Exploring the link between self‐regulated learning and learner behaviour in a massive open online course

• Published in: Journal of computer assisted learning Vol. 38; no. 4; pp. 993 - 1004
• Main Authors: Jansen, Renée S., Leeuwen, Anouschka, Janssen, Jeroen, Kester, Liesbeth
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Inc 01-08-2022; Wiley; Wiley Subscription Services, Inc
• Subjects: Autonomy; CAI; Clusters; Computer assisted instruction; Distance learning; Instructional design; learner behaviour; Learning Processes; MOOC; MOOCs; Online Courses; online education; Online instruction; Personal Autonomy; process mining; Profiles; Self Control; Self regulation; SRL; Student Behavior
• ISSN: 0266-4909; 1365-2729
• DOI: 10.1111/jcal.12675

Background
Learners in Massive Open Online Courses (MOOCs) are presented with great autonomy over their learning process. Learners must engage in self‐regulated learning (SRL) to handle this autonomy. It is assumed that learners' SRL, through monitoring and control, influences learners' behaviour within the MOOC environment (e.g., watching videos). The exact relationship between SRL and learner behaviour has however not been investigated.
Objectives
We explored whether differences in SRL are related to differences in learner behaviour in a MOOC. As insight in this relationship could improve our understanding of the influence of SRL on behaviour, could help explain the variety in online learner behaviour, and could be useful for the development of successful SRL support for learners.
Methods
MOOC learners were grouped based on their self‐reported SRL. Next, we used process mining to create process models of learners' activities. These process models were compared between groups of learners.
Results and conclusions
Four clusters emerged: average regulators, help seekers, self‐regulators, and weak regulators. Learners in all clusters closely followed the designed course structure. However, the process models also showed differences which could be linked to differences in the SRL scores between clusters.
Takeaways
The study shows that SRL may explain part of the variability in online learner behaviour. Implications for the design of SRL interventions include the necessity to integrate support for weak regulators in the course structure.
Lay Description
Practitioners Notes
What is currently known:
Learners' self‐regulated learning (SRL) is related to learner behaviour.
Inadequate SRL may result in learner dropout in MOOCs.
Learners in open online education behave in a variety of ways.
What this paper adds:
Most learners follow the designed course structure.
Learners' SRL influences learner behaviour in a MOOC.
Low SRL activity is related to adherence to the course structure.
High SRL activity is related to more variety in learner behaviour.
Implications for practitioners:
SRL support should be integrated in the course structure.
Results of process mining can inform instructional design.