TY - JOUR
T1 - Relationships between medical students' co-regulatory network characteristics and self-regulated learning
T2 - a social network study
AU - Bransen, Derk
AU - Govaerts, Marjan J. B.
AU - Sluijsmans, Dominique M. A.
AU - Donkers, Jeroen
AU - Van den Bossche, Piet G. C.
AU - Driessen, Erik W. F.
N1 - Funding Information:
The authors wish to thank all course coordinators and staff members within the master’s in medicine programme at Maastricht University for their support in collecting the data.
Publisher Copyright:
© 2021, The Author(s).
PY - 2022/1
Y1 - 2022/1
N2 - 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 (beta = 0.095, p < 0.05) and between network size and tie strength (beta = 0.530, p < 0.001), and a negative relationship between network diversity and tie strength (beta = -0.474, p < 0.001). Students' perceptions of learning opportunities showed positive relationships with both self-regulated learning (beta = 0.295, p < 0.001) and co-regulatory network size (beta = 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.
AB - 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 (beta = 0.095, p < 0.05) and between network size and tie strength (beta = 0.530, p < 0.001), and a negative relationship between network diversity and tie strength (beta = -0.474, p < 0.001). Students' perceptions of learning opportunities showed positive relationships with both self-regulated learning (beta = 0.295, p < 0.001) and co-regulatory network size (beta = 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.
KW - Self-regulated learning
KW - Co-regulated learning
KW - Network characteristics
KW - Social network analysis
KW - Clinical clerkship contexts
U2 - 10.1007/s40037-021-00664-x
DO - 10.1007/s40037-021-00664-x
M3 - Article
C2 - 33929685
SN - 2212-2761
VL - 11
SP - 28
EP - 35
JO - Perspectives on Medical Education
JF - Perspectives on Medical Education
IS - 1
ER -