Learning behaviour and preferences of family medicine residents under a flexible academic curriculum.
Bibliographic record
Abstract
OBJECTIVE: To determine family medicine residents' learning behaviour and preferences outside of clinical settings in order to help guide the development of an effective academic program that can maximize their learning. DESIGN: Retrospective descriptive analysis of academic learning logs submitted by residents as part of their academic training requirements between 2008 and 2011. SETTING: London, Ont. PARTICIPANTS: All family medicine residents at Western University who had completed their academic program requirements (N = 72) by submitting 300 or more credits (1 credit = 1 hour). MAIN OUTCOME MEASURES: Amount of time spent on various learning modalities, location where the learning took place, resources used for self-study, and the objective of the learning activity. RESULTS: A total of 72 residents completed their academic requirements during the study period and logged a total of 25 068 hours of academic learning. Residents chose to spend most of their academic time engaging in self-study (44%), attending staff physicians' teaching sessions (20%),and participating in conferences, courses, or workshops (12%) and in postgraduate medical education sessions (12%). Textbooks (26%), medical journals (20%), and point-of-care resources (12%) were the 3 most common resources used for self-study. The hospital (32%), residents' homes (32%),and family medicine clinics (14%) were the most frequently cited locations where academic learning occurred. While all physicians used a variety of educational activities, most residents (67%) chose self-study as their primary method of learning. The topic for academic learning appeared to have some influence on the learning modalities used by residents. CONCLUSION: Residents used a variety of learning modalities and chose self-study over other more traditional modalities (eg, lectures) for most of their academic learning. A successful academic program must take into account residents' various learning preferences and habits while providing guidance and training in the use of more effective learning methods and resources to maximize educational outcomes.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".