A Comparison of Standard-