The role of students' motivation and participation in predicting performance in a MOOC

The role of students' motivation and participation in predicting performance in a MOOC

Over the last 5 years, massive open online courses (MOOCs) have increasingly provided learning opportunities across the world in a variety of domains. As with many emerging educational technologies, why and how people come to MOOCs needs to be better understood and importantly what factors contribut...

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Bibliographic Details
Published in:Journal of computer assisted learning Vol. 32; no. 3; pp. 218 - 231
Main Authors: de Barba, P.G., Kennedy, G.E., Ainley, M.D.
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01-06-2016
Wiley-Blackwell
Wiley Subscription Services, Inc
Subjects:
Academic Achievement
Academic Persistence
Assessments
College students
Computer assisted instruction
Design analysis
Distance education
Distance learning
Education
Educational psychology
Educational Technology
Electronic Learning
Large Group Instruction
Learning
learning analytics
Mathematical analysis
MOOC
MOOCs
Motivation
Online Courses
participation
persistence
Predictor Variables
Student Motivation
Student Participation
Students
Technology Uses in Education
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Summary:Over the last 5 years, massive open online courses (MOOCs) have increasingly provided learning opportunities across the world in a variety of domains. As with many emerging educational technologies, why and how people come to MOOCs needs to be better understood and importantly what factors contribute to learners' MOOC performance. It is known that online learning environments require greater levels of self‐regulation, and that high levels of motivation are crucial to activate these skills. However, motivation is a complex construct and research on how it functions in MOOCs is still in its early stages. Research presented in this article investigated how motivation and participation influence students' performance in a MOOC, more specifically those students who persist to the end of the MOOC. Findings indicated that the strongest predictor of performance was participation, followed by motivation. Motivation influenced and was influenced by students' participation during the course. Moreover, situational interest played a crucial role in mediating the impact of general intrinsic motivation and participation on performance. The results are discussed in relation to how educators and designers of MOOCs can use knowledge emerging from motivational assessments and participation measures gleaned from learning analytics to tailor the design and delivery of courses. © 2016 John Wiley & Sons Ltd
Bibliography:ark:/67375/WNG-SF451PCF-6
ArticleID:JCAL12130
istex:3329C0934083DA9FD38F0D030E0FD0443D98D595
The University of Melbourne
Science of Learning Research Centre
Institute for a Broadband-Enabled Society
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0266-4909
1365-2729
DOI:10.1111/jcal.12130