%0 Journal Article
%T Towards Adaptive E-Learning using Decision Support Systems
%A Maryam Yarandi
%A Hossein Jahankhani
%A Abdel-Rahman H. Tawil
%J International Journal of Emerging Technologies in Learning (iJET)
%D 2013
%I Universit?t Kassel
%R 10.3991/ijet.v8is1.2350
%X The significance of personalization towards learners¡¯ needs has recently been agreed by all web-based instructional researchers. This study presents a novel ontol-ogy semantic-based approach to design an e-learning Deci-sion Support System (DSS) which includes major adaptive features. The ontologically modelled learner, learning do-main and content are separately designed to support per-sonalized adaptive learning. The proposed system utilise captured learners¡¯ models during the registration phase to determine learners¡¯ characteristics. The system also tracks learner¡¯s activities and tests during the learning process. Test results are analysed according to the Item Response Theory in order to calculate learner¡¯s abilities. The learner model is updated based on the results of test and learner¡¯s abilities for use in the adaptation process. Updated learner models are used to generate different learning paths for individual learners. In this study, the proposed system is implemented on the ¡°Fraction topic¡± of the mathematics domain. Experimental test results indicated that the pro-posed system improved learning effectiveness and learner¡¯s satisfaction, particularly in its adaptive capabilities.
%K Adaptive learning
%K e-learning systems
%K Item response theory
%K Ontology
%K Personalised learning
%U http://online-journals.org/i-jet/article/view/2350