Evaluation of the “Resident as teacher” curriculum: a needs assessment in medical education at a large academic institution
Bibliographic record
Abstract
<ns3:p>Introduction Strong skills in teaching for residents contribute to increased satisfaction and improved student interest. Few opportunities in medical education are offered at the junior resident level. We aim to evaluate the needs of residents in teaching at Université de Montréal Methods A 19 question survey created after a literature review was sent to all 769 current PGY1 to PGY3 residents at UdeM to assess their interest and needs in various aspects of clinical teaching. Descriptive statistics were analyzed to make recommendations for improvements in medical education training. Results We received 65 completed surveys (8.5% response rate), mostly in family and internal medicine. Eighty percent of participants were interested in further training in teaching and 58% were interested in a medical education elective. Main skills to be improved are indirect supervision and adapting feedback to different learners. Lack of time was considered by most responders (89%) as the main factor limiting participation in further training. Narrative comments noted the lack of information on medical education resources and lack of recognition by faculty compared to clinical performance or research, particularly in family medicine. Conclusion Protected time for varied medical education activities is needed, including better offers for an elective rotation. Information on currently available resources should be more widely circulated. Promoting and recognizing teaching and reserving time for direct supervision by faculty of teaching by junior residents should be encouraged.</ns3:p>
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".