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Motivation to learn in massive open online courses: Examining aspects of language and social engagement
ARTICLE

, Head of the Science and Learning Technology Group, Israel ; , The Department of Education in Science and Technology, Israel ; , The Department of Chemical Engineering, Israel

Computers & Education Volume 94, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd

Abstract

Learning is mediated by language of instruction and social engagement. Both factors may play a significant role in understanding motivation to learn in massive open online courses (MOOCs). Therefore, the goal of this study was threefold: a. to compare motivation patterns of MOOC participants who study the same course but in a different language of instruction; b. to examine relationships between motivation gain and diverse modes of engagement; and c. to characterize MOOC completers according to their learning motivation. An exploratory case-study was conducted in the settings of a MOOC in Nanotechnology and Nanosensors, delivered in two languages: English and Arabic. The research sample included 325 participants from the English (N = 289) and Arabic (N = 36) MOOCs. The study applied the mixed methods approach, collecting data via pre- and post-questionnaires, forum posts, and email messages. Findings indicated that regardless the language of instruction, MOOC participants were driven to learn by similar goals, emphasizing intrinsic motivation and self-determination. Findings indicated a positive relationship between motivation gain, the number of messages posted to the online forums, and the number of members in the online study groups. Five types of MOOC completers were identified: problem-solvers, networkers, benefactors, innovation-seekers, and complementary-learners.

Citation

Barak, M., Watted, A. & Haick, H. (2016). Motivation to learn in massive open online courses: Examining aspects of language and social engagement. Computers & Education, 94(1), 49-60. Elsevier Ltd. Retrieved September 29, 2020 from .

This record was imported from Computers & Education on January 31, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.compedu.2015.11.010

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