Straight from the Horse's Mouth: Using Vignettes to Support Student Learning in Veterinary Ethics
Bibliographic record
Abstract
In the last few decades, the importance of imparting ethical competences to veterinary students has been increasingly acknowledged. Despite its relevance, there are few published descriptions of teaching approaches to veterinary ethics and their effect on student learning. At University College Dublin, veterinary ethics is part of a core module on animal behavior and welfare in the pre-clinical teaching program. The present study describes the implementation of a student-centered, skills-based approach to veterinary ethics teaching using vignettes (i.e., case scenarios). Vignettes were inspired by several resources, including a focus group, and designed to represent significant ethical challenges faced by veterinary professionals in Ireland in addition to cases of potential professional misconduct. In small groups, students had to identify the stakeholders and their conflicting interests and to suggest possible solutions and alternative outcomes to the case scenario. Results from qualitative material from the teaching sessions and from a quantitative post-teaching survey show that student understanding of stakeholders increased as a result of the tutorial, which helped them to clarify possible solutions to the scenario and to propose alternative outcomes to either mitigate or avoid future occurrence of the ethical challenges. These findings suggest that incorporating meaningful vignettes into the teaching of veterinary ethics can support student ethical awareness and skills, while promoting a pluralistic approach to considering ethical issues, making the best of available time and human resources.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".