describe the basic assumptions of the Competence-based
Knowledge Space Theory.
having a deeper understanding of basic concepts and terms used in this theory.
Competence-based Knowledge Space Theory: Basic Assumption 2.2
Original Knowledge Space Theory exclusively focuses on the observable solution behaviour
of learners and does not refer to underlying skills and competencies. Since these issues are
of special interest and importance for practical applications in knowledge transfer and
acquisition in educational settings, the extended framework explicitly refers to learning
objects as well as skills and competencies.
Knowledge Space Theory can be enriched by approaches that do not only model the
observable behaviour (i.e. the solving of the problems of a domain), but also the underlying
latent skills and competencies. The association of the posed problems to the portions of
knowledge required for their solution allows for an assessment of the underlying skills and
competencies. Considerations in this regard are subsumed by the so-called Competence-
based Knowledge Theory (CbKST).
CbKST can consequently provide a basis for realizing personalized learning paths on the skill
level and adaptive assessment of a learner’s competence in technology enhanced learning.
The idea behind
The basic assumption is the existence of a set of skills that are relevant for solving the
problems, and that are taught by learning objects of the respective domain. Note that skills
are meant to provide a fine-grained, low-level description of students' underlying
capabilities with respect to the domain and that the association of skills to the problems of a
domain allows for uncovering a learner’s skills in the frame of an efficient assessment. The
collection of skills a person has available is then called the competence state of this
individual. It is not directly observable but can be inferred on the basis of the knowledge
state.
iClass Skill Definition 2.3
Skills form the basis of the knowledge representation in the frame of CbKST. The basic
assumption of CbKST is the existence of a set of skills that are relevant for solving the
problems, and that are taught by learning objects of the respective domain. Note that skills
are meant to provide a fine-grained, low-level description of students' underlying
capabilities with respect to the domain.
As skills are defined in form of capabilities or latent constructs that underly the observable
behaviour they relate to concepts of a domain on the one hand, and to an activity aspect on
the other hand. Thus, skills can be defined in the tradition of Anderson by distinguishing two
components, a declarative and a procedural one. The declarative part refers to concepts of
the knowledge domain, whereas the procedural refers to actions aiming at applying the
declarative knowledge in a problem solving or learning context. When using a skill, the
declarative (conceptual) and the procedural (action) components are related and tuned into
their application.
In iClass4, therefore skills are characterised by a pair consisting of one or more concepts of a
certain knowledge domain and an action verb characterising some kind of cognitive activity
on the on the other hand. Take as an example the skill ‘apply the Pythagorean Theorem’,
which consists of the concept ‘Pythagorean Theorem’ and the action verb ‘apply’.
The concepts and action verbs for defining a skill may be chosen from provided taxonomies,
e.g. taxonomies of learning activities (e.g. Bloom’s taxonomy) or taxonomies of instructional
concepts in a certain subject. In principle, the concepts represents the declarative part of a
skill, indicating the target to which the action part refers. The action verb will most likely
recur for a range of skills referring to different concepts (e.g. state Pythagorean Theorem,
Euclidean Theorem etc.). Similarly, there will usually be several skills referring to the same
concept but covering different action verbs (e.g. state, explain, apply etc. Pythagorean
Theorem).
Figure 7: Taxonomy of learning activities (Bloom’s taxonomy)
Skills are commonly used for describing and stating learning goals or objectives (in form of a
competence goal), as they refer to what the learner is expected to be able to do as a result
of instruction and thus also allow for easily checking whether a learner has achieved a
particular learning objective.
Prerequisite Relation on Skills 2.4
Similar to a set of problems representing a knowledge domain, also on a set of skills of a
knowledge domain a prerequisite relation may be established, capturing logical,
psychological, or pedagogical dependencies among skills. For example, a certain skill will be
available only if some other skill has already been acquired by a person. In some other case,
4 e.g. Heller, Steiner, Hockemeyer, & Albert, 2006; Anderson et al., 2001
a certain skill possibly is always taught before a certain other skill (even if there is no special
reason to do so).
In CbKST such mutual dependencies between skills are defined through a prerequisite
relation on the skills, which is defined in complete analogy to a prerequisite relation on a set
of problems. This prerequisite relation restricts the number of competence states (subsets of
skills) expected to occur, thus giving rise to the competence structure collecting all
competence states corresponding to the prerequisite relation, including the naïve and the
expert competence state.
As a generalization of the prerequisite relation also a prerequisite function may be
established on the set of skills, taking into account that there may be different ways for
acquiring a certain skills, and correspondingly different possible sets of prerequisite skills for
a certain skill.
