Abstract:

The recommender systems are the technique of processing and evaluation of user behavioral data to suggest the resources according to user needs. In e-learning system, it is used to propose resources and relevant contents to learners. Thus e-Learning recommender system can take advantage of semantic reasoning capabilities to overcome common limitations of current systems and improve the recommendations’ quality and provide learners with relevant learning content. Although, most e-learning systems are often ignoring students with disabilities and they are not providing appropriate adaptation or personalization to satisfy their needs. In this paper, we present a personalized recommendation e-learning system for students with learning disabilities, a system that makes use of representations of learner profiles and learning object based on ontologies to give a semantic application with personalized services, this model allows the learning environment to present to students learning materials in suitable formats while considering their disability and learning needs through an ontology-driven personalized e-learning system model.

Keywords:

e-learning system, recommended systems, semantic web, ontologies, learning disabilities, learning object.