MedTalks: developing teaching abilities and experience in undergraduate medical students
Bibliographic record
Abstract
OBJECTIVES: According to the CanMEDS' Scholar competency, physicians are expected to facilitate the learning of colleagues, patients and other health professionals. However, most medical students are not provided with formal opportunities to gain teaching experience with objective feedback. METHODS: To address this, the University's Medical Education Interest Group (MEIG) created a pilot teaching program in January 2015 entitled 'MedTalks'. Four 3-hour sessions were held at the University Faculty of Medicine, where first and second year medical students taught clinically oriented topics to undergraduate university students. Each extracurricular session included three 30-minute content lectures, and a 90-minute small group session on physical examination skills. Each medical student-teacher received formal feedback from undergraduate students and from faculty educators regarding teaching style, communication abilities, and professionalism. In addition, medical student-teachers self-evaluated their own teaching experience. RESULTS: Over 50 medical students from the University participated as medical student-teachers. Based on quantitative and qualitative evaluation surveys, 100% of medical students agreed that MedTalks was a useful way to develop teaching skills and 92% gained a greater confidence in individual teaching capabilities, based largely on the opportunity to gain experience (with feedback) in teaching roles. CONCLUSIONS: A program designed to give medical students multi-source teaching experience (lecture- and small group-based) and feedback on their teaching (from learners and Faculty observers, in addition to their own self-reflection) can improve medical student confidence and enthusiasm towards teaching. Future studies will clarify if medical student self-perceived enhancements in teaching ability can be corroborated by independent (Faculty, learner) observations of future teaching activity.
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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 | 0.002 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".