出版社：University of Malaya * Faculty of Computer Science and Information Technology
摘要：This paper introduces a novel architecture for an elearning recommender system which is based on good learners’ average ratings strategy and contentbased 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 students’ learning performance. Experimental result has shown that the recommender strategy can improve students’ 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 students’ performance.
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