A Learning System Based on Learner Profile

Smain Nasr-Eddine Bouzenada

, Olivier Boissier

, Philippe Beaune

and Nacer Eddine Zarour

LIRE Laboratory, GLIA Team, University Constantine 2, Constantine, Algeria

LST Laboratory, ISCOD Team, Ecole Nationale Supérieure des Mines, Saint-Etienne, France

Keywords: e-Learning, Learning Style, Learning Object, Learner Profile, SCORM.

Abstract: The main purpose of e-learning systems is to provide learning materials through Internet to let learners

upgrade their knowledge. To be more efficient, these systems must be able to present their learning

materials based on learners’ acquired knowledge as well as their learning capabilities (learning styles).

Therefore, their development should be based on pedagogical models that make them able to adapt their

learning materials on the bases of learners’ competences (acquired knowledge and learning capabilities).

This paper proposes a model and architecture of a learning system able to support pedagogical concepts

such as learning styles and pre-requisite competences to adapt learning materials to learners based on their

profiles.

1 INTRODUCTION

To improve their knowledge, many people use

existing e-learning systems such as Moodle

(Moodle). Unfortunately, these platforms don’t offer

learners’ centred courses; therefore, most of the

time, learners don’t find a suitable ways of learning

(learning style). It is noticed also that, the current

platforms don’t give much importance to the

pedagogical side of the learning process; this can be

seen through the used metadata model descriptor

such as SCORM (ADL, 2009). However, many

experimental research (Kolb D., 1984), (Chartier D.,

2003) have noted that taking into consideration the

pedagogical side of the learning process leads to

better results. Furthermore, these researches led by

these psychologists (Kolb D., 1984) (Chartier D.,

2003) explain that school failure is mainly due to the

lack of consideration of learning’s styles which

differs from one individual to another. Daniel

Chartier (Chartier D., 2003) has also noticed that

different learners have different ways of learning

(learning style). Their success or their failure is thus

related not only to the efficiency level, but also, to

the ways they perceive, store and restore the

information, how they build their knowledge bases.

Individual human don’t have the same competencies

for acquiring knowledge.

Hence, the pedagogy sides of learning process

must be introduced in learning systems to improve

learners’ results. This may be done by supplying

learning systems with some reasoning capabilities to

enable them to use the learner’s learning style to

adapt the learning process. Therefore, the

description metadata model of learning object must

be supplied with items that let Authors (Expert) to

introduce pedagogical items within courses’

descriptors, such as learning styles, pre-requisites

courses and so on. These items can then be used by

learning systems to generate adapted courses based

on captured learners’ profiles.

Being the most used learning system, we

consider that SCORM LOM (IEEE, 2001) is the

most appropriate learning object metadata descriptor

to be extended to describe pedagogical items and

particularly learning styles. This standard emerged

among many others to allow reusability of

educational objects and interoperability between

developed learning systems. It happens that, these

characteristics (re-usability and interoperability) are

not enough to support learners’ pedagogical profile

such as learning styles. This limitation has been

discussed in many research papers since the

apparition of SCORM in 2000 with SCORM V1.0,

modified in 2001 to SCORM V1.2 (ADL, 2001),

then in 2004 to SCORM 2004 3rd edition V1.0

(ADL, 2006) and finally in 2009 to SCORM 2004

4th edition V1.1 (ADL, 2009). Referring to (ADL,

2009), SCORM LOM can be extended whenever the

core set of metadata elements defined by LOM is not

adequate enough to describe SCORM Content

Model Components. SCORM allows two types of

205

Bouzenada S., Boissier O., Beaune P. and Zarour N..

A Learning System Based on Learner Proﬁle.

DOI: 10.5220/0004791602050212

In Proceedings of the 6th International Conference on Computer Supported Education (CSEDU-2014), pages 205-212

ISBN: 978-989-758-020-8

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

extensions’ mechanism within the LOM which are:

 XML element extensions: it is permitted to add

additional elements to metadata instances;

 Vocabulary extensions: list of vocabulary value

proposed by the IEEE of the LOM.

