Levels of Continuing Veterinary Medical Education Program Evaluation: Assessing a Course on Dairy Reproductive Management
Bibliographic record
Abstract
There are four different levels of continuing education program evaluation: participant perceptions of the program or course; participant competence with new skills, knowledge, and abilities; participant performance or change in behavior; and health care or client outcomes, such as resultant changes in patient care or herd/flock production performance. The purpose of this article is to describe different levels of evaluation and demonstrate some methods used in evaluating a continuing veterinary medical education (CVME) course in dairy reproductive management. Participants' learning needs were assessed using learning stage theory and a pre-test of knowledge. Post-program assessments included a test of knowledge, a satisfaction survey, a commitment to change, and self-reported behavior change. The results of the evaluation indicate that self-reports of learning needs do not necessarily reflect actual needs and that satisfaction with a course does not necessarily indicate behavior change. Providers of CVME must recognize the value of program evaluation, as well as the advantages and disadvantages of different evaluation methods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".