Novel Board Game versus Active Case-Based Discussion to Teach Final-Year Veterinary Students the Diagnostic Approach to Clinical Cases
Why this work is in the frame
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Bibliographic record
Abstract
Traditional lectures, where students listen passively, often do not reflect the complexity of real-life decision-making situations. Furthermore, modern students are using online devices for daily activities, and this has a challenging side effect for educators, as many people these days can only maintain their focus if topics are discussed in concise and engaging ways. For these reasons, there is growing interest in the use of games for educational purposes. The aim of this study was to introduce a board game based on the Clue game for final-year veterinary students during their practical activity in large animal medicine. This type of learning process was compared with a classical case-based discussion and evaluated via a survey delivered to the students to both test their acquired knowledge and obtain their evaluation of the activity. A total of 49 students were enrolled in this study. While the board game was evaluated as being significatively better than the traditional class, no statistically significant differences were observed for the answers given to questions assessing their veterinary skills. The proposed game requires few resources other than a case-based visual materials and analyses from clinical patients, a board, two dice, and some imagination to create cases at the appropriate level for students' knowledge. We conclude that this board game-based activity represents innovative techniques to teach clinical approaches in an interactive way with the same utility as a traditional class but is more enjoyable for the students.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it