Designing faculty development to support the evaluation of resident competency in the intrinsic CanMEDS roles: practical outcomes of an assessment of program director needs
Bibliographic record
Abstract
BACKGROUND: The Royal College of Physicians and Surgeons of Canada and the College of Family Physicians of Canada mandate that faculty members demonstrate they are evaluating residents on all CanMEDS (Canadian Medical Education Directions for Specialists) roles as part of the accreditation process. Postgraduate Medical Education at the University of Ottawa initiated a 5-year project to develop and implement a comprehensive system to assess the full spectrum of CanMEDS roles. This paper presents the findings from a needs assessment with Program Directors, in order to determine how postgraduate medical faculty can be motivated and supported to evaluate residents on the intrinsic CanMEDS roles. METHODS: Semi-structured individual interviews were conducted with 60 Postgraduate Program Directors in the Faculty of Medicine. Transcribed interviews were analyzed using qualitative analysis. Once the researchers were satisfied the identified themes reflected the views of the participants, the data was assigned to categories to provide rich, detailed, and comprehensive information that would indicate what faculty need in order to effectively evaluate their residents on the intrinsic roles. RESULTS: Findings indicated faculty members need faculty development and shared point of care resources to support them with how to not only evaluate, but also teach, the intrinsic roles. Program Directors expressed the need to collaborate and share resources across departments and national specialty programs. Based on our findings, we designed and delivered workshops with companion eBooks to teach and evaluate residents at the point of care (Developing the Professional, Health Advocate and Scholar). CONCLUSIONS: Identifying stakeholder needs is essential for designing effective faculty development. By sharing resources, faculties can prevent 'reinventing the wheel' and collaborate to meet the Colleges' accreditation requirements more efficiently.
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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 | 0.084 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".