Development and implementation of a longitudinal students as teachers program: participant satisfaction and implications for medical student teaching and learning
Bibliographic record
Abstract
BACKGROUND: Teaching is a key component of medical practice, but medical students receive little formal training to develop their teaching skills. A longitudinal Students as Teachers (SAT) program was created at the University of Toronto to provide medical students with opportunities to acquire an understanding of educational pedagogy and practice teaching early in their medical training. This program was 7-months in duration and consisted of monthly educational modules, practical teaching sessions, feedback, and reflective exercises. METHODS: A mixed methods study design was used to evaluate initial outcomes of the SAT program by obtaining the perspectives of 18 second-year medical students. Participants filled out questionnaires at the beginning and end of the 7-month program to indicate their skill level and confidence in teaching. Differences between pre- and post-intervention scores were further explored in a group interview of 5 participants. RESULTS: Participants expressed a high degree of satisfaction with the SAT program structure and found the educational modules and practical teaching sessions to be particularly beneficial to their learning. Over the course of the program, there were significant increases in students' confidence in teaching, and self-perceived teaching capacity and communication skills. Furthermore, participants discussed improvements in their effectiveness as learners. CONCLUSIONS: Teaching is a skill that requires ongoing practice. Our results suggest that a longitudinal program consisting of theoretical modules, practical teaching sessions, feedback, and reflective exercises for medical students may improve teaching and communication skills, and equip them with improved learning strategies. This program also provides students with insight into the experience of teaching while holding other academic and clinical responsibilities.
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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 | 0.010 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".