Skill Assignments 2.5
The relationship between skills and assessment problems or learning objects, respectively, is
established through skill assignments.
2.5.1 Assigning skills to assessment problems
The so-called skill function associates to each problem a collection of subsets of skills
(competence states) Note, that in case of a prerequisite relation on the skills also the
prerequisite skills are assigned, even if not directly tested by the problem. Each of theses
subsets consists of those skills that are sufficient for solving the problem. Assigning more
than one subset to a problem takes care of the fact that there may be more than one way to
solve it. The skill function corresponds to the assignment of metadata to the problems.
Conversely, the so-called problem function associates to each subset of skills the set of
problems that can be solved in it. When a prerequisite relation on the skills has been
established, the domain of the problem function is restricted to the competence states
corresponding to this relation. The problem function in this way defines the knowledge
structure because the associated subsets of problems are nothing else but the possible
knowledge states (expectable answer patterns). This means, the assignment of skills to
assessment problems induces a knowledge structure on the set of problems, which is
actually given by the subsets of problems in the range of the problem function.
puts constraints on the possible knowledge states that can occur.
Both notions, skill and problem function are equivalent, i.e. given the skill function, the
problem function is uniquely determined, and vice versa.
2.5.2 Assigning skills to learning objects
To each learning object a subset of skills is associated, which refers to the content actually
taught by the learning object. In analogy to skill assignment to assessment problems, this
corresponds to the assignment of metadata to learning objects. The skill assignments to
learning objects are utilized for deciding upon which learning object(s) should be
presented/recommended next, given a certain competence state.
Competence Performance Approach 2.6
Another competence-based extension of Knowledge Space Theory is given by the so-called
competence-performance approach introduced by Korossy (e.g. 1999). This approach takes a
slightly different route for establishing a competence-based knowledge representation by
identifying also prerequisite relationships between the skills, which are called 'elementary
competencies' in Korossy's terminology.
2.6.1 Competence Structure
Thus, in analogy to the knowledge structure (i.e. performance structure according to
Korossy's terminology) on a knowledge domain he introduced the notion of a competence
structure on the set of skills. A competence structure is made up by the collection of possible
competence states, including the naïve competence state (i.e. no skill available) and the
expert competence state (i.e. all skills available). On principle, for a knowledge domain of n
skills there exist 2n potential competence states.
If a prerequisite relation is established on the set of skill representing a domain is
established, capturing dependencies among skills, not all subsets of skills are plausible
competence states. If the availability of a skill can be inferred given another skill is available,
then each competence state will contain the first skill whenever it contains the second one
(i.e. the first skill may be considered a prerequisite to the second). From this it becomes
obvious that the mutual dependencies covered by the prerequisite relation on the skills
reduce the number of competence states that are expected to occur.
A competence structure can be used for realising personalised learning paths. This means,
once the competence state of a learner has been identified (problem-based skill
assessment), skills that should be acquired next can be identified and appropriate learning
objects can be presented or recommended.
These skills (i.e. elementary competencies) result from a thorough analysis of the solution
behaviour that tries to identify single steps in the observed solution paths. Performance and
competence structure are related by two mappings, an interpretation function, and a
representation function, which allow for defining a competence-based performance state
(i.e. knowledge state), which is the subset of exactly those problems that are solvable with
the competencies in a given competence state.
CbKST and Self-Regulated Personalised Learning (SRPL) 2.7
SRPL means that the learning process and its content are adapted to the personal
characteristics and preferences of the learner, by letting learners actively take part and
charge of their learning process. Learners are provided with multiple options and the
freedom to choose among them. This choice, in order to be mindful necessitates the
understanding of the meaning of the provided options, and in order to be mindful requires
to provide at least some options that are relevant (in terms of preferences and personal
parameters) for the learner.
The knowledge representation framework of CbKST is able to support not only automated
customisation through automatically selecting and presenting learning objects and
assessment problems, but is also especially suited for scaffolding self-personalisation and
self-regulation. This can be done by exploiting information on the competence structure and
the current competence (or knowledge) state of the learner.
2.7.1 Supporting self-regulated learning paths by CbKST
When choosing among learning objects or learning paths, providing the learner with the
whole range of options (i.e. all learning objects/paths available in the e-learning system –
even if restricted to a certain subject or topic) to choose from will most probably
overburden the learner.
Consider for example a set of four skills. Without taking into account dependencies among
skills, i.e. structuring the domain in terms of CbKST, any sequence of skills would constitute a
possible learning path (see Figure 8). This means, the skills could be learned in any order and
correspondingly the learner will be provided with learning objects to each skill, which will
most probably result in a large amount of options from which the learner has to choose.
