Something’s missing from my education: Using a cross sectional survey to examine the needs and interest of Canadian medical students relating to their roles as teachers and educators
Bibliographic record
Abstract
BACKGROUND: Current theory in medical education emphasizes engaging learners as educators while tailoring teaching to their learning needs. However, little is known about learners' perceptions of their proposed roles as teachers and educators. METHODS: Canadian medical students were invited to complete an English language online questionnaire structured to include: teaching experience, participation and/or awareness of teacher development at their school and awareness and/or interest in further training in medical education. The survey was developed by the Canadian Association for Medical Education (CAME) Membership Subcommittee, and distributed via the Canadian Federation of Medical Students (CFMS) email list and the CAME twitter account in March 2014. RESULTS: Of the 169 undergraduate medical student respondents, 36% (n=61) reported a lack of prior teaching experience and 45% (n=73) were unsure if their school provided teaching instruction. Overall, 91% (n=150) indicated that they planned to incorporate teaching or medical education into their future careers. CONCLUSION: While the majority of medical student respondents are expecting or planning to teach, most report not having access to adequate training through medical school. Further effort is necessary to support medical students as teachers to prepare them for increased teaching responsibilities as residents and to expose them to potential careers in medical education.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".