Malaysian Journal of Computer Science (ISSN 0127-9084)
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Article Information
Title:An Empirical Evaluation Of Learner Performance In E-Learning Recommender Systems And An Adaptive Hypermedia System
Auhtor(s): Khairil Imran Ghauth,Nor Aniza Abdullah ,
Journal:Malaysian Journal of Computer Science (ISSN 0127-9084)
Volume:23, No 3
Keywords:E-learning, Recommendation System, Adaptive Hypermedia System, Content-based Filtering, Collaborative Filtering
Abstract:This paper introduces a novel architecture for an e-learning recommender system which is based on good learnersí average ratings strategy and content-based filtering approach. The feasibility of the proposed system is conducted by comparing its performance against other recommender systems and an adaptive hypermedia system in order to measure the effectiveness of the proposed strategy in improving studentsí learning performance. Experimental result has shown that the recommender strategy can improve studentsí performance by at least 12.16%, as compared to other recommendation techniques. A performance evaluation with an adaptive hypermedia system that uses knowledge level as its adaptation feature also showed a positive increase of 14.99% in terms of studentsí performance.

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