Publication | Closed Access
The role of students' motivation and participation in predicting performance in a MOOC
399
Citations
46
References
2016
Year
E-learningEducational PsychologyEducationParticipation Influence StudentsOnline LearningStudent OutcomeStudent EngagementStudent MotivationGeneral Intrinsic MotivationLearning StrategiesMooc PerformanceAchievement GoalLearning SciencesMotivationLearning AnalyticsOnline Course DevelopmentLearning BehaviourPerformance StudiesOnline TeachingOnline EducationLearning DesignAchievement MotivationSelf-regulated Learning
MOOCs have expanded learning opportunities worldwide, yet understanding learner motivation, self‑regulation, and factors influencing performance remains underexplored. The study investigates how motivation and participation affect performance of students who complete a MOOC. The authors assessed motivation and participation levels of students who persisted to the end of the course. Participation was the strongest predictor of performance, followed by motivation; motivation and participation influenced each other, and situational interest mediated the impact of intrinsic motivation and participation on performance. © 2016 John Wiley & Sons Ltd.
Abstract 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
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