Faculty Development- Is Some Better Than None?
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. Introduction: With the advent of competency-based medical education there is an emphasis on formative workplace based assessment. The quality of these assessments is a concern for medical educators and their trainees. Faculty development (FD) strategies to improve assessment quality have resulted in some success. However, few faculty participate, and those who do are likely more motivated to improve, making it difficult to demonstrate a conclusive benefit. To address these weaknesses, we designed a FD initiative to improve the quality of completed in-training evaluation reports (ITERs). All faculty within a division participated. We hypothesized that clinical supervisors would improve their ITER quality based on feedback, regardless of their own motivation to do so, with a simple, point-in-time intervention. Methods: In this three-phase study, two independent raters used the Completed Clinical Evaluation Report Rating (CCERR) to assess the quality of ITERs completed by all faculty in the Division of Orthopedic Surgery at the University of Ottawa. In phase one, ITERs from the previous nine months were evaluated. In phase two, the participants were aware that their ITERs were being evaluated, but they did not receive feedback. In phase three, participants received regular feedback on their performance in the form of their mean CCERR scores. Mean CCERR scores from the different phases of the study were compared. Results: CCERR scores were similar for all three phases (one: 17.56 ± 1.02, two: 17.65 ± 0.96, three: 17.54 ± 0.75, p=0.98). Discussion and Conclusions: There was no evidence in our study that participants' improved their ITER quality despite being aware that they were being evaluated and/or receiving feedback. Potentially, this was related to a lack of motivation. Alternatively, the intensity and/or frequency of the feedback may have been inadequate to create change. These results raise concerns that some faculty development may not necessarily be better than none.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.059 | 0.018 |
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".