An Exploratory Study of the Impact of COVID-19 Pandemic Disruptions on Veterinary Medical Education
Bibliographic record
Abstract
The COVID-19 outbreak forced educators worldwide to transition to remote teaching, which caught most of the instructors and students off-guard. Instructors had to quickly adapt and find effective substitute teaching methods during this unprecedented period, while students had to maintain motivation and engagement in the learning process. As with all educational levels and disciplines, teaching and assessment in veterinary medicine were forced to change during this adjustment period. The biggest concern regarding educational experiences was potential learning loss caused by the disruption. This study examined whether COVID-19 pandemic disruptions negatively impacted veterinary students' knowledge and skill acquisition in both basic science education, and clinical science education employing a quasi-experimental approach. Data sources included the results from standardized exams including Veterinary Educational Assessment (VEA), the North American Veterinary Licensing Examination (NAVLE), Objective Structured Clinical Examinations (OSCEs), and surveys (i.e., Senior Exit Survey, Alumni Survey, and the Employer Survey). Analysis of variance was computed to compare pre-COVID results with those attained during and after pandemic restrictions. The results indicated no statistically significant difference in student performance on standardized exams, but a significant drop in the mean scores for OSCEs. Students whose education was disrupted by COVID-19 pandemic restrictions were as much satisfied with the education they received as their peers whose education was not disrupted. Conclusions are discussed and recommendations for further research are provided.
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How this classification was reachedexpand
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".