Mason R.T. and Ellis T.J. (Mason R.T. and Ellis

T.J., 2009) expose an approach to extend SCORM

LOM with additional metadata to support adaptive

learning. Baldoni M. & al. (Baldoni M. & al., 2004)

propose to use ontology to add knowledge level to

SCORM LOM. Milosevic D. and Brkovic M.

propose as well to use ontology to expend SCOs

Metadata in terms of pre-requisites (Milosevic D.

and Brkovic M. ,2007).

Therefore, our objectif is to take benefit of this

feature to design an adaptive learning system based

on learning style. That means that a course can be

planned differently according to learners’ learning

style. This planification will be use the different

versions of the same course that have been prepared

by experts for each leaning style.

This paper presents the concept of learning styles

as proposed by psychologists and how it can help

learners to get better results. This work reviews and

presents a solution to enable SCORM LOM

suporting both conceptes learning styles and pre-

requisites. An architecture of such learning systems

is then presented which adapts learning materials to

learners based on learners’ profile.

This paper is structured as follows. We present

first the concept of learning style in section two and

the one of learning object in section three. In section

four we focus on SCORM on which we base our

proposal presented in section five. Before

concluding we present in section six the architecture

of our system.

2 LEARNING STYLE

Many studies focus on the study of behavior of a

human faced to a training session. In his book, the

psychologist David A.Kolb (Kolb D., 1984) states

that any person, who is in a learning situation to get

a new concept, must go through a learning cycle

consisting of four ordered phases. From a concrete

experience phase of the target world, the person will

be engaged in reflective observation phase on that

experience, which will lead to an abstract

conceptualization generating new hypotheses to be

tested in a phase of active experimentation, feeding a

new concrete experience that loops the cycle as

shown in figure 1.

Experimentatio

n

(

Concrete

)



PutinPractice

(

Active

)

Reflexion

(

lective

)



Reasoning

(

Abstrac

)



Figure 1: Kolb’s Cycle.

Kolb (Kolb D., 1984) also noticed that each

learner is characterized by the preferences he/she

gives to one of these four phases of the learning

cycle. On the basis of this learning cycle, Kolb

positions the learner on two orthogonal axes:

Concrete/Abstract and Active/Reflective (see Figure

1). From these two dimensions, Kolb propose four

types of learning styles:

 The Divergent (Concrete/Reflective), is

characterized by his capacity of imagination and

his “emotional intelligence”;

 The Convergent (Abstract/ Active), who likes to

apply the ideas;

 The Accommodator (Concrete/Active), who

prefers facts to theory and action to meditation;

 The Assimilator (Abstract/Reflective), who is

interested in the concepts and theories.

Based on this theory, Professor Jean There

(There J., 1998) established a standard of these

learning styles called ISALEM-97 (L’Inventaire des

Styles d’Apprentissage du Laboratoire

d’Enseignement Multimédia).

The integration of learning styles in the training

process seems to be very beneficial for learners, but

some questions need to anwsered before apply it.

First, how can learners be classified in their

appropriate learning style? Secondly, how can we

manage to present the same content, with the same

objective, to different learners of different learning

styles?

A first solution to these questions is to proceed

as Kolb’s experience propose: teach then first and

then classify then after each assessment. In this case,

the preparation of the content of the assessment must

also take into account the classification in order to

interpret the results of learners. Based on the results,

a categorization of learners is performed which

allows the teacher to prepare different approaches of

presentation of the same content (same objective) to

the various obtained classes. This approach is an

ongoing and a long term work which will also

situate the learner and eventually upgrade the learner

to develop all his faculties of knowledge acquisition.

A second solution consists in passing a test to

learners so that they can be classified as proposed by

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

206

ISALEM (Isalem-97). This test will allow the

teacher to categorize these learners and then to

prepare the presentations required for the subject to

be taught. The major drawback of this approach is

that the learner profile is fixed in advance, which

does not give a chance for the learner to develop his

abilities to acquire knowledge.

