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Towards Adaptive Web-Based Learning Systems Katerina Georgouli, MSc, PhD Associate Professor T.E.I. of Athens Dept. of Informatics Tempus.

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Presentation on theme: "Towards Adaptive Web-Based Learning Systems Katerina Georgouli, MSc, PhD Associate Professor T.E.I. of Athens Dept. of Informatics Tempus."— Presentation transcript:

1 Towards Adaptive Web-Based Learning Systems Katerina Georgouli, MSc, PhD Associate Professor T.E.I. of Athens Dept. of Informatics Tempus CD JEP Workshop “Tools for CS education” Bitola, 2003

2 Bitola, December Web-based learning systems (WBLS)  Support and partially automate the instructional process in a subject field  Follow the general model of usual instructional systems using web in the instructional process  more sophisticate or commercial WBLS try to facilitate communication among the human agents incorporating synchronous and asynchronous communication tools.

3 Bitola, December Instructional models of WBLS  The information based models which serve only for information retrieval  The educational material based models for the dissemination of this material to distant students  The enriched classroom models, which offer distance learning complementary to traditional classroom-based teaching  The virtual classroom models which emphasize on collaboration and computer mediated human interaction

4 Bitola, December Effectiveness of WBLS Indispensable properties of effective Web- based learning systems are:  adaptivity,  retrieval of history and state,  comparison of results,  existence of alternative teaching strategies,  shared reference databases, and  problem databases.

5 Bitola, December Adaptive Educational Hypermedia (AEH) is a new generation of Educational Hypermedia (EH) systems, which possess the ability to:  make intelligent decisions, aiming to support learners without being directive,  increase the functionality of hypermedia combining free browsing with personalisation,  support all the continuum of learning modes, from pure system-controlled to learner- controlled

6 Bitola, December Student Model AEH cater information to the user and may guide the user in the information space to present the most relevant material, taking into account a model, called Student Model, of the user’s:  goals,  interests,  preferences,  competence level and  motivation.

7 Bitola, December Adaptivity in AEH Adaptivity may be at the content level or at the link level.  Content level adaptivity is the dynamic generation of content based on the student model (adaptive presentation).  Link level adaptivity, on the other hand, assumes a static content and alters the appearance or prominence of the links connecting elements of this hyperspace (adaptive navigation).

8 Bitola, December Adaptation Technologies Brusilovsky’s taxonomy (Brusilovsky, 2001)  adaptive presentation  adaptive navigation support  curriculum sequencing (most suitable, individually planned, sequence of knowledge units for studying)  problem-solving support (adaptable to learners help during solving an educational problem) Actually, in several AEH, the above technologies are combined, enriching systems’ functionality and enhancing support offered to learners.

9 Bitola, December The challenge in the AEH area  To simplify AEH construction through web- based authoring environments and  To make their reuse possible through the use of metadata models based on hypermedia structures (e.g. SCORM 3.1 specifications) Our proposal: The Adaptive Hypermedia Metadata (AHM) model adding a structure for representing teaching strategies

10 Bitola, December Adaptive Hypermedia Metadata (AHM) Structures AHM supports the adaptive techniques of Brusilovsky’s taxonomy, combining the different structured objects to implement a range of adaptive hypermedia techniques: the data basic building blocks, the navigation link basic building blocks, the teaching strategy, the Type of Educational Objective (TEO), the chain and the concept.

11 Bitola, December The Data Object The data object represents any piece of media like text, image, graphic, video etc. These objects can be manipulated by any technique from Brusilovsky’s taxonomy in order to adapt the presentation and the navigation support to the user. Data objects have a context attribute attached to each of them. Context attributes indicate whether a data object will be visible or not to a user with a specific user profile.

12 Bitola, December The Link Object Links (navigation or semantic) are associations between a data object and one or more other data objects or other associations.  Navigation links have context attributes attached to them, indicating whether they should be visible or not according to the user’s profile.  Semantic links have the loose attribute attached to them indicating whether the link may change from a data knowledge unit to another during a curriculum sequencing adaptation procedure.

13 Bitola, December The Teaching Strategy Object It is used to represent a teaching strategy, e.g. different tactics to support a user in answering correctly an exercise. A teaching strategy always supports the same teaching model, e.g. always uses analogies for tutoring, changing the teaching tactic (implicity, explicity or anything in between) to help the student understanding the subject matter.

14 Bitola, December The Type Of Educational Objective (TEO) Alternative options to succeed an educational objective, filtered by the user. For example:  choose a specific language for the text lessons,  decide which alternative teaching strategies, sharing common believes will compose a specific teaching style.

15 Bitola, December The Chain Object A set of knowledge or teaching chain objects to be viewed in sequence.  Knowledge chain objects are knowledge units, or smaller chains of knowledge units associated by links (loose or not) determining the curriculum sequencing.  Teaching chain objects are alternative teaching strategies of the same teaching style to be implemented in sequence during tutoring.

16 Bitola, December The Concept Object An association used to collect together multiple data objects that represent:  the same conceptual entity (for example the same text lesson in different languages or  the same self-assessment exercise contextualized in alternative ways suitable for different teaching strategies).

17 Bitola, December Conclusions – Future work The AHM metadata model provides the means to implement a wide range of adaptive technologies. We believe that AEH systems that implement the AHM model have an advantage in that they may handle adaptation consistently across different techniques and media. Our aim is to work on open source LMS to explore the possibility of adding contextual structures in SCORM 1.3 to allow it to support some of the techniques described by Brusilovsky.

18 Bitola, December THANK YOU!


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