Evaluation of an Immersive Farm Experience to Teach and Attract Veterinary Students to Food-Animal Medicine
Bibliographic record
Abstract
The Bovine Educational Symposium (BES) is a unique opportunity for North Carolina State University (NCSU) veterinary students to visit dairy farms, feedlots, cow-calf operations, and processing facilities, and to meet local bovine veterinarians. We hypothesized that this active learning opportunity would increase knowledge, change perceptions of animal agriculture and food-animal medicine, and provide skills that persist beyond graduation. Pre- and post-trip surveys were administered to 124 first-, second-, and third-year veterinary students attending BES over 3 years. The surveys assessed students' perceived competence with regard to 12 key areas of bovine practice, attitudes toward segments of the cattle industry, attitudes to veterinarians' role in these segments, and interest in a career in bovine practice. Content knowledge was assessed using a multiple-choice test for comparison to self-assessments. A control group of 10 fourth-year students was administered the same tests before and after a 2-week food-animal clinical rotation. A convenience sample of nine BES alumni were interviewed to assess their opinion on the educational impact of BES. BES participants exhibited significant gains in perceived competence and actual knowledge in all 12 areas, and they also had improved perceptions of animal agriculture and increased interest in food-animal careers. Benefits noted by alumni ranged from improved knowledge of basic concepts of biosecurity and population medicine to greater appreciation for professional skills, including client communication. Immersing pre-clinical veterinary students in an active learning environment can have a significant impact on their knowledge and perception of food-animal medicine, irrespective of students' ultimate career goals.
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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 | 0.007 | 0.011 |
| 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 | 0.001 | 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".