Figure 8: Competence structure and learning paths for a set of four skills without any structure. Two possible learning paths
from the naïve to the expert competence state are marked by dashed and, respectively, dotted arrows.
When structuring the skills of a knowledge domain according to CbKST, i.e. taking into
account prerequisite relationships between skills, the number of learning paths and thus can
be reasonably reduced (see Figure 8). This information can be used in two ways for
scaffolding SRPL. Either, still the whole range of options can be provided to the learner, but
those options corresponding to a reasonable learning path (according to the competence
structure) are recommended (e.g. through annotation). Another possibility is to reduce the
number of options from which the learner can choose to those learning paths that
correspond to the competence structure.
Figure 9: Competence structure and learning paths for a set of four skills when taking into account prerequisite relationships
among skills. The number of learning paths is reduced reasonably (compared to the situation without prerequisite relation).
Two possible learning paths from the naïve to the expert competence state are marked by dashed and, respectively, dotted
arrows.
Furthermore, information on the learner’s current level of knowledge and competence can
be taken into account in order to provide him/her with options that are meaningful for
him/her. Meaningfulness in this context means that options are relevant with respect to the
current competence state. The result of an adaptive assessment, or even information about
the learner’s learning history can be utilized in order to determine what the learner is ready
to learn next and what he/she can do or should review.
Regarding the question what should be learned next, i.e. when proceeding in the learning
process, options can be recommended to the learner that correspond to possible next steps
of learning paths considering to the competence structure. Alternatively, the number of
options can actually be reduced to those corresponding to the competence structure.
When previously learned material is going to be reviewed, e.g. as a preparation for an exam,
learning material corresponding to the most sophisticated skills that have been learned may
be recommended to the learner, or the number of options provided may be reduced
accordingly.
Course 4: Application of MyClass in
the Classroom
Overview on Content of this Course
In this course we will focus on giving you an overview and introduction to the software
application MyClass, an activity tracking tool that supports you in both capturing and
generating data on behavior and sharing the results with parents, administrators, or
students. Furthermore, we introduce to you the authoring function of MyClass that supports
you in compiling your own classes, students, and activities.
The course includes the following main units: i) introduction, ii) working with MyClass in the
classroom, and iii) authoring in MyClass. After completing the whole training course,
teachers will know the main functionalities of MyClass and consequently be able to
efficiently use and apply MyClass in the classroom. Furthermore, they will know how to use
the provided authoring tool. To begin, click on one of these chapters, and follow the
navigation at the bottom of each page to proceed.
1 Introduction In this chapter, we will introduce you to the MyClass tool, a
multiplatform online system, design to be used in particular
with mobile devices that serves as an easy and intuitive
access point to maintain students, classes, and subjects.
More importantly, it allows tracking activities of students
by mouse/finger clicks, and it allows adjusting
competencies and learning goals.
2 Working with MyClass In this chapter, we will show you the single steps of how
you can work with MyClass. Thus, the main functionalities
of the tool are described in more detail.
3 Authoring with
MyCLass
MyClass provides to you an authoring function that enables
you to manage the data stored in MyClass by yourself. The
main functionalities are described in more detail.
1 Introduction
The main goal of the European project NEXT-TELL is to support teachers from all over Europe
in efficiently using modern technologies and media such as virtual worlds in the classroom.
In doing so, one important aspect is the appropriate assessment and evaluation of students.
MyClass is a multiplatform online system, design to be used in particular with mobile devices
that serves as an easy and intuitive access point for teachers to maintain students, classes,
and subjects, more importantly, it allows tracking activities of students by mouse/finger
clicks, and it allows adjusting competencies and learning goals. Furthermore, myClass
supports you in sharing the results of their activity tracking with partents, administrators, or
students. In class and in real time feedback points for behaviour can be awarded by simply
clicking on the tablet/smartphone/laptop. Beside this activity tracking feature, myClass
allows for adjusting competencies and learning goals as well as visualising learning
processes/progress by a range of different visualisation features. Additionally, myClass
allows different roles, such as teachers, students, or administrators.
In the following part (section 2 of this course), the main functionalities of myClass that allow
you for using the tool in the classroom will be described in more detail.
Section 3 of this course will describe the authoring tool of MyClass - a web application which
allows administrators to manage the data of MyClass platform in a simple and user friendly
way .
