Veterinary Medical Students' Retention of and Attitudes Toward the Biomedical Sciences: A Comparison Between Students in the Legacy and in the New Integrated Curriculum
Bibliographic record
Abstract
Most North American veterinary schools have undergone, are currently engaged in, or plan to redesign their curriculum. In 2022, the University of Pennsylvania School of Veterinary Medicine launched a new pre-clinical curriculum with an integrated systems framework. Similar to human undergraduate medical training, there are concerns about the impact of shifting from discipline-based biomedical education to integrated coursework on student learning. This study investigates the performance in and attitudes toward the biomedical sciences of students enrolled in the legacy and redesigned curricula as the transition occurred. Biomedical science retention was assessed by comparing the performance of students in the legacy curriculum (LC) and new curriculum (NC) on the standardized Veterinary Educational Assessment examination. In the subcomponent analysis, the LC students performed significantly better than the NC students in pharmacology and pathology ( p ≤ .01) but not in anatomy, physiology, or microbiology. Survey results and open text responses provided insight into students’ perceptions of the relevance and effectiveness of their pre-clinical educational experience. NC students responded significantly more favorably than LC students did to four of eight survey questions related to the perceived effectiveness of the biomedical education they received and its importance for their future veterinary careers ( p < .01). Qualitative analysis of two open text responses demonstrated shared themes between the cohorts. This study, as part of program evaluation of the new curriculum, identified possible areas for improvement and refinement in the pre-clinical curriculum and revealed that students in the NC had more favorable attitudes toward the biomedical sciences.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".