Towards Adaptive E-Learning using Decision Support Systems

Authors

  • Maryam Yarandi School of Architecture, Computing and Engineering, University of East London
  • Hossein Jahankhani School of Architecture, Computing and Engineering, University of East London
  • Abdel-Rahman H. Tawil School of Architecture, Computing and Engineering, University of East London

DOI:

https://doi.org/10.3991/ijet.v8iS1.2350

Keywords:

Adaptive learning, e-learning systems, Item response theory, Ontology, Personalised learning

Abstract


The significance of personalization towards learnersâ?? 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 learnersâ?? models during the registration phase to determine learnersâ?? characteristics. The system also tracks learnerâ??s activities and tests during the learning process. Test results are analysed according to the Item Response Theory in order to calculate learnerâ??s abilities. The learner model is updated based on the results of test and learnerâ??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 â??Fraction topicâ? of the mathematics domain. Experimental test results indicated that the pro-posed system improved learning effectiveness and learnerâ??s satisfaction, particularly in its adaptive capabilities.

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Published

2013-01-28

How to Cite

Yarandi, M., Jahankhani, H., & Tawil, A.-R. H. (2013). Towards Adaptive E-Learning using Decision Support Systems. International Journal of Emerging Technologies in Learning (iJET), 8(S1), pp. 44–51. https://doi.org/10.3991/ijet.v8iS1.2350

Issue

Vol. 8 (2013): Special Issue: ICL2012

Section

Special Focus Papers

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