Creating a Pedagogical Development Program for Veterinary Clinical Teachers: A Discipline-Specific, Context-Relevant, Bottom-Up Initiative
Bibliographic record
Abstract
At veterinary university hospitals, clinical teachers have two responsibilities: treating patients and teaching students. At the University of Copenhagen, many teachers are involved in the clinical teaching and assessment of veterinary students, but only some of these teachers-the academic faculty-have access to pedagogical training. We conceived an idea to develop a pedagogical program aimed specifically at clinical teachers. However, instead of implementing an existing program developed elsewhere, we decided to create a discipline-specific, context-relevant program. The creational process applied the principles of action learning consulting (ALC), which dictate that a pedagogical consultant and key involved employees cooperate closely in a dynamic, creational process. A program was developed with content focused on addressing the perceived needs expressed by the clinical teachers. The program consisted of three 2.5-hour seminars, each covering one of the main themes: teaching situations in clinical settings, pedagogical psychology in clinical teaching, and assessment and feedback. The seminars were conducted in the afternoon approximately 2 months apart and were facilitated by the two authors with a veterinary background (CBM, RL). Ten to 20 clinical teachers participated in each seminar, and feedback from participants was positive overall, acknowledging the creation of a forum for critical discussions on clinical teaching and learning and greater insight into pedagogical themes. As a result of the application of the ALC principle, the program is highly context relevant and has gained optimal anchorage within the organization; the seminars will therefore be repeated and allowed to continuously evolve.
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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 | 0.019 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".