Is exam performance in anatomy influenced by teaching with prosected cadavers? An evidence‐based study
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Bibliographic record
Abstract
INTRODUCTION: Little empirical evidence substantiates the need to use cadavers to teach anatomy effectively. We investigated the effect of attendance at anatomy laboratories and cadaver use on .anatomy exam performance over a 12-year period (2006-2007 to 2018-2019) before and after a curricular change (2013-2014). MATERIALS AND METHODS: Anatomy exam performance data were collected from undergraduate files at Memorial University of Newfoundland, Canada, for 782 medical students over a 12-year period. Three groups emerged: (i) 6 years of the old curriculum using prosected specimens, N = 376; (ii) 3 years of the new curriculum using prosected specimens, N = 239; (iii) 3 years of the new curriculum using no prosected specimens, N = 240. For the 2018-2019 academic year, laboratory attendance was recorded, N = 80. RESULTS: The unplanned discontinuation of prosected specimens did not markedly impact anatomy instruction. Student performance under the new and old curricula (p = .0018) and with and without cadavers (p = .0117) is slightly, but significantly, different. Student performance is not associated with the number of missed laboratories (Spearman ρ = 0.145, p = .2). DISCUSSION: Although use of cadavers and prosected specimens continues in anatomy-wet laboratories, today's tech-savvy students want information at their fingertips 24/7. The three factors examined in this study suggest a surprisingly consistent performance on anatomy examinations despite changing conditions. Perhaps medical schools should offer as many quality resources as budgets allow, inform students of their availability and let students decide which learning methods work best for them individually, thus facilitating self-directed learning. CONCLUSION: Consistent exam performance can be achieved using a variety of teaching and learning methods.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it