A Model for an Adaptive e-Learning Hypermedia System

A Model for an Adaptive e-Learning Hypermedia System

Lamia Mahnane (University of Badji Moktar, Annaba, Algeria), Laskri Mohamed Tayeb (LRI Laboratory, University of Badji Moktar, Annaba, Algeria) and Philippe Trigano (University of Technologie of Compiegne, Compiegne, France)
DOI: 10.4018/ijicte.2013100102
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Recent years have shown increasing awareness for the importance of adaptivity in e-learning. Since the learning style of each learner is different. Adaptive e-learning hypermedia system (AEHS) must fit different learner’s needs. A number of AEHS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: lack of maintenance, adaptation to learning style, less attention was paid to thinking styles and the insertion of specific teaching strategies into learning content. This paper proposes an AEHS model based on thinking styles and knowledge level. On one hand, the developed prototype will assist a learner in accessing and using learning resources which are adapted according to his/her personal characteristics (in this case his/her thinking style and level of knowledge). On the other hand, it will facilitate the learning content teacher in the creation of appropriate learning objects and their application to suitable pedagogical strategies.
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Literature Review

There were some studies related to AEHS with different focuses and approaches can be found in the literature, one may cite:

  • Dall Acqua (Dall, 2009) proposed a multidimensional design model, describing the specifications needed for an educational environment and examined the condition that makes a learning environment “adaptive”;

  • Dekson and Suresh (2010) conducted a survey on the various models of adaptive content delivery system and proposed newer methods of delivering adaptive content for adaptive e portfolio system;

  • Mustafa and Sharif (2011) presented an approach to integrate learning styles into AEHS and assessed the effect of adapting educational materials individualized to the student’s learning style;

  • PERSO (Chorfi, & Jemni, 2004) employs RBC approach (case based reasoning) to determine which courses to suggest to learners based on their knowledge level, and their media preferences;

  • TANGOW (Paredes, P., & Rodriguez, P, 2004) is based on two dimensions of FSLSM (Felder- Silverman Learning style Model): deductive/ intuitive and sequential/ global. Learners are invited to fill ILS (Index of Learning Styles) assessment when they connect to the system for the first time, the learner‘s model is initialized accordingly. Afterword, learner's actions are monitored by the system, and if they controvert the expected behavior for these learning preferences, the model is updated;

  • WELSA (Web-based Educational with Learning Style adaptation) (Popescu, Trigano, Badica, Butoi, & Duica, 2008) adopts the unified model of learning style which embeds characteristics of several models proposed in literature, to adapt courses to learners.

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