2 Working with MyClass Opening myClass ....................................................................................................... 55 2.1
LogIn .......................................................................................................................... 56 2.2
Welcome window ...................................................................................................... 57 2.3
Capturing of activities in one subject with help of MyClass...................................... 59 2.4
2.4.1 Creating Notes .................................................................................................... 61
2.4.2 Tracking activities ............................................................................................... 62
2.4.3 Editing learning goals ......................................................................................... 63
Learning process (Lernverlauf) ..................................................................................... 65
Learning radar .............................................................................................................. 68
2.4.4 Events record ...................................................................................................... 70
2.4.5 Combine activities and learning goals with each other ..................................... 73
Presentation of the activities at the class level ......................................................... 74 2.5
2.5.1 The individual report capabilities (features) about students level in MyClass .. 76
Full Report .................................................................................................................... 78
Learning-Radar ............................................................................................................. 79
2.5.2 Visualization of subjects and class level ............................................................. 80
Learning goal achievement in one subject ................................................................... 80
Further visualization options .................................................................................... 82
Visualization of the recorded activities ........................................................................ 89
In this chapter, we will introduce you to the MyClass system and its application in the
classroom. Thus, we will provide information regarding the essential functionalities of this
tools allowing you to use it in your teaching lesson.
Learning Goals
knowing the main functionalities and having a deeper knowledge of MyClass
being able to apply MyClass in the classroom
Opening myClass 2.1
MyClass can be used by visiting the following link:
http://css-kmi.tugraz.at/myClass/login.php
It appears the following entry-level or login page (Figure 1).
LogIn 2.2
In order to work with MyClass you have to log in first where the password was announced by
TUGraz. In case of problems, you can send an email to the responsible person at TUGraz by
simply clicking on the link Need help?
After entering the password in the login box and after clicking the Login button it will
appears the following page:
Welcome window 2.3
The welcome window is divided in the following areas:
Welcome message: here appears the username with which you logged in (in these example:
KPH User).
In this section appears the school year in which MyClass is used (in this example: school year
2012/13 winter semester)
By clicking on the exit button you can exit MyClass and go back to the login page (http://css-
kmi.tugraz.at/myClass/login.php)
The view of teaching subjects on different grade level: here will be presented those subjects
in the form of little boxes, that a teacher teaches in a particular school year. Besides subjects
also overriding learning goals can be displayed as tiles (Little boxes) (e.g. ‚Behaviour and
work attitude‘ (‚Verhalten und Arbeitshaltung‘)in the figure above).
Note
This view is individually adaptable: so every teacher sees only those subjects or learning goals that he/she teaches or are relevant to them.
In the figure above are presented the subjects, that are taught in the 3rd and in the 4th grade.
The tile‚ Sachunterricht‘ (appropriate teaching) – background image can be individually
designed here.
Representation of the classes level. This view is especially for a class teacher who wants to
make an overview of an entire class.
Capturing of activities in one subject with help of MyClass 2.4
In order to track activities in a particular subject, first we have to select a corresponding
subject.
After clicking on the corresponding icon for each subject or learning objective, it opens a
new window, which let us see all students that are attending this course (subjects) and also
other functions that will be described below. In our example is selected the subject
‘Sachunterricht’.
This window is divided into the following areas:
In this area is displayed the selected subject.
MyClass offer four different functions or submenus to track pupil’s activity, to make notes of
pupils, to add events and also to edit learning goals.
Notes,
Activities,
Learning goals
Events.
By simply clicking on the icons, it takes you to the corresponding submenu.
In a list are presented the students in form of avatar. The teacher can choose a pupil there,
by simple clicking on a name or an avatar of a certain pupil.
By clicking on the Home button, this window can be left and takes you back to the
welcome page.
Note
In order to be able to track activities, first the pupil must be selected.
2.4.1 Creating Notes
After a pupil was selected, her/his name will be grayed out and in the center of the screen it
will appear a text box. In this textbox, notes can be made and formatted. After you are done
with notes you can save them by clicking on this symbol:
Note
The taken notes always refer to the selected pupil.
2.4.2 Tracking activities
By first clicking on the pupil’s avatar and then on the activity’s icon, it takes you to the
corresponding submenu, into which you can track different pupil’s activities.
These activities relate to a wide range of behaviors that a pupil may indicate during a class
(e.g. having a great homework, helps others, shows great insights etc.). Each of these
activities or behaviors is backed by a corresponding graph.
Note
Activities or behaviors and the associated graphs can be defined from the teacher himself and therefore are customizable.
If the pupil shows a particular behavior or activity, this can be tracked by simply clicking on
the appropriate graph (icon). You can also delete one counted activity or behavior by clicking
on the red X. Each time you click on the icon, MyClass will count the number of activities, so
in this way the number which stands in the button of the icon, will grow up.
2.4.3 Editing learning goals
By clicking on the learning goals symbol, you get into the sub menu, in which individual
learning goals that can be achieved are presented in a list form.
When you click on the learning goals symbol, you will get into the sub menu where the reaching of competencies, which is controlled by simple slider.
