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

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.

Putting self‐regulated learning in context: Integrating self‐, co‐, and socially shared regulation of learning

“…Other studies into CRL adopted a social network perspective, and examined characteristics of the networks students’ deploy when regulating their learning. Findings revealed that, in particular, the interaction frequency with which others are engaged in CRL positively relates to students’ self‐reported regulation of learning proficiency 49 …”

“…Findings revealed that, in particular, the interaction frequency with which others are engaged in CRL positively relates to students’ self‐reported regulation of learning proficiency. 49 …”

Social Network Analysis in Undergraduate and Postgraduate Medical Education: A Scoping Review

“…49,58 The influence of social support was also examined, 31 as was the process of peer nominations, 40,43 cheating, 41 and student well-being. [32][33][34]53 In addition, SNA was used to explore informal learning outside the classroom, including on social -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Population Medical students, residents, or fellows in medical and surgical specialties Nonmedical students, faculty members/attending physicians - ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Type of study Quantitative, qualitative, mixed methods Nonprimary publications (reviews, commentaries, opinion pieces, and letters), conference papers without full texts - ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Language Any n/a Abbreviations: SNA, social network analysis; n/a, not applicable.…”

Qualitative ego networks in health professions education: Capturing the self in relation to others

“…This approach reveals an individual's perception of their interactions and relationships with others, emphasising the meaning and dynamics of their local social structures 28 . Data on an ego network can be obtained either quantitatively, 42,43 qualitatively 4 or using mixed methods 3 . Table 1 provides a comparison of quantitative, qualitative and mixed methods approaches to explore ego networks in HPE.…”