Workplace‐based assessments in postgraduate medical education: A hermeneutic review
Bibliographic record
Abstract
OBJECTIVES: Since their introduction, workplace-based assessments (WBAs) have proliferated throughout postgraduate medical education. Previous reviews have identified mixed findings regarding WBAs' effectiveness, but have not considered the importance of user-tool-context interactions. The present review was conducted to address this gap by generating a thematic overview of factors important to the acceptability, effectiveness and utility of WBAs in postgraduate medical education. METHOD: This review utilised a hermeneutic cycle for analysis of the literature. Four databases were searched to identify articles pertaining to WBAs in postgraduate medical education from the United Kingdom, Canada, Australia, New Zealand, the Netherlands and Scandinavian countries. Over the course of three rounds, 30 published articles were thematically analysed in an iterative fashion to deeply engage with the literature in order to answer three scoping questions concerning acceptability, effectiveness and assessment training. As each round was coded, themes were refined and questions added until saturation was reached. RESULTS: Stakeholders value WBAs for permitting assessment of trainees' performance in an authentic context. Negative perceptions of WBAs stem from misuse due to low assessment literacy, disagreement with definitions and frameworks, and inadequate summative use of WBAs. Effectiveness is influenced by user (eg, engagement and assessment literacy) and tool attributes (eg, definitions and scales), but most fundamentally by user-tool-context interactions, particularly trainee-assessor relationships. Assessors' assessment literacy must be combined with cultural and administrative factors in organisations and the broader medical discipline. CONCLUSIONS: The pivotal determinants of WBAs' effectiveness and utility are the user-tool-context interactions. From the identified themes, we present 12 lessons learned regarding users, tools and contexts to maximise WBA utility, including the separation of formative and summative WBA assessors, use of maximally useful scales, and instituting measures to reduce competitive demands.
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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 | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".