How instructors evaluate an e-learning system? An evaluation model combining fuzzy AHP with association rule mining

Online learning is becoming increasingly popular as a result more courseware is being converted into digital materials, resulting in the rapid development of e-Learning 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 e-Learning system can improve user experience using these criteria and their priorities accordingly.