Article Preview
TopIntroduction To The Study
The educational domain is changing quickly due to progressions in the Information and Communication Technologies (ICT) (Paliwoda-Pękosz & Stal, 2015; Sharma et al., 2017). Massive Open Online Course (MOOC) is one of such provision responsible for changing educational domain. MOOC is an open online learning environment that caters the need of learners but significantly differing from earlier online education approaches (Alraimi et al., 2015). The features that distinguish MOOC from other online approaches are massiveness, openness, free, and quality education. (Liyanagunawardena et al., 2013; Ebben & Murphy, 2014; Stracke et al., 2018). Despite benefits, MOOC providers are confronting with learner’s high attrition rate. The MOOC completion rate is around 10% (Gregori et al., 2018). Students' incessant exit from courses puts learning and education in danger and blocks the formative advancement of MOOCs. The legitimate explanations given by researchers for low completion rate were: (1) limited self-regulated learning aspects; (2) lack of basic computing skills; (3) clashes with other students during discussion; and (4) the sense of isolation (Hew & Cheung, 2014; Shapiro et al., 2017). Nevertheless, Laurillard (2016) found mostly MOOC learners as professionally highly qualified instead of deprived ones as initially imagined. The primary reason is that mostly courses are offered in English language. These aforementioned reasons restrain MOOCs from achieving the objectives of inclusive education. Thus, a study is needed to identify factors that are critical for learners to accept MOOC. But majority of the literature showed that mostly MOOC studies were conducted from the learners’ perspective of developed nations. Based on that true generalisation of the facts cannot be done. This motivated researchers to conduct study of MOOC acceptance in a densely populated developing nation like India for better generalisation of facts. It was also noticed that very few MOOC studies were conducted in Indian context (Nemer & O'Neill, 2019). Hence, researchers examined the subject matter with three purposes. First, to identify key acceptance factors (KAFs) from the extant MOOC literature. With due consideration to earlier work, the current work reassesses the identified KAFs during pandemic for broad generalisation of results. Second, implementing multi-criteria decision-making (MCDM) techniques for ranking and classification of MOOC KAFs, which has not been widely discussed. Third, the outcome presents a comprehensive KAF list, critical for MOOC designers, developers and providers. They need to focus on these KAFs to fulfil the expectations of MOOC learners. As a result, the popularity of MOOC among learners will increase.
The remaining portion of the study is as follows. The following section systematically examines prior MOOC literature to identify KAFs. The subsequent section conceptual development of adopted methodology discusses algorithm of two MCDM techniques namely, fuzzy TOPSIS and fuzzy AHP along with their application on MOOC KAFS. The findings and discussion section presents the results. Contributions and conclusion section discusses the implications of the study along with concluding remarks. Finally, future bearings and shortcomings of this study are briefly discussed under the limitations and future direction section.