Student Perceptions of Veterinary Anatomy Practical Classes: A Longitudinal Study
Bibliographic record
Abstract
Using cadaveric material to teach veterinary students poses many challenges. However, little research exists on the contribution of this traditional approach to student learning. This longitudinal study aimed to investigate student perceptions of cadaver-based anatomy classes in a vertically integrated veterinary curriculum at the University of Nottingham's School of Veterinary Medicine and Science. Likert-scale statements and free-text boxes were used in a questionnaire distributed to second-year veterinary students (response rate 59%, 61/103). The same questionnaire was subsequently distributed to the same cohort 2 years later, in the students' fourth year of study (response rate 68%, 67/98). Students agreed that cadaver-based activities aid their learning, and they particularly value opportunities to develop practical skills while learning anatomy. There are few changes in perception as undergraduates progress to clinical years of teaching. Students perceive anatomy to be important, and feel that their learning has prepared them for clinical placements. This study emphasizes the importance of using cadaveric materials effectively in anatomy teaching and, in particular, using clinical skills training to enhance the anatomy curriculum.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".