What do we do? Practices and learning strategies of medical education leaders
Bibliographic record
Abstract
BACKGROUND: Continuous changes in undergraduate and postgraduate medical education require faculty to assume a variety of new leadership roles. While numerous faculty development programmes have been developed, there is little evidence about the specific practices of medical education leaders or their learning strategies to help inform their design. AIM: This study aimed to explore what medical education leaders' actually do, their learning strategies and recommendations for faculty development. METHOD: A total of 16 medical education leaders from a variety of contexts within the faculty of medicine of a large North American medical school participated in semi-structured interviews to explore the nature of their work and the learning strategies they employ. Using thematic analysis, interview transcripts were coded inductively and then clustered into emergent themes. RESULTS: Findings clustered into four key themes of practice: (1) intrapersonal (e.g., self-awareness), (2) interpersonal (e.g., fostering informal networks), (3) organizational (e.g., creating a shared vision) and (4) systemic (e.g. strategic navigation). Learning strategies employed included learning from experience and example, reflective practice, strategic mentoring or advanced training. CONCLUSIONS: Our findings illuminate a four-domain framework for understanding medical education leader practices and their learning preferences. While some of these findings are not unknown in the general leadership literature, our understanding of their application in medical education is unique. These practices and preferences have a potential utility for conceptualizing a coherent and relevant approach to the design of faculty development strategies for medical education leadership.
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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 | 0.004 | 0.020 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".