<scp>Students‐As‐Teachers</scp> : Fostering medical educators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: While mounting evidence supports various benefits of Students-As-Teachers (SAT) curricula in preparing students to teach, limited SAT electives are offered across Canada. We developed a 4-week SAT selective for fourth-year medical students at the University of Toronto to enhance medical education knowledge and teaching skills. This study aimed to evaluate the SAT programme and its impact on students' development as educators, their experience as learners and educators, and their future plans for involvement with medical education. APPROACH: Students participated in highly interactive small group seminars and teaching opportunities in nonclinical and clinical environments. Course evaluation consisted of pre-selective and post-selective surveys and written reflections on the selective experience and future career aspirations. A theory-based evaluation approach was utilized to compare the SAT programme's theory with course outcomes. EVALUATION: Post-SAT selective, students self-reported greater knowledge and confidence in teaching methods, provision of feedback, medical education scholarship, and interest in further medical education training. Student reflections highlighted three key themes. Identity formation as educators and the importance of mentorship in medical education aligned with our programme theory, while an unexpected outcome included a shifting perception on teaching and feedback from a learner to an educator lens. IMPLICATIONS: This study's findings demonstrate the ability of SAT curricula to build capacity for future medical educators. Positive factors contributing to the programme's outcomes included cohort size, course and seminar structure, and active group participation. Future iterations may explore use of flipped classroom models, additional clinical teaching opportunities, and near-peer teaching.
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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 | 0.009 | 0.017 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it