Exploring success factors and relationships in virtual learning using ISM and fuzzy MICMAC analysis
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2024-04-15
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24058440
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2-s2.0-85188793125
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Heliyon
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10
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7
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SCOPUS
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Heliyon Vol.10 No.7 (2024)
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Chuaphun P., Samanchuen T. Exploring success factors and relationships in virtual learning using ISM and fuzzy MICMAC analysis. Heliyon Vol.10 No.7 (2024). doi:10.1016/j.heliyon.2024.e28100 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/97843
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Exploring success factors and relationships in virtual learning using ISM and fuzzy MICMAC analysis
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The COVID-19 pandemic's consequences have led to a global change in educational settings towards online learning. The utilization of virtual learning (VL) has increased significantly. This study aimed to extract the success factors of VL and also examine the relationships among them. The research method involves examining factors identified in the literature review and seeking confirmation from experts using the Content Validity Index (CVI) method. Ten success factors are extracted and confirmed, including Technological, Management, Learning Capability, Pedagogical, Ethical, Resource Support, Interface Design, Evaluation, Institutional, and Study Environment. Based on the Interpretive Structural Model (ISM) method and the fuzzy matrix of cross-impact multiplications applied to classification (MICMAC), which divides the factors into five levels, the relationship between these factors is examined. Level I emphasizes the importance of evaluation mechanisms. Level II stresses integrating pedagogical, ethical, resource support, and institutional aspects. Level III highlights the alignment of learner capabilities with platform interfaces. Level IV underscores the significance of the learning environment. Lastly, Level V emphasizes the interplay between technology and management in VL's expansion. The findings of this study can be developed and customized through collaboration among instructors, learners, and institutions. Moreover, the findings from correlating success factors can be applied in practical learning experiments or utilized to develop efficient modeling manuals.