Examining the use of prompts to facilitate self-regulated learning in Massive Open Online Courses

L.Y.J. Wong, Martine Baars, Björn B de Koning, Fred Paas

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The limited instructional support in Massive Open Online Courses (MOOCs) inherently demands learners to self-regulate their learning. MOOC research shows that learners are more successful when they engage in self-regulated learning (SRL) behaviors such as planning what to study and reviewing study materials. However, many learners struggle with SRL. In this study, we examined the effect of two types of SRL prompts (i.e., questions or a combination of questions and recommendations) on SRL activities, course engagement, and performance in MOOCs. Learners either received questions supporting SRL, questions supporting SRL followed by recommendations, or neither questions supporting SRL nor recommendations. Log data was used to examine learners’ behavior in the MOOCs. Results showed the SRL prompts, in general, are effective in enhancing SRL-related activities and course engagement. However, the effectiveness of the SRL prompts may be influenced by the complexity of the MOOCs. The current study adds to the field of SRL by examining prompting as an approach to enhance SRL in MOOCs.
Original languageEnglish
Article number106596
Pages (from-to)1-27
JournalComputers in Human Behavior
Volume115
DOIs
Publication statusPublished - Feb 2021
Externally publishedYes

Keywords

  • Self-regulated learning (SRL)
  • Massive open online course (MOOC)
  • Video prompts
  • Log file analysis
  • Process mining
  • Course performance

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