The Effects of Deliberate Practice in Open Access Sessions on Veterinary Students' Confidence and Performance of Large Animal Clinical Skills
Bibliographic record
Abstract
Veterinary education demands high levels of competence in clinical skills, including in large animal practice, yet many students struggle with both performance and confidence. This study investigates the effects of deliberate practice strategies on the confidence and competence of veterinary students enrolled in large animal medicine and surgery courses at City University of Hong Kong. In our prospective cohort study, 22 fifth-year veterinary students participated in Open Access practice sessions, engaging in self-directed learning supplemented with feedback from clinical educators. Data were collected through a series of questionnaires assessing self-reported confidence levels, practice strategies and practice frequency. Students' Objective Structured Clinical Examination (OSCE) results were also analyzed. Our findings show that a higher deliberate practice score predicted better objective performance in large animal skills. However, confidence levels did not consistently correlate with performance. Interestingly, while practice increased confidence after a session, students who passed experienced a smaller confidence boost compared to their peers who failed. This suggests a complex relationship between practice frequency, confidence, and objective performance. Our results highlight the effectiveness of deliberate practice in enhancing veterinary students' competencies in large animal skills. By focusing on structured, goal-oriented practice, this study aims to inform curriculum development regarding strategies that would improve student preparedness for clinical practice in large animal medicine.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".