Academic Performance and Student Satisfaction under Two Teaching Approaches in Neuroanatomy among Medical Students: A Quasi-Experimental Difference-in-Differences Study.
Abstract
Objective. This study aimed to evaluate differences associated with two teaching methodologies on academic performance and student evaluation of teaching quality in neuroanatomy, using physiology as a control group. Methodology. A quasi-experimental study compared two academic years (2023–2024 and 2024–2025). Neuroanatomy changed from a flipped classroom to a traditional lecture-based teaching format, while physiology remained traditional lecture-based teaching in both years. Academic performance was assessed using final grades (primary outcome), examination scores, and continuous assessment. Student evaluation of teaching quality was measured using institutional surveys and normalized to a 0–100 scale. Comparisons were performed using the Mann–Whitney U test. Difference-in-differences (DiD) analyses were conducted using linear regression models including academic year, subject, and their interaction. Results. A total of 87 neuroanatomy students and 86 physiology students were included. In neuroanatomy, final grades decreased from 4.44 ± 2.33 to 3.02 ± 2.21 (p = 0.006), with significant reductions in examination scores (p = 0.007) and continuous assessment (p < 0.001). Similar declines were observed in physiology (final grades: 6.20 ± 1.27 vs. 3.39 ± 2.98; p < 0.001). In the DiD analysis, the interaction term showed a non-significant effect (β = -1.387; 95% CI [-2.814, 0.039]; p = 0.057), suggesting that no statistically significant independent effect of teaching methodology on performance could be demonstrated after adjustment for cohort effects. In contrast, student satisfaction was higher in 2024–2025 after normalization, with DiD analyses indicating improved engagement (β = -7.17; p < 0.05) and a trend toward higher perceived clarity. Conclusions. No teaching methodology demonstrated statistically significant superiority in academic performance after adjustment for cohort effects. However, the methodology implemented in 2024–2025 was associated with higher student satisfaction, particularly in engagement. These findings suggest a dissociation between perceived and objective learning outcomes and highlight the importance of controlled designs in educational research.
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References
1. Chen F, Lui AM, Martinelli SM. A systematic review of the effectiveness of flipped classrooms in medical education. Medical Education. 2017, 51(6), 585-597. https://doi.org/10.1111/medu.13272
2. Hew KF, Lo CK. Flipped classroom improves student learning in health professions education: a meta-analysis. BMC Medical Education. 2018, 18(1), 38. https://doi.org/10.1186/s12909-018-1144-z
3. Freeman S, Eddy SL, McDonough M, Smith MK, Okoroafor N, Jordt H, Wenderoth MP. Active learning increases student performance in science, engineering, and mathematics. Psychological and Cognitive Sciences. 2014, 111(23), 8410-5. https://doi.org/10.1073/pnas.1319030111
4. Prober CG, Heath C. Lecture halls without lectures — a proposal for medical education.
New England Journal of Medicine. 2012, 366(18), 1657–1659. https://doi.org/10.1056/nejmp1202451
5. Chen KS, Monrouxe L, Lu YH, Jenq CC, Chang YJ, Chang YC, Chai PY. Academic outcomes of flipped classroom learning: a meta-analysis. Medical Education. 2018, 52(9), 910–24. https://doi.org/10.1111/medu.13616
6. O’Flaherty J, Phillips C. The use of flipped classrooms in higher education: a scoping review. The Internet and Higher Education. 2015, 25, 85–95. https://doi.org/10.1016/j.iheduc.2015.02.002
7. Uttl B, White CA, Wong Gonzalez D. Meta-analysis of faculty’s teaching effectiveness: Student evaluation of teaching ratings and student learning are not related. Studies in Educational Evaluation. 2017, 53, 22–42. https://doi.org/10.1016/j.stueduc.2016.08.007
8. Braga M, Paccagnella M, Pellizzari M. Evaluating students’ evaluations of professors. Economics of Education Review. 2014, 41, 71–88. http://dx.doi.org/10.1016/j.econedurev.2014.04.002
9. Shadish WR, Cook TD, Campbell DT. Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin; 2002. https://iaes.cgiar.org/sites/default/files/pdf/147.pdf
10. Dimick JB, Ryan AM. Methods for evaluating changes in health care policy: the difference-in-differences approach. JAMA. 2014, 312(22), 2401-2. https://doi.org/10.1001/jama.2014.16153
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