In his book, David Kolb (Kolb D., 1984) noted

that the teacher has also preferences of learning style

which influence him on preparing a learning content.

Preaparing the same content in differente versions

according to differente styles is thus a difficult task.

It requires differente teacher with differente learning

style preferences.

3 LEARNING OBJECT

The learning object is a current tendency that plays a

very important role in the development of learning

systems. Its goal is to produce usable and reusable

digital courses in varieties of learning context

situation (K.Verbert, 2004). Production of a course

by an Author becomes just an assembling of existing

learning objects and/or eventually a production of

other learning objects that can be themselves

reusable. To generalize this methodology of course

design based on learning objects shared on the Web,

standardization happens to be necessary. Many

studies have been conducted in this context to

describe precisely the features and services to ensure

sharing and reuse of these objects (Forte E., & all,

1997) (Downes S., 2000) (Koper R., 2002).

Two proposals of standards for describing

learning objects have emerged in recent years. The

central objective concerns the indexing of learning

objects for their reuse on different learning systems.

The most important models and more standardized

ones are:

 LOM (Learning Object Metadata), describes the

object from an economic point of view

(profitability, rationality and reuse) (LOM);

 SCORM (Sharable Content Object Reference

Metadata), deals with object from a technical

point of view (operating, control) (SCORM);

 IMS-LD (IMS Learning Design), deals with

object from a pedagogical point of view (design,

teaching tools, scenarios) (IMS);

Among these models, the most popular and

largely used one is SCORM leading to a large

variety of learning objects. This is what justifies our

choice of SCORM as the underlying model of the

solution that we propose. In the next part of this

paper, SCORM is described and analyzed to see

how it can be used to adapt learning resources to

learner based mainly on his learning style and his

acquired knowledge.

4 PRESENTATION OF SCORM

As described in ADL’s work (ADL, 2009), SCORM

allows the exploitation of learning objects on the

Internet. Its main objective is to propose a formalism

and a mechanism to describe and publish learning

objects and control their uses.

SCORM proposes a learning object definition

and exploitation process, composed of Content

aggregation, Metadata annotation and Content

packing.

4.1 Content Aggregation

The Content aggregation is based on the content

Model (ADL, 2009) which describes the SCORM

components used to build a learning experience from

reusable learning resources. At the same time, the

Content Model defines how these reusable learning

resources are aggregated to compose units of

instruction. A Content Model in SCORM consists in

Assets, Sharable Content Object (SCO) and Content

Aggregations.

4.1.1 Assets

An Asset (ADL, 2009) is an electronic

representation of media, text, images, sounds, web

pages, assessment objects, or other pieces of data

that can be delivered to a web client. To be reused

and reached within online repositories, Assets can be

described with Asset Metadata.

4.1.2 Sharable Content Object (SCO)

A SCO in SCORM (ADL, 2009) is a collection of

one or more Assets that include a specific

launchable asset that uses the SCORM Run-Time

Environment to communicate with Learning

Management Systems (LMS). SCO represents the

lowest level of granularity of learning resources that

can be tracked by an LMS using the SCROM Run-

Time Environment. SCO can be described with SCO

Metadata.

4.1.3 Content Aggregations

A Content Aggregation (ADL, 2009) is an organized

structure of content, which can be used to organize

ALearningSystemBasedonLearnerProfile

207

learning resources on a coherent unit of learning and

to schedule learning resources, which are going to be

presented to learners. Once defined, a Content

Aggregation can be used and reused by LMSs, that’s

why they are described by metadata.

4.2 Metadata Annotation

Metadata in SCORM (ADL, 2009), based on the

IEEE LTSC Learning Object Metadata (IEEE,

2001); describe different levels of the Content

Model of learning units, such as Assets, SCO and

Content Aggregation. This description ensures the

research for these resources within and across

systems to further facilitate sharing and reuse. As

described in IMS Learning Resource Meta-data

XML Binding Specification (IMS-LR), SCORM

Metadata is composed by nine (9) categories of

elements: general, lifecycle,

Meta-metadata, Technical,

Education, Rights, Relation and Annotation, where each

category

regroupeds elements referring to it.

