A Hybrid Approach Based on Fuzzy TOPSIS-AHP for Ranking and Classifying MOOC Key Acceptance Factors

Neeraj Chopra, Rajiv Sindwani and Manisha Goel
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Neeraj Chopra: J. C. Bose University of Science and Technology, YMCA, India
Rajiv Sindwani: J. C. Bose University of Science and Technology, YMCA, India
Manisha Goel: J. C. Bose University of Science and Technology, YMCA, India

International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 2021, vol. 16, issue 5, 1-20

Abstract: This investigation is done during COVID-19 to identify, rank, and classify MOOC (massive open online course) key acceptance factors (KAFs) from an Indian perspective. A systematic literature review identifies 11 KAFs of MOOC. One more novel factor named ‘contingent instructor' is proposed by the authors considering pandemic and new normal post-COVID-19. The paper implements two popular fuzzy MCDM (multiple-criteria decision-making) techniques, namely fuzzy TOPSIS and fuzzy AHP, on 12 KAFs. The fuzzy TOPSIS approach is used to rank factors. Affordability, performance expectancy and digital didactics are found as the top three KAFs. Fuzzy AHP classified KAFs into three groups, namely high, moderate, and low influential. Examination of the literature indicates that this study is among the first attempt to prioritize and classify MOOC KAFs using fuzzy TOPSIS and fuzzy AHP approach. The results offer managerial guidance to stakeholders for effective management of MOOC, resulting in higher acceptance rate. Likewise, this investigation will upgrade the comprehension of MOOC KAFs among academicians.

Date: 2021
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