A Model for an Adaptive Hypermedia Learning System Based on Data Mining Technique

Author:

Lamia Mahnane1,Hafidi Mohamed1

Affiliation:

1. University of Badji Moktar, Algeria

Abstract

Since the learning style of each learner is different. Adaptive hypermedia learning system (AHLS) must fit different learner's needs. A number of AHLS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: less attention was paid to the relationship between learning styles and learning performance. This paper proposes an AHLS model based on learning styles and learning performance. 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 learning 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.

Publisher

IGI Global

Reference48 articles.

1. State of The Art of Learning Styles-Based Adaptive Educational Hypermedia Systems (Ls-Baehss)

2. Alves, P., Pires, J., & Amaral, L. (2009, March). The role of learning styles in intelligent tutoring systems. In Proceedings of the CSEDUInternational Conference on Computer Supported Education. Lisbon, Portugal: INSTICC Press.

3. A Survey of Clustering Data Mining Techniques

4. Survey of learning experiences and influence of learning style preferences on user intentions regarding MOOCs

5. Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance

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