Purpose Collaborative communication and teamwork are core competencies in medical education, yet they remain difficult to assess objectively during Problem-Based Learning (PBL). This study evaluates Social Network Analysis (SNA) as a technology-enhanced assessment tool to quantify peer collaboration patterns and identify learners’ engagement profiles. We examined how PBL interaction networks differ across cohorts and whether SNA-derived indicators align with academic achievement. Methods A comparative SNA was conducted across 17 PBL groups (N = 176; Year 1: 77, Year 2: 99). Directed, weighted ties were constructed by integrating ranked peer nominations with a validated five-item collaboration rubric to generate hybrid edge weights. Cohort-level network properties (density, path length, transitivity, reciprocity, modularity) and node-level centrality measures (in-degree, closeness, betweenness) were computed as indicators of collaborative competence. Between-cohort differences were analysed using non-parametric tests, and alignment between centrality and cumulative grade point average (CGPA) was examined to provide preliminary validity evidence. Results Year 2 demonstrated a more cohesive and integrated collaboration structure, reflected by higher density (0.313 vs. 0.277), greater transitivity (0.532 vs. 0.443), and shorter average path lengths (1.72 vs. 2.06). At the individual level, Year 2 students showed significantly higher closeness (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(p < .01\)</EquationSource> </InlineEquation>) and lower betweenness (p = .027), indicating more efficient communication pathways. Across both cohorts, higher in-degree (representing peer-recognized collaborative competence) showed the strongest alignment with CGPA, whereas other centrality measures demonstrated smaller, cohort-dependent effects. Conclusion SNA provides quantifiable, competency-linked indicators of collaboration and communication in PBL, functioning as a novel technology-enhanced assessment tool. Patterns of social prominence and integration were meaningfully associated with academic achievement, suggesting that SNA may support early identification of highly engaged learners and those at risk of marginalization. These findings highlight the potential of SNA to complement existing assessment methods and enhance feedback within competency-based medical education. Further research using longitudinal and multilevel designs is warranted to strengthen the tool’s validity and inform its integration into routine educational assessment.

Social network analysis as a technology-enhanced assessment tool for collaborative skills in medical PBL

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2026年5月9日

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Ahmad Hathim Ahmad Azman,
Nee Tiong,
Mohammad Arif Kamarudin,
Zamira Hasanah Zamzuri

摘要

Purpose

Collaborative communication and teamwork are core competencies in medical education, yet they remain difficult to assess objectively during Problem-Based Learning (PBL). This study evaluates Social Network Analysis (SNA) as a technology-enhanced assessment tool to quantify peer collaboration patterns and identify learners’ engagement profiles. We examined how PBL interaction networks differ across cohorts and whether SNA-derived indicators align with academic achievement.

Methods

A comparative SNA was conducted across 17 PBL groups (N = 176; Year 1: 77, Year 2: 99). Directed, weighted ties were constructed by integrating ranked peer nominations with a validated five-item collaboration rubric to generate hybrid edge weights. Cohort-level network properties (density, path length, transitivity, reciprocity, modularity) and node-level centrality measures (in-degree, closeness, betweenness) were computed as indicators of collaborative competence. Between-cohort differences were analysed using non-parametric tests, and alignment between centrality and cumulative grade point average (CGPA) was examined to provide preliminary validity evidence.

Results

Year 2 demonstrated a more cohesive and integrated collaboration structure, reflected by higher density (0.313 vs. 0.277), greater transitivity (0.532 vs. 0.443), and shorter average path lengths (1.72 vs. 2.06). At the individual level, Year 2 students showed significantly higher closeness ( \(p < .01\) ) and lower betweenness (p = .027), indicating more efficient communication pathways. Across both cohorts, higher in-degree (representing peer-recognized collaborative competence) showed the strongest alignment with CGPA, whereas other centrality measures demonstrated smaller, cohort-dependent effects.

Conclusion

SNA provides quantifiable, competency-linked indicators of collaboration and communication in PBL, functioning as a novel technology-enhanced assessment tool. Patterns of social prominence and integration were meaningfully associated with academic achievement, suggesting that SNA may support early identification of highly engaged learners and those at risk of marginalization. These findings highlight the potential of SNA to complement existing assessment methods and enhance feedback within competency-based medical education. Further research using longitudinal and multilevel designs is warranted to strengthen the tool’s validity and inform its integration into routine educational assessment.