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- Title
Relationships between medical students' co-regulatory network characteristics and self-regulated learning: a social network study.
- Authors
Bransen, Derk; Govaerts, Marjan J. B.; Sluijsmans, Dominique M. A.; Donkers, Jeroen; Van den Bossche, Piet G. C.; Driessen, Erik W.
- Abstract
Introduction: Recent conceptualizations of self-regulated learning acknowledge the importance of co-regulation, i.e., students' interactions with others in their networks to support self-regulation. Using a social network approach, the aim of this study is to explore relationships between characteristics of medical students' co-regulatory networks, perceived learning opportunities, and self-regulated learning. Methods: The authors surveyed 403 undergraduate medical students during their clinical clerkships (response rate 65.5%). Using multiple regression analysis, structural equation modelling techniques, and analysis of variance, the authors explored relationships between co-regulatory network characteristics (network size, network diversity, and interaction frequency), students' perceptions of learning opportunities in the workplace setting, and self-reported self-regulated learning. Results: Across all clerkships, data showed positive relationships between tie strength and self-regulated learning (β = 0.095, p < 0.05) and between network size and tie strength (β = 0.530, p < 0.001), and a negative relationship between network diversity and tie strength (β = −0.474, p < 0.001). Students' perceptions of learning opportunities showed positive relationships with both self-regulated learning (β = 0.295, p < 0.001) and co-regulatory network size (β = 0.134, p < 0.01). Characteristics of clerkship contexts influenced both co-regulatory network characteristics (size and tie strength) and relationships between network characteristics, self-regulated learning, and students' perceptions of learning opportunities. Discussion: The present study reinforces the importance of co-regulatory networks for medical students' self-regulated learning during clinical clerkships. Findings imply that supporting development of strong networks aimed at frequent co-regulatory interactions may enhance medical students' self-regulated learning in challenging clinical learning environments. Social network approaches offer promising ways of further understanding and conceptualising self- and co-regulated learning in clinical workplaces.
- Subjects
SOCIAL learning; STUDENT attitudes; CLINICAL clerkship; MEDICAL students; SOCIAL networks; MULTIPLE regression analysis
- Publication
Perspectives on Medical Education, 2022, Vol 11, Issue 1, p28
- ISSN
2212-2761
- Publication type
Article
- DOI
10.1007/s40037-021-00664-x