Validation of the 25-Item Stanford Faculty Development Program Tool on Clinical Teaching Effectiveness
Bibliographic record
Abstract
UNLABELLED: CONSTRUCT: The 25-item Stanford Faculty Development Program Tool on Clinical Teaching Effectiveness assesses clinical teaching effectiveness. BACKGROUND: Valid and reliable rating of teaching effectiveness is helpful for providing faculty with feedback. The 25-item Stanford Faculty Development Program Tool on Clinical Teaching Effectiveness was intended to evaluate seven dimensions of clinical teaching. Confirmation of the structure of this tool has not been previously performed. APPROACH: This study sought to validate this tool using a confirmatory factor analysis, testing a 7-factor model and compared its goodness of fit with a modified model. Acceptability of the use of the tool was assessed using a 6-item survey, completed by final year medical students (N = 119 of 156 students; 76%). RESULTS: The testing of the goodness of fit indicated that the 7-factor model performed poorly, χ(2)(254) = 457.4, p < .001 (root mean square error of approximation [RMSEA] = 0.08, comparative fit index [CFI] = 0.91, non-normed fit index [NNFI] = 0.89). Only standardized root mean square residual (SRMR) indicated acceptable fit (0.06). Further exploratory analysis identified 10 items that cross-loaded on 2 factors. The remainder of the items loaded on factors as originally intended. By removing these 10 items, repeat confirmatory factor analysis on the modified 15-item, 5-factor model demonstrated a better fit than the original model: SRMR = 0.075, NNFI = 0.91, χ(2)(80) = 150.1, p < .001; RMSEA = 0.09; CFI = 0.93. Although 75% of the participants stated they were willing to fill the tool on their preceptors on a biweekly basis, only 25% were willing to do so on a weekly basis. CONCLUSIONS: Our study failed to confirm factor structure of the 25-item tool. A modified tool with fewer, more conceptually distinct items was best fit by a 5-factor model. Further, the acceptability of use for the 25-item tool may be poor for rotations with a new preceptor weekly. The abbreviated tool may be preferable in that setting.
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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 | 0.024 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".