Effect of field notes on confidence and perceived competence: survey of faculty and residents.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of field notes in assessing teachers' confidence and perceived competence, and the effect of field notes on residents' perceptions of their development of competence. DESIGN: A faculty and resident survey completed 5 years after field notes were introduced into the program. SETTING: Five Dalhousie University family medicine sites--Fredericton, Moncton, and Saint John in New Brunswick, and Halifax and Sydney in Nova Scotia. PARTICIPANTS: First- and second-year family medicine residents (as of May 2009) and core family medicine faculty. MAIN OUTCOME MEASURES: Residents' outcome measures included beliefs about the effects of field notes on performance, learning, reflection, clinical skills development, and feedback received. Faculty outcome measures included beliefs about the effect of field notes on guiding feedback, teaching, and reflection on clinical practice. RESULTS: Forty of 88 residents (45.5%) participated. Fifteen of 50 faculty (30.0%) participated, which only permitted a discussion of trends for faculty. Residents believed field note-directed feedback reinforced their performance (81.1%), helped them learn (67.6%), helped them reflect on practice and learning (66.7%), and focused the feedback they received, making it more useful (62.2%) (P < .001 for all); 63.3% believed field note-directed feedback helped with clinical skills development (P < .01). Faculty believed field notes helped to provide more focused (86.7%) and effective feedback (78.6%), improved teaching (75.0%), and encouraged reflection on their own clinical practice (73.3%). CONCLUSION: Most surveyed residents believed field note use improved the feedback they received and helped them to develop competence through improved performance, learning, reflection, and clinical skills development. The trends from faculty information suggested faculty believed field notes were an effective teaching, feedback, and reflection tool.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".