The development of an instrument to assess clinical teaching with linkage to CanMEDS roles: A psychometric analysis
Bibliographic record
Abstract
BACKGROUND: Assessment of clinical teaching by learners is of value to teachers, department heads, and program directors, and must be comprehensive and feasible. AIMS: To review published evaluation instruments with psychometric evaluations and to develop and psychometrically evaluate an instrument for assessing clinical teaching with linkages to the CanMEDS roles. METHOD: We developed a 19-item questionnaire to reflect 10 domains relevant to teaching and the CanMEDS roles. A total of 317 medical learners assessed 170 instructors. Fourteen (4.4 %) clinical clerks, 229 (72.3%) residents, and 53 (16.7%) fellows assessed 170 instructors. Twenty-one (6.6%) did not specify their position. RESULTS: A mean number of eight raters assessed each instructor. The internal consistency reliability of the 19-item instrument was Cronbach's α = 0.95. The generalizability coefficient (Ep(2)) analysis indicated that the raters achieved Ep(2) of 0.95. The factor analysis showed three factors that accounted for 67.97% of the total variance. The three factors together, with the variance accounted for and their internal consistency reliability, are teaching skills (variance = 53.25s%; Cronbach's α = 0.92), Patient interaction (variance = 8.56%; Cronbach's α = 0.91), and professionalism (variance = 6.16%; Cronbach's α = 0.86). The three factors are intercorrelated (correlations = 0.48, 0.58, 0.46; p < 0.01). CONCLUSION: It is feasible to assess clinical teaching with the 19-item instrument that has demonstrated evidence of both validity and reliability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".