ArticleAdvances in medical education and practice2026
Using Score Distribution Patterns to Detect Auscultation Teaching Challenges: An Empirical Study of 284 Medical Undergraduates.
Article in Advances in medical education and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Auscultation is a recognized challenge in teaching physical diagnosis, yet the instructional and assessment information reflected in score distribution patterns remains underexplored. Methods: In this quasi-experimental comparative study, we analyzed final auscultation exam scores of 284 medical undergraduates from two pre-existing intact classes without random assignment (Class 1: n = 136, web-based platform‑assisted; Class 2: n = 148, traditional) using normality tests, descriptive statistics, Mann‑Whitney Results: Both classes showed non‑normal distributions (p < 0.05). Class 1 had moderate negative skewness (-0.696) and leptokurtosis (0.511), indicating score clustering at the high end; Class 2 had slight negative skewness (-0.185) and platykurtosis (-0.764), reflecting greater variability (SD: 19.19 vs 14.72) and one extreme zero score. Group difference was significant (U = 7202.50, Z = -4.142, p < 0.001) with a small-to-medium effect (r = 0.246), and variances were heterogeneous (F = 14.351, p < 0.001). Conclusion: Score distribution patterns may serve as a hypothesis-generating tool for detecting potential teaching and assessment issues. Leptokurtosis might suggest insufficient test discrimination, while platykurtosis could point to instructional variability. These findings warrant further validation in diverse settings before any routine application. We recommend that educators consider such distributional analyses as an exploratory supplement to existing assessment reviews.
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