Assessing commitment to reflection: perceptions of medical students
Bibliographic record
Abstract
Background: While developing reflection skills is considered important by educators, the assessment of these skills is often associated with unintended negative consequences. In the context of a mandatory longitudinal course that aims to promote the development of reflection on professional identity, we assessed students' commitment to reflection. This study explores students' perception of this assessment by their mentor. Methods: year medical students. Thematic analysis was informed by Braun and Clarke's six-step approach. Results: We identified four main themes: 1- assessment as a motivator, 2- consequences on authenticity, 3- perception of inherent subjectivity, and 4 - relationship with the mentor. Conclusions: In the context of assessing reflection skills in future physicians, we observed that students -when assessed on the process of reflection- experienced high motivation but were ambivalent on the question of authenticity. The subjectivity of the assessment as well as the relationship with their mentor also raises questions. Nevertheless, this assessment approach for reflective skills appears to be promising in terms of limiting the negative consequences of assessment.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".