期刊论文详细信息
Malaysian Journal of Computer Science
An Empirical Evaluation Of Learner Performance In E-Learning Recommender Systems And An Adaptive Hypermedia System
Khairil Imran Ghauth1  Nor Aniza Abdullah1 
关键词: E-learning;    Recommendation System;    Adaptive Hypermedia System;    Content-based Filtering;    Collaborative Filtering;   
DOI  :  
学科分类:社会科学、人文和艺术(综合)
来源: University of Malaya * Faculty of Computer Science and Information Technology
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【 摘 要 】
This paper introduces a novel architecture for an e-learning recommender system which is based on good learners�? 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 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.
【 授权许可】

Unknown   

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