4.3 Content Packing

A content packing in SCORM (ADL, 2009) defines

the structure and the behaviour of a collection of

learning resources. Its purpose is to provide a

standardized way to exchange digital resources

between different learning systems or tools. The

structure of a content packing is as shown in figure2.



eta

ata

zat

on

esources

(



est

(

)



Phy



Fil

es

Package

Interchang

eFile

Manifest

File

Figure 2: Typical SCORM Content Packing.

5 ADAPTING CONTENTS IN

SCORM

After this overview and analysis, we present our

proposal to enable SCORM to support contents

based first, on learners’ knowledge and second, on

learner’s learning style preferences.

5.1 Supporting Learner’s Knowledge

In order to support learner’s knowledge, learning

system must maintain a knowledge profile for each

learner, in which all acquired resources are hold.

This information can be extracted from the

“General” category of SCORM Metadata (ADL,

2009) which are: General.Identifier, General.Title,

General.Description and General.Keyword.

Once maintained update, the learning system can

use this knowledge profile to evaluate the learner’s

capabilities in terms of acquired Knowledge and pre-

requisite knowledge.

5.1.1 Knowledge Already Acquired

Once a resource present in the schedule is acquired

the adaptation process suppresses it from that

schedule. This can be seen in the following scenario.

Let us take for example two lessons with the

organization as defined in figures 3 and 4 where S1,

S2, S3, S4, S5, S6 are SCOs and A1, A2, A3, A4,

A5 are Assets.

Lesson 1

A1

A2

A3

Figure 3: Learning Resource1.

Lesson2

A3

A4

A5

A6

Figure 4: Learning Resource2.

Let’s note that Asset A3 is both used by SCO S3 and

SCO S4.

Let L1 and L2 be two learners. L1 wants to learn

Lesson1 and then Lesson2, whereas L2 wants to

learn only Lesson2.

As they are new in the learning system, their

knowledge profile are empty.

Once learner L1 starts the learning process, the

adapter schedules the Lesson1 learning resources as

shown in figure 3. At the end of this learning

process, the L1’s knowledge profile becomes {A1,

A2, A3}. As the resoure A3 is now acquired, the

adapter schedules the Lesson2 learning resources as

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

208

shown in figure 5, deleting resource A3 from

Lesson2.

Lesson2

S4

S5

S6



A5

A6

Figure 5: Organization of Learning Resource 2 adapted to

learner L1.

At the end of the learning process of the

Lesson2, L1’s knowledge profile is {A1, A2, A3,

A4, A5, A6}.

In the case of L2, the adapter schedules for the

same lesson (Lesson2) the learning resources as

shown in figure 4. At the end of Lesson2 learning

process L2’s knowledge profile is {A3, A4, A5,

A6}.

This scenario confirms that it is possible to build

a learner knowledge profile from the “General”

category of SCORM.

5.1.2 Pre-requisite Knowledge

In the adaptation of learning resources to learner, the

other most important pedagogical situation is to take

into account, the pre-requisite resources when

scheduling lessons. Let us illustrate this situation by

the following example. Suppose that the knowledge

within the learning resource S1 of Lesson1 is

necessary to understand Lesson2, i.e. S1 is pre-

requisite to Lesson2. Let us see now how the adapter

process should schedule Lesson2 for learner L2.

Referring to learner’s knowledge profile and the pre-

requisite resources of a specific lesson, the adapter

can verify if learner is capable to learn this lesson or

not. At this moment, the adapter will schedule

Lesson2 to learner L2 as shown in figure 6.

At the end of the learning process L2’s

knowledge profile becomes {A1, A3, A4, A5, A6}.

To enable the scheduling of this type of situation,

the authors must be given the possibility to specify

pre-requisites resources during the description of the

learning resources. Therefore, metadata must be

supplied by some elements to enable the expression

of such relationship. SCORM provide the “Relation”

category in which the relationship between learning

resources are described. Refering to (ADL, 2009),

the element Relation.Kind defines all the kind of

existing relationship between two learning

resources. This element is bounded by a set of

vocabulary defined by IEEE LOM (Dublin Core).