On the right sight of each learning goal is located a slider control, whose control button can
be moved arbitrary on a scale from 0 to 100 (up and down). The current value, at which
slider control is located, appears on the right side in orange color.
For example in our case the value 94 in the figure below means that the pupil has already
reached 94 percent of the learning objective.
By clicking on the arrow symbol next to the learning goal text, opens a note field in
which you can take notes and write comments. It is also possible to add or delete on ore
more files.
By clicking again on the arrow icon the text field can be closed again.
Depending on where we click on “Open All Notes” (“Alle Notizen öffnen”) or on “close all”
(“Alle schließen”), all note fields of each learning goal appears or disappears.
By clicking on the disk symbol the made changes will be saved (such as: adding file,
made notes, changes on the slider control and so on).
In the learning goals menu, it is possible to look in details at the learning
process of a pupil. For this we click on the link “Lernverlauf” (Learning
process) or on the link (“als kurve”)
MyClass visualizes the learning process of a pupil in two different ways:
as a bar graphs (by clicking on the link “Lernverlauf”)
as a curve or line charts (by clicking on the link “als Kurve”).
Learning process (Lernverlauf)
By clicking on the arrow symbol on the right side of the screen, you go back into the
learning goals submenu.
Also here if we click on the arrow symbol we go back into the submenu learning
goals.
The learning goals achievements percentage of all the competencies of the
selected subjects (the percentage value that is shown in slider control) can be
visualized using the so called learning radar.
Learning radar
The learning radar enables the separate representation of teachers and pupils assessment of
each competency (blue for teachers and orange for pupils). This makes possible to see at
one glace if a student and a pupil assesses different to each other.
The learning goals achievements (in percent) of all the competencies of the selected subjects
are presented by a point. The closer is the point on the edge the more the pupil has achieved
the learning goal.
Conversely, this kind of representation allows also identifying possible deficits. Thus, in our
example Martin has still weaknesses in the learning objective 2, learning objective 13 and in
learning objectives 14. But by himself estimates Martin much better.
2.4.4 Events record
MyClass offers the possibility to record events separately, such as exams or tests. We simply
can compare it to an e-portfolio.
By clicking on the events icon you reach the corresponding submenu:
In the submenu events, the teacher now has the opportunity to make the following entries:
Date: is automatically displayed and updated from MyClass but the teacher can also
enter and change it manually.
Events/task: in this field specifies the teacher what that event is about for (such as:
test, exams or group exercise). In this way by start typing on that field, the teacher
will get some auto suggestion of possible MyClass events from where he can choose
one, but it doesn’t mean he has to choose one, he can write another new one.
Note: a free field for possible comments or notes
Assessment: here for example can be entered a grade. It is also possible to enter a
verbal assessment.
File: here the teacher has the ability to upload a file, which is supported in all
formats, in terms of an e-Portfolio.
Skills: When you click on skills (“Kompetenzen”), it will be displayed a list of learning
objectives for the selected subject. There are the same learning objectives as in the
submenu “learning objectives”. The teacher has here the opportunity to change and
to adjust the percentage achieving of each learning objectives by a simple click on the
plus or minus symbol.
By clicking on the disk symbol the made entries and changes will be saved.
By clicking on the show events (“Zeige Ereignisse”) will be displayed a list with all events that
relate to all selected pupils.
By clicking on the link on the right side of the screen, you go back to the
events submenu.
2.4.5 Combine activities and learning goals with each other
In MyClass is possible to link the learning goals with activities or possible behaviors that are
exhibited by pupils.
If for example the pupil Martin shows the behavior to help the others and this activity is
recorded, then it will be increased its value at the corresponding learning goals
“Zusammenleben in der Schule ” (living together in the school) by social understanding and
action.( soziales Verständnis und Handeln)
The connection between activities and learning objectives can be defined by teachers
themselves.
Note
The links between activities and learning objectives are defined and allocated from the teacher himself.
Presentation of the activities at the class level 2.5
With MyClass is possible to get an overview to the activities of the whole class. This is
especially important for a class teacher or for a class board (Klassenvorstand)
On the welcome page, in the lower half of the window can be found the so called
representation at the class level, i.e. the respective class or the respective class name
In our representation are the classes 3a, “Delphinklasse” as well as the class 4b and the
“sonnenklasse”.
By clicking on the appropriate class, it opens the following window, which is divided into the
following areas:
Here appears the class or the class name that is selected.
In this section are listed the pupils who are attending this class. Every single pupil is given an
avatar. The student name appears as well as three reporting functions, from which the
teacher can choose one or more:
Certificate (in PDF- form)
Full Report
Learning-Radar.
