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Title: How Instructors Evaluate an e-Learning System? An Evaluation Model Combining Fuzzy AHP with Association Rule Mining
Authors: 林湘霖
Lin, Shiang-Lin
Wang, Chen-Shu
Contributors: 資管博七
Keywords: e-Learning;e-Learning system evaluation;Fuzzy AHP;Association rule mining
Date: 2019-11
Issue Date: 2021-05-26 10:43:34 (UTC+8)
Abstract: Online learning is becoming increasingly popular as a result more courseware is being converted into digital materials, resulting in the rapid development of eLearning systems. The ways in which users (particular instructors) evaluate e-Learning systems are an important issue. In this study, the Fuzzy Analytic Hierarchy Process (FAHP) and Association Rule Mining methods are combined to rank criteria for evaluating e-Learning systems in order of importance. The proposed evaluation model comprises three steps. In step 1, a hierarchal structure of evaluation criteria is established. In step 2, 30 instructors who have practical experience of e-Learning system are interviewed according to this hierarchal structure. Finally, in step 3, a fuzzy mechanism is utilized to normalize the semantic variation among domain experts. Then, the normalized results of the questionnaires are analyzed to obtain the fuzzy weights (via FAHP) and association rules (via Association Rule Mining) among the evaluation criteria. The results of the analysis reveal that “connection quality”, “ease of use”, “visualization”, “waiting time” and “graphical arrangement of interface” are the top five criteria for evaluating an e-Learning system. A developer of an eLearning system can improve user experience using these criteria and their priorities accordingly.
Relation: Journal of Internet Technology, 20:6, 1947-1959
Data Type: article
Appears in Collections:[資訊管理學系] 期刊論文

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