Creating an Authentic Small Animal Primary Care Experience Using Online Simulated Appointments
Bibliographic record
Abstract
Clinical clerkships have long been a pillar of veterinary medical education. These experiences provide students a unique opportunity to apply skills learned in pre-clinical training through hands-on practice. However, the emergence of the novel coronavirus, SARS-CoV-2, and the subsequent global pandemic of 2020 forced many clinical instructors to adapt to teaching online. This teaching tip describes the use of backward design to create a three-part online clinical learning environment for the delivery of small animal primary care consisting of synchronous rounds, simulated online appointments, and independent learning activities. Results of a survey of students' perspectives on the experience demonstrate that the majority of students found that the online clinical experience met or exceeded expectations and provided a meaningful learning experience. Recommendations based on student feedback and instructor reflection are provided to guide creation and implementation of future online clinical courses. As the field of telemedicine grows, we view incorporation of such learning environments into veterinary medical education curriculum as essential to preparing students to enter the modern veterinary workplace.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".