Here you can find links to the individual learning subjects and to the related activities. In
addition different display modes such as Word-Cloud, parallel coordinates about pupils and
parallel coordinates about learning goals, can be selected by the teacher.
2.5.1 The individual report capabilities (features) about students level in MyClass
MyClass provides three different types of reports. By clicking on the appropriate icon under
the pupil’s name, you can reach the respective report.
Certificate BY clicking on the first icon below, under the pupil’s name, MyClass will generate a
certificate as a pdf file, in which all learning objectives are ordered by subjects, as well as by
corresponding percentage target achievement.
In the document, the subjects (in the below figure is Math) will be presented. Under this
school subject we will find the list of learning goals (see also Chap.2.4.3 Edit learning goals)
that can be achieved in this subject.
Possible made notes or comments are shown under each learning goals.
On the right side, next to the appropriate learning goal, its achievement is displayed in
percent.
By clicking on the full report icon, under the pupil’s name you get access to a
new page where are listed all subjects with the corresponding learning goals and
associated activities.
To each learning goal is displayed the corresponding learning goals achievement (in percent)
and to each activity is displayed their occurrence frequency. At the end of the learning goals
list is shown the overall achievement about all learning goals across for the concerned
subjects.
Annotations and notes that have been made will be displayed in the corresponding learning
goals.
Files that have been uploaded or allocated to each learning goal are listed and can be shown
by simply clicking on the name of the file.
By clicking on the arrow icon, which can be found on the top right side of the screen,
will take you back to the main page of the class.
Full Report
By clicking on the learning radar icon, which can be found under the pupil’s
name, opens a new window with the learning radar. The learning radar
represents (in percent) the total achievements of all learning goal for each
school subject.
Again by clicking on the arrow symbol you get back to the main page of the class.
Learning-Radar
2.5.2 Visualization of subjects and class level
For every school subject it is possible to represent the learning goal achievement of the class
level. Thus, a comparison between pupils will be possible. On the one hand MyClass can
visualize the learning goals achievements in a specific subject. On the other hand the
activities and the behaviors that the pupils have shown in this subject are graphically
illustrated.
By clicking on the appropriate subject (e.g. behavior and work attitude) opens a new
window. Here are presented in bar charts the achievement of each learning goal for every
pupil (see figure below).
Learning goal achievement in one subject
In the upper left of the window is indicated, which class and which subject is going to be
shown. This information can be found in all coming display options.
Name presentation of the learning goals.
Again by clicking on the arrow symbol you get back to the main page of the class.
Further visualization options By clicking on the link [Word cloud], the entire learning goal achievement of a specific
subject can be presented in form of so called Word cloud.
The font size of the pupils name depends on the overall achievement of the learning goal in
a particular subject.
Blue View: The larger the pupil’s name in the visual the higher the learning goal
achievement was in that subject from concerned pupil (inside brackets in percent).
Red View: The larger the pupil’s name in the visual the less the learning goal
achievement was in that subject from concerned pupil.
In the illustration below Maria has reached 73.33% of all learning goals in the
subject “Verhalten und Arbeitshaltung”. On the other hand Susi has reached
only 41.67% of all learning goals.
By clicking on the link [as parallel coordinates (via students)] the entire learning goal
achievements of a specific subject about each student can be illustrated as a parallel
coordinates.
This kind of illustration allows the teacher to see at a glance the results of each individual
student and also to compare them to each other.
Each learning goal achievement corresponds to one dot in the illustration. All pupils’
achieved learning goals are connected to each other by a line. This gives the learning goal
profile of a student.
In the table below the illustration only one pupil can be marked and hence are highlighted in
the visual representation.
By clicking on the link [as parallel coordinates (via learning objectives)] the entire learning
goal achievements of a specific subject about each learning goal can be illustrated as a
parallel coordinates.
In this kind of display it is possible to give the teacher an overview of how the individual
learning goals have been achieved.
Now if a specific learning goal is selected in the table located below the visual representation
then the percentage of learning goals achievements about this learning goal are going to be
highlighted in the display.
By clicking on the link [as matrix] the entire learning goal achievement of a specific subject
for each student can be presented in the form of a matrix.
This type of presentation allows the teacher to see at a glance which learning goal from
which student is reached or not. The achievement of a learning goal (from a certain reached
percentage) is indicated by a green tick.
By clicking on the link [as rotated matrix] will get the teacher the same matrix, where now in
the column are listed the various students and in the rows are listed the various learning
goals of the appropriate subject.
Also in this display, the green tick shows which student has achieved which learning goal
about a certain subject.