This vocabulary is :

IsParOf, HasPart, IsVersionOf,

HasVersion, IsFormatOf, HasFormat, References,

IsReferenceBy, IsBasedOn, Requires and IsRequiredBy.

Lesson2

A1

A3

A4

A5

S6 A6

Figure 6: Organization of Learning Resource 2 adapted to

learner L2.

Regarding to this description and this set of

vocabulary, SCORM’s Metadata doesn’t support

pre-requisite relationship. We thus propose to

upgrade the existing set of vocabulary by the

following new ones:

 HasPrerequisite: defines the pre-requisite

resource specified on the element

Relation.Resource, which is needed for the actual

resource.

 IsPrerequisiteBy: defines the resource where the

actual resource is pre-requisite.

This proposed solution enables SCORM to

support the pre-requisite relationship between

learning resources, by upgrading the IEEE LOM

(Dublin Core) vocabulary used in Relation.Kind by

HasPrerequisite and IsPrerequisiteBy. The learner’s

knowledge profile, can be of a great contribution in

building an adapted scheduling of learning

resources.

5.2 Supporting Learning Style

The second side of our contribution consists of the

addition to SCORM of the very elements to let the

adapter schedules learning resources based on

leaning style. As it is defined, SCORM doesn’t give

much importance to pedagogy. Nevertheless, the

“Educational” category holds some elements, which

need to be further analyzed.

As mentioned earlier, David Kolb (Kolb D.,

1984) proposed four types of learner : Divergent,

Convergent, Accommodator and Assimilator.

Authors have thus to prepare four versions of the

same lesson for each type of learner. See Figures 7,

8, 9 and 10 that show four versions of the same

lesson but for different type of learner.

ALearningSystemBasedonLearnerProfile

209

LessonV1

S1

S2

S3

A1

A2

A3

Figure 7: Lesson V1.

LessonV2

S1’

S2’

S3’

A1’

A2’

A3’

Figure 8: Lesson V2.

LessonV3

S1’’

S2’’

S3’’

A1’’

A2’’

A3’’

Figure 9: Lesson V3.

As we can see, the main difference between

these lessons is the content of the learning resources

which leads to the same learning objectives.

Therefore, these four learning resources are

different but are equivalent.

LessonV4

S1’’’

S2’’’

S3’’’

A1’’’

A2’’’

A3’’’

Figure 10: Lesson V4.

When applied to this example the following

assumptions are valid:

1. Lesson V1, V2, V3 and V4 are equivalent;

2. Resources S1, S1’, S1’’, S1’’’ are equivalent;

3. Resources A1, A1’, A1’’, A1’’’ are equivalent;

To enable SCORM supporting learning styles it

is necessary to:

1. Specify the learning style for each learning

resource;

2. Specify the relationship between equivalent

learning resources;

3. Keep track of the preference learning style for

each learner;

4. Have a method to schedule the appropriate

learning resources to learner.

5.2.1 Specifying Learning Style to Learning

Resources

SCORM provides the category “Education” in

which the element “Interactivity Type” indicates the

flow of interactivity between learning resource and

the learner. This element is bounded by a set of

vocabulary defined by IEEE LOM (Dublin Core).

This vocabulary is :

Active, Expositive, Mixed and

Undefined (ADL, 2009).

When comparing this vocabulary to the learning

styles defined earlier, it can be observed that:

1. The Assimilator type of learner expects

information to come only from the resource. This

means that an Expositive resource is well suited.

2. The Accommodator type of learner prefers to

participate to the learning process by being

active. He surely prefers Active resource.

3. The Convergent type of learner prefers neither

pure Expositive resource, nor pure Active

resource; but prefers applying theoretical

concepts. Therefore the suitable resource is the

one which is at the same time Expositive and

Active resource. That is the Mixed resource.

4. The Divergent type of learner prefers neither

Expositive resource, nor Active resource.

