Competency based medical education implementation at the institutional level: A cross-discipline comparative program evaluation
Bibliographic record
Abstract
INTRODUCTION: As an early adopter of competency-based medical education (CBME) our postgraduate institution was uniquely positioned to analyze implementation experience data across programs, while keeping institutional factors constant. We described participants' experiences related to CBME implementation across programs derived from early program evaluation efforts within our setting. METHODS: = 175) included program leaders, faculty, and residents. The study consisted of 3 phases: (1) describing intended implementation; (2) documenting enacted implementation; and (3) comparing intended with enacted implementation to inform adaptations. Each program's findings were summarized in technical reports which were then analyzed thematically. Cross program data were organized by themes. RESULTS: Six themes were identified. All groups emphasized the need for ongoing refinement of CBME resulting from shared tensions such as increased assessment burden. However, there were some disparate CBME-related experiences between programs such as the experience with entrustable professional activities, the interpretation of retrospective entrustment anchors, and quality of feedback. CONCLUSION: We detected several cross-program successes and important challenges related to CBME. Our experience can inform other programs engaging in implementation and evaluation of CBME.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 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".