By clicking on the arrow icon, on the top right side of the screen of each display
mode, will take you back to the main page of the class.
By clicking on the link activities next to the appropriate subject (e.g.
Behavior and work attitude, se the figure below) opens a new
window.
Here are now presented the frequencies of all activities only in bar charts, without
considering each student.
Visualization of the recorded activities
3 Authoring with MyCLass Visit ........................................................................................................................... 92 3.1
Entry ......................................................................................................................... 92 3.2
Main page ................................................................................................................. 93 3.3
People Tab – Main Page ........................................................................................... 95 3.4
3.4.1 Adding New Person ............................................................................................ 95
3.4.2 Editing Person ..................................................................................................... 99
3.4.3 Deleting person ................................................................................................ 100
Classes Tab ............................................................................................................. 100 3.5
3.5.1 Adding New Class ............................................................................................. 101
3.5.2 Editing Classes .................................................................................................. 102
3.5.3 Deleting Classes ................................................................................................ 103
Subjects Tab ........................................................................................................... 103 3.6
3.6.1 Adding New Subject ......................................................................................... 105
3.6.2 Editing and Deleting Subjects ......................................................................... 106
Skills Tab ................................................................................................................. 106 3.7
3.7.1 Adding New Skill ............................................................................................... 107
3.7.2 Editing Skills ...................................................................................................... 108
3.7.3 Deleting Skills ................................................................................................... 108
Activities Tab .......................................................................................................... 109 3.8
3.8.1 Adding New Activity ......................................................................................... 110
3.8.2 Editing Activities ............................................................................................... 110
3.8.3 Deleting Activities ............................................................................................. 111
Settings Tab ............................................................................................................ 111 3.9
3.9.1 Adding New Setting .......................................................................................... 111
3.9.2 Editing Settings ................................................................................................. 112
3.9.3 Deleting Settings .............................................................................................. 112
In this chapter, we will introduce you to the MyClass authoring system. We will provide
information regarding the essential functionalities of this tools allowing you to use it in your
teaching lesson.
Learning Goals
knowing the main functionalities and having a deeper knowledge of the
authoring system of MyClass
being able to apply the MyClass-authoring system
Visit 3.2
The authoring Tool of MyClass can be used by visiting the following link:
http://css-kmi.tugraz.at/myClass/mc/client/
After entering the link, you will reach an entry-level or login page (see figure1).
Figure 1: Login-page
Entry 3.3
In order to process and insert new data, such as new sudents, classes, activities subjects,
skills and settings, you need to log in first as an administrator of the school.
Finally you have to click on the ‘Log in’ button in order to get the main page as is show in the
figure below.
Figure 2: Main page
Main page 3.4
The main page is divided into the following areas. See Fig 3.
Figure 3: Divided main page
On this taskbar is a distinction between five different categorise, where each of them will be
discussed later in detail.
By clicking on the logout button, you can leave the main page and come back to the login
page (http://css-kmi.tugraz.at/myClass/mc/client/).
Here you can choose how many records would you like to see on the page.
Through this field, certain data can be searched.
Here data can be sorted ascending and descending by several properties, by simply clicking
the sort elements in the column headers.
By clicking on the button ‘Details’ you get more detailed informaation for a particular
person, as is shown in the following figure.
Abbildung 4: Details
Here you can add, edit or even delete rows. Each of this options will be explained in detail
later.
In the lower right area, the pages can be selected.
People Tab – Main Page 3.5
This page contain all registered persons of the school and ther associated information such
as: icon, username, name etc.
3.5.1 Adding New Person
In order to add a new person, you have to clikc first on the add button so that a new window appear with all necessary data that has to be inserted. See figure below
Figure 5: Adding new person
In this field has to be inserted the basic information such as: username, name, surname and so on.
In order to insert an icon (avatar) to the person, first you have to click on this symbol
which will bring a new form where standards available icons can be chosen. See figure 6
Figure 6: Avatar selection of the person
After selecting the icon, this icon appears next to the default icon folder, as you can see it in
the figure 7
Figure 7
Here is the possibility to uplod a photo by their own choice.
In this field the user can set the role of the new person, which can be teacher, student or
administrator . See Figure 8.
Figure 7: Role selection
Here are shown the groups. With groups is meant the school level or different group names
that exist in my class, where each group has various subjects. These subjects can be selected
by the checkbox list as it is show in th figure 9.
There is no need to specify classess and subjects if we want to add a new student. This is
mandatory only wenn we add a new teacher, because only the teacher has various subjects
and classes, where every subject and class has various students that can be specified on the
main menu tabs, such as classes and subjects.
