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

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 characteri...

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Detalles Bibliográficos
Autores principales: Bransen, Derk, Govaerts, Marjan J. B., Sluijsmans, Dominique M. A., Donkers, Jeroen, Van den Bossche, Piet G. C., Driessen, Erik W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bohn Stafleu van Loghum 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733107/
https://www.ncbi.nlm.nih.gov/pubmed/33929685
http://dx.doi.org/10.1007/s40037-021-00664-x
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s40037-021-00664-x) contains supplementary material, which is available to authorized users.