How workplace‐based assessments guide learning in postgraduate education: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Competency-based medical education (CBME) led to the widespread adoption of workplace-based assessment (WBA) with the promise of achieving assessment for learning. Despite this, studies have illustrated tensions between the summative and formative role of WBA which undermine learning goals. Models of workplace-based learning (WBL) provide insight, however, these models excluded WBA. This scoping review synthesizes the primary literature addressing the role of WBA to guide learning in postgraduate medical education, with the goal of identifying gaps to address in future studies. METHODS: The search was applied to OVID Medline, Web of Science, ERIC and CINAHL databases, articles up to September 2020 were included. Titles and abstracts were screened by two reviewers, followed by a full text review. Two members independently extracted and analysed quantitative and qualitative data using a descriptive-analytic technique rooted in Billett's four premises of WBL. Themes were synthesized and discussed until consensus. RESULTS: All 33 papers focused on the perception of learning through WBA. The majority applied qualitative methodology (70%), and 12 studies (36%) made explicit reference to theory. Aligning with Billett's first premise, results reinforce that learning always occurs in the workplace. WBA helped guide learning goals and enhanced feedback frequency and specificity. Billett's remaining premises provided an important lens to understand how tensions that existed in WBL have been exacerbated with frequent WBA. As individuals engage in both work and WBA, they are slowly transforming the workplace. Culture and context frame individual experiences and the perceived authenticity of WBA. Finally, individuals will have different goals, and learn different things, from the same experience. CONCLUSION: Analysing WBA literature through the lens of WBL theory allows us to reframe previously described tensions. We propose that future studies attend to learning theory, and demonstrate alignment with philosophical position, to advance our understanding of assessment-for-learning in the workplace.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.004 | 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".