Figure 8: Group selection
After the subjects selection, the selected subjects can be sorted in arbitrary order, via drag
and drop. This is achieved by clicking the button , wherby a new window opens as in Fig.10.
Figure 9: Subjects ordering
Here can be selected the teacher’s class through a checkboxlist.(Figure.11).
Figure 10. Class selection
For each checkboxlist it is possible to serch a certain records.
For adding a further group, there is a button which is located in lower task
bar. The removal of the group can be done by simple clicking on the x-symbol , which is located next to the group name.
In order to save all entered data on this window you have to click on the save button respectively the user can cancel them by clicking on the cancel button .
3.5.2 Editing Person
The editing can be performed in two different methods. In the first method the data can be
modified direct by double click on a particular field and then at the end of editing just press
enter. See figure.12
Figure 11: Editing person – First method
In order to edit data by the second method, first you have to select any row that you want to
change and after that you have to click on the edit button. It appears a new window where
you can edit the data same as in “Add a person” window (Fig.13)
1
1
Figure 12: Editing person – second method
3.5.3 Deleting person
Furthermore there is as usual a delete button where selected row can be deleted.
Classes Tab 3.6
Similar to the people tab, here you have the same functions such as: hanging the page
number, searching data, processing data, setting the number of entries and so on. The same
functionality is provided in the other tabs as well.
Figure: 13 Class tab
3.6.1 Adding New Class
By clicking on the add button it opens a new window named “Add a Class”, where you
can add necessary data such as: name of the class, students that going to attend this class
and also the icon of the class. See fig.15
Figure 14: Adding class
In order to insert an icon to the class, first you have to click on this symbol which will
bring a new form where standards available icons can be chosen. See Figure 16.
Figure 15: Icon selection of the class
3.6.2 Editing Classes
In order to edit the classes first you have to select any row you want to change and then click
on the edit button which will bring you a new form named “Edit Class” where you can edit
the records. See Fig.17.
Also in the classes tab, works the double click editing of a particular data, where the changes
can be saved either by simple pressing enter or losing the focus from the input element.
Figure 16: Editing class
As usually, there is always an option to save record or to cancel it by clicking on the button
or .
3.6.3 Deleting Classes
There is also the option to delete data. First you have to select any rows you want to delete
and then you just click on the delete button .
Subjects Tab 3.7
In this tab you can see the necessary and sufficient information about subjects, such as: icon
and name of the subject, class and the school level in which a certain subject is going to be
taught and also the students that are attending those subjects. The students, skills and
activities related to the subject can be displayed by clicking on , which can be found on
each row at the detail column. See figures 18 and 19.
Figure 17: Subjects tab
Figure 18: Details of subjects
3.7.1 Adding New Subject
In order to add a new subject, as before you have to click first on the add button . After
clicking the button the following window appears.
Figure 19: Adding subject
After the activities selection, the selected sctivities can be sorted in arbitrary order, via drag
and drop. This is achieved by clicking the button , wherby a new window opens as in following figure.
3.7.2 Editing and Deleting Subjects
As already mentioned in the previous points, the editing and deleting of data, works in the
same way as we have explained before. We can edit subject in 2 methods, by double clicking
on a particular row and also with help of edit button.
Abbildung 20
Skills Tab 3.8
In this tab are listed the skills, that students have in a certain school level, semester and
subjects, as it is shown in the figure below.
Figure 21: Skills Tab
3.8.1 Adding New Skill
In order to add a new skill, you have to click first on the add button. After clicking the button
it appears a new form named “Add a Skill” in which the required data can be entered . See
figure 23.
Figure 22: Adding new skill
3.8.2 Editing Skills
The processing of skills runs here only with doubleclick.
Abbildung 23
3.8.3 Deleting Skills
Hre it is also possible to delete rows by clicking on the delete button .
Activities Tab 3.9
In MyCalss it is possible to see the activities of the whole class in a single view. With activity
it is meant the behaviours of the pupils. Here it will be shown Icons, names, skills, and
classes.
Figure 24: Activities Tab
3.9.1 Adding New Activity
By clicking Add Button a new window will open, on which the necessary information for
adding an activity can be typed in. The functionality (editing and inserting) goes as
mentioned earlier in the previous cases.
Figure 26: Activities tab
3.9.2 Editing Activities
Figure 27: Editing Activities
3.9.3 Deleting Activities
By clicking on the delete button you can delete the record you want to delete, but
you have to select that row first.
Settings Tab 3.10
Abbildung 28
3.10.1 Adding New Setting
Figure 29: Adding new setting
3.10.2 Editing Settings
Also here the editing of settings runs only with a double click.
3.10.3 Deleting Settings
There is as usual a delete button where you can delete the selected data.
top related