 Identifying and prioritising MOOC attrition reasons using best worst methodNeeraj Chopra, Rajiv Sindwani, Manisha Goel and Ashutosh Nigam International Journal of Business and Globalisation, 2024, vol. 38, issue 4, 481-496 Abstract: Despite the noticeable strengths of massive open online courses (MOOCs), the high attrition rate of learners is posing challenges in its way to successful diffusion. This created the need to know the reasons behind the high attrition rate among learners. The present work identifies nine MOOC attrition specific reasons from the literature on MOOC and resistance to innovation. The study also classifies and prioritises the attrition reasons in terms of criticality. The reasons for attrition are grouped according to their nature into three categories, referred to as general reasons. The prominence of reasons is established by using the best worst method (BWM), a multi-criteria decision-making (MCDM) technique. The optimised weights determined by BWM arranged them from most critical to least critical in terms of learners attrition. The results revealed technical reasons as the most critical general reason. The most and least critical specific reasons are identified as perceived risk and no penalty or reward. The study also suggested effective measures to address the challenges posed by various attrition reasons. Keywords: MOOC attrition; prioritisation; best worst method; BWM; general reasons; specific reasons. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbglo:v:38:y:2024:i:4:p:481-496 Access Statistics for this article More articles in International Journal of Business and Globalisation from Inderscience Enterprises Ltd |
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