Bibliographic record
Abstract
INTRODUCTION: This study was undertaken to evaluate the influence of a continuing education course in facilitating the development and implementation of educational projects of course participants. METHODS: This is a case study evaluating a full-year course that consisted of 11 monthly seminars, each 4 hours in length, including practice in a computer laboratory. The class size was limited to 12 participants. Needs-assessment surveys at the beginning of the course, student evaluations, and midterm and final progress reports were analyzed. RESULTS: Seven staff physicians, 3 clinical fellows, a nurse educator, and a research assistant enrolled in the course. Initial needs-assessment surveys indicated that most people had adequate computer skills-11 (90%)-but only 2 (17%) were able to type well, 11 (90%) had no statistical knowledge, and 10 (83%) had limited literature-searching skills. The mean score on speaker evaluations for lectures was 4.5 on a scoring scheme of 1-5 where 1 was poor and 5 was outstanding. Ten participants (83%) had a complete proposal for an educational project written by midterm. Nine participants applied for external grants and 2 of them received external funding for their projects. Five participants (42%) completed a publishable educational project by the end of the 11-month course, and submitted it for presentation at scientific meetings. DISCUSSION: Like many adults, health care professionals experience limited time for involvement in formal education. This study shows that a limited-time-commitment course could facilitate health care professionals to develop and successfully implement educational projects translating ideas into action.
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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 | 0.040 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.005 | 0.030 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.074 | 0.017 |
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".