Validity evidence for summative performance evaluations in postgraduate community pharmacy education
Bibliographic record
Abstract
INTRODUCTION: Workplace-based assessment of competencies is complex. In this study, the validity of summative performance evaluations (SPEs) made by supervisors in a two-year longitudinal supervisor-trainee relationship was investigated in a postgraduate community pharmacy specialization program in the Netherlands. The construct of competence was based on an adapted version of the 2005 Canadian Medical Education Directive for Specialists (CanMEDS) framework. METHODS: The study had a case study design. Both quantitative and qualitative data were collected. The year 1 and year 2 SPE scores of 342 trainees were analyzed using confirmatory factor analysis and generalizability theory. Semi-structured interviews were held with 15 supervisors and the program director to analyze the inferences they made and the impact of SPE scores on the decision-making process. RESULTS: A good model fit was found for the adapted CanMEDS based seven-factor construct. The reliability/precision of the SPE measurements could not be completely isolated, as every trainee was trained in one pharmacy and evaluated by one supervisor. Qualitative analysis revealed that supervisors varied in their standards for scoring competencies. Some supervisors were reluctant to fail trainees. The competency scores had little impact on the high-stakes decision made by the program director. CONCLUSIONS: The adapted CanMEDS competency framework provided a valid structure to measure competence. The reliability/precision of SPE measurements could not be established and the SPE measurements provided limited input for the decision-making process. Indications of a shadow assessment system in the pharmacies need further investigation.
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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 | 0.198 | 0.573 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier 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".