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Impact of learner motivation on MOOC preferences: Transfer vs. made MOOCs

Publisher : 2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015

Campus : Coimbatore

School : School of Business

Year : 2015

Abstract : pFrom being video repositories of courseware to dynamic adaptive e-learning models, the Massive Online Open Courseware (MOOC) ecosystem has matured significantly leading to a wider taxonomy of MOOCs. The most recent taxonomy of MOOCs captures eight broad classifications of MOOCs. Learners have different motivational drivers to choose and consume the different categories of MOOCs. There have been in-depth studies on the design of various pedagogical styles for MOOCs. There are also studies on learner's motivation for effective learning, retention and completion. However there have been few contributions to the literature in discerning the varying motivational drivers for choosing to consume the different styles of MOOCs. This study shows how motivation impacts the variations in the Indian learner's preferences to consume two contrasting classes of MOOCs which have fundamentally different philosophies: Transfer MOOCs and Made MOOCs. MOOCs created with recordings of existing classroom video lectures are categorized as Transfer MOOCs. Courses created exclusively for being presented as a MOOC with extensive use of modern video production and interactive digital content fall under Made MOOCs. The measure for learner's motivation has been developed through extensive exploratory studies and with revelations from relevant literature. The methodology involved a pan-India survey. Using the collected responses, an analytical model of preference for the respective MOOC categories was built using Ordinal Logit Regression with the scales on the motivation factors as the independent variables and age, gender, education and occupation as control variables. The results show preference for Transfer MOOCs and Made MOOCs are impacted by different motivating factors. These results would empower the MOOC designers to better understand the motivation of learners to prefer their respective MOOC styles and hence better cater to the consumer's needs. © 2015 IEEE./p

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