Relationships between medical students' co-regulatory network characteristics and self-regulated learning: a social network study.

Autor: Bransen D; School of Health Professions Education (SHE), Maastricht University, Maastricht, The Netherlands. d.bransen@maastrichtuniversity.nl., Govaerts MJB; Department of Educational Development and Research, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, The Netherlands., Sluijsmans DMA; Faculty of Social Sciences, Radboud University, Nijmegen, The Netherlands., Donkers J; School of Health Professions Education (SHE), Maastricht University, Maastricht, The Netherlands., Van den Bossche PGC; Department of Training and Education, Faculty of Social Sciences, University of Antwerp, Antwerp, Belgium.; Department of Educational Research and Development, School of Business and Economics, Maastricht University, Maastricht, The Netherlands., Driessen EW; Department of Educational Development and Research, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, The Netherlands.
Jazyk: angličtina
Zdroj: Perspectives on medical education [Perspect Med Educ] 2022 Jan; Vol. 11 (1), pp. 28-35. Date of Electronic Publication: 2021 Apr 30.
DOI: 10.1007/s40037-021-00664-x
Abstrakt: 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.
(© 2021. The Author(s).)
Databáze: MEDLINE
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