Therefore, his preference type of resource is not

proposed yet by this vocabulary.

The proposed solution which enables SCORM to

support all these learning styles, is to add a new

vocabulary for the remaining learning style

(Reflective type).

This proposed solution, gives authors the

opportunity to specify the learning style of the

learning resource on its metadata.

5.2.2 Relationship between Equivalent

Resources

As mentioned earlier, specifying the learning style

for learning resource doesn’t mean that it is a new

knowledge to teach but it is another way to

communicate the knowledge of an existing learning

resource. Therefore, they are two different but

equivalent learning resources.

The proposed solution to enable SCORM to

support this kind of relationship, is to upgrade the

element Relation.Kind with a new vocabulary

“IsEquivalentTo”.

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

210

5.2.3 Keeping Track of Learner Learning

Style

To give the opportunity to the adapter to provide the

right resources to learners, the learning system must

keep track of learning style for each learner. A

learning style profile can be associated to each

learner where it is hold all his preferences learning

styles. This learning style profile must be kept

updated.

5.2.4 Scheduling

When applying all these proposed modification on

SCORM Content Metadata, the obtained result is an

adapted scheduling of learning resources based on

learner profiles (knowledge profile and learning

style profile). As an example, the scheduling of the

four versions of the same lesson described in figures

7, 8, 9 and 10, gives the result of figure 11. Where

Type1, Type2, Type3 and Type4 are the four types

of learning styles as defined by Kolb.

Yes

Lesson

Type1?

Type2?

Type3?

Type4?

LessonV1

LessonV2

LessonV3

LessonV4

Figure 11: Organization of lesson after Scheduling.

This first scheduling gives to the learning system

the ability to select the right resources depending on

the learning style profile of the learner.

However, to adapt this first scheduling based on

the learner profile (learning style and knowledge)

and the pre-requisite resources of the selected

lesson, the system must re-generate a new

scheduling by adding or removing resources in the

appropriate place of the learning style.

6 PROPOSED ARCHITECTURE

To support all the presented concepts of adaptation

based on learner profile, the proposed architecture of

the learning system is as shown in figure 12.

Authors Interface



‐



e

NewLearning

Resources

Learning

Ressources

Learners Profiles

LearningResourcesCollector



r

e

Figure 12: Architecture of a learning System.

This architecture supports the three types of

users: Authors, Experts in pedagogy and learners.

All these users are served by three modules and

communicate with the learning system through

interfaces. The roles of these modules are:

1. Learning resource collector: this module take

care of all new learning resources uploaded by

authors or those of other learning systems, it

stock them into storage for further treatments by

the Organiser;

2. Organizer: the new posted learning resources are

analysed and verified if they contains

pedagogical Metadata or no. If no, the human

expert is solicited to add the appropriate

Metadata. To be added to learning resources of

the learning system, the new learning resources

with pedagogical Metadata are related to the

existing ones. This operation can’t be done

automatically but with the help of the human

expert.

3. Pedagogue: this module satisfy the willing of the

learner by proposing him course based on the

learning resources available, the learner learning

style preference and his background knowledge.

7 CONCLUSIONS

The main contribution of this paper is the

introduction of the pedagogical side of the learning

process into the learning systems. The pedagogical

concepts introduced are the learning style and the

acquired knowledge of the learner.

By this modification, learning systems become

capable to adapt learning resources to the learner

ALearningSystemBasedonLearnerProfile

211

based on his preferred learning style and his

acquired knowledge.

This proposed solution has upgraded SCORM

metadata by introducing some new vocabularies by

which pedagogical concepts were introduced.

To validate this proposed solution an architecture

of learning system is presented. This system is under

development.

REFERENCES

ADL, 2001. « The SCORM Content Aggregation Model »

SCORM_Content_Aggregation.pdf; disponible on

http://www.adlnet.gov/scorm/scorm-version-1-2.

ADL, 2006. “SCORM 2004 3rd edition V1.0

Conformance Requirements”; available on http://

www.adlnet.gov/wp-content/uploads/2011/07/scorm.

