Role of graduate courses in promoting educational scholarship of health care professionals.
Bibliographic record
Abstract
PROBLEM ADDRESSED: Many courses are offered to health care professionals to improve educational scholarship and scholarly teaching. The literature on the effect of such courses on promoting educational scholarship and scholarly teaching is currently suboptimal. OBJECTIVE OF PROGRAM: To evaluate scholarly productivity of health care professional learners participating in 2 graduate courses in which curricula and assignments facilitated experiential learning. PROGRAM DESCRIPTION: A retrospective analysis of course assignments and publications of learners from 2007 to 2014 was conducted. Learners' current positions were identified through Google Scholar searches, and publication of course work was identified through PubMed or EMBASE author searches. There were 137 learners, with a male to female ratio of 3:7, consisting of physicians (73%) and other health care professionals (27%). During the 7 years, 50% completed both courses, 42% only the first course, and 8% only the second course. Of the learners whose current positions could be identified, 66% worked at academic centres, 20% at community hospitals or office practices, and 5% were in senior leadership positions. Current positions were unidentifiable through public records for 9% of learners. Sixty-eight percent of learners (93 of 137) published 1050 articles in peer-reviewed journals. Twenty-six percent of learners (35 of 137) published 1 or more articles based on their course assignments, for a total of 49 peer-reviewed articles; 80% of articles were published within 3 years of completing the course. CONCLUSION: Experiential learning facilitated by curricular design and assignments coupled with mentorship stimulated scholarly publications. Educational courses should design curricula to promote scholarship in learners and evaluate their effect.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".