Efficacy of an Antimicrobial Reality Simulator (AMRSim) as an Educational Tool for Teaching Antimicrobial Stewardship to Veterinary Medicine Undergraduates
Bibliographic record
Abstract
PURPOSE: Simulation-based medical education has changed the teaching of clinical practice skills, with scenario-based simulations being particularly effective in supporting learning in veterinary medicine. In this study, we explore the efficacy of simulation education to teach infection prevention and control (IPC) as part of Antimicrobial Stewardship (AMS) teaching for early years clinical veterinary medicine undergraduates. METHODS: The intervention was designed as a 30-minute workshop with a simulation and script delivered online for 130 students as a part of hybrid teaching within the undergraduate curriculum. Learning outcome measures were compared between an intervention group and waitlist-control group using one-way between-groups analysis of covariance tests. RESULTS: Significant differences between groups were found for outcome measures related to short-term knowledge gain and confidence in IPC and AMS in small animal clinical practice. However, lateral knowledge transfer to large animal species clinical practice showed no significant differences. Student feedback indicated that the intervention was an enjoyable and engaging way to learn AMS. CONCLUSIONS: The intervention provided short-term knowledge gain in IPC protocols and enhanced procedural skills via active learning and motivation to learn in large groups of students. Future improvements would be to include large animal clinical scenario discussions and evaluate longer-term knowledge gain.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".