2004.3ed.confreq.v1.0.pdf.

ADL, 2009. Sharable Content Object Reference Model

(SCORM) 2004, 4th Edition Content Aggregation

Model (CAM) Version 1.1, available on http://

www.moschorus.com/centre/MosPub/documents/cont

enu/pages/SCORM_2004_4ED_CAM.pdf.

ADLNET: in http://www.adlnet.gov/

SCORM_Users_Guide_For_Programmers.pdf .

Chartier Daniel, 2003. «Les styles d’apprentissage : entre

flou conceptuel et intérêt pratique » in Savoirs 2/2003,

N°2, pp 7-28.

Danijela Milosevic and Mijana Brkovic, 2007. «Adaptive

Learning by Using SCOs Metadata», in

Interdisciplinary Journal of Knowledge and Learning

Objects. Vol 3, 2007.

De Bra P., Smits D., Stash N., 2006. « Creating and

Delivering Adaptive Courses with AHA! » Paper

presended at the Proceeding of the first European

Conference on Technology Enhanced Learning, EC-

TEL 2006, Crete.

Downes S., 2000, “Learning Objects: Resources For

Distance Education WordWide”. International Review

of Research in Open and Distance Learning: Vol. 2,

N° 1.

Dublin Core Metadata Initiative. Available at:

http://www.dublincore.org/

Forte E., Wentland Forte M., Duval E., 1997, The

ARIADNE Project (Part 2): Knowledge Pools for

Computer-based and Telematics-supported Classical,

Open and distance Education, European Journal of

Engineering Education, Vol.22, N°2, pp 153-166.

Gilbert J.E., Han C.Y., 2002. Arthur: A Personalized

Instructional System. Journal of Computing in Higher

Education, 14(1): 113-129;

IEEE, 2001. Information Technology – Learning

Technology – Learning Objects Metadata LOM:

Working Draft V6.1 (2001-05-03) as reference by IMS

Learning. Resource Meta-Data Specification Version

1.2. available at : http://ltsc.ieee.org/

IMS: in http://www.imsglobal.org/learningdesign/

IMS-LR: Learning Resource Meta-data Specification

Version 1.2. includes: IMS Learning Resource Meta-

data Information Model, IMS Learning Resource

Meta-data XML Binding Specification, and IMS

Learning Resource Meta-data Best Practice and

Implementation Guide. Available at:

http://www.imsglobal.org/

Isalem-97 in http://isalem-97.org.

Kolb David, 1984. “Experiental Learning”, Engle Cliffs,

Prentice Hall, 256 p.

Koper R., 2002, “From change to renewal: Educational

technology foundations of electronic learning

environments”. Open University of Netherlands.

K.Verbert et al, 2004. “Towards a Global Component

Architecture for Learning Objects: An Ontology Bases

Approach.” R.Meesman et al (Eds): OTM Workshops

2004, LNCS 3292, pp 713-722, Springer-Verlag

Berlin Heidelberg.

LOM: in http://ltdc.ieee.org/wg12:files/

LOM_1484_12_1_v1_Final_Draft.pdf.

Matteo Baldoni, Cristina Baroglio, Viviana Patti and

Laura Torasso, 2004. « Reasoning about learning

object metadata for adapting SCORM courseware», in

L.Aroyo and C.Tasso, editors, AH 2004: Workshop

Proceeding, Part 1, International Workshop on

Engineering the Adaptive Web, EAW’04: Methods

and Technologies for personalization and Adaptation

in the Semantic Web, Eindhoven, The Netherlands,

August (2004): 4-13.

Moodle in https://moodle.org/

Rebert T. Mason and Timothy J. Ellis, 2009. « Extending

SCORM LOM», in Informing Science and

Information Technology, Vol. 6, 2009. p 863-875.

SCORM: in http://adlnet.org/downloads/70/.cfm.

There Jean, 1998. « Styles d’enseignement, styles

d’apprentissage et pédagogie différenciée en

sciences », in Informations Pédagogiques n°40, Mars

1998.

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

212