The CBVE Model—Keystone and Stimulus for Educational Transformation in Veterinary Schools
Bibliographic record
Abstract
The AAVMC CBVE (American Association of Veterinary Medical Colleges Competency-Based Veterinary Education) model was developed in three parts and published in 2018-2019, providing an evidence-based foundation for use in all aspects of veterinary curricula management from review to redesign and continuous curricular improvement. The Ohio State University College of Veterinary Medicine (OSU CVM) recently undertook a comprehensive review and complete redesign of their curriculum, incorporating all the components of the CBVE model and, in the process, developed a continuous curricular improvement system that may serve other veterinary programs making similar changes. Anchoring the CBVE model within an adapted LEAN approach for systemic change created an outcomes-aligned system for faculty to engage with for curricular development, oversight, and modification based on continuous data collection and analysis. Even though the CBVE model has been in existence for 5 years, confusion remains as to how the three parts of the model best work together and how they can be used for much more than just curriculum redesign, and programs report struggle with how to effectively implement and manage the model. We share how the CBVE model has not only driven our college's curriculum redesign, but how it has also created an opportunity to develop a foundational educational system focused on competency, continual improvement, and innovation. This emerging system for managing curricular change acts in accordance with accreditation demands for ensuring faculty ownership and provides documented evidence-based processes for any changes undertaken.
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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 | 0.003 | 0.003 |
| 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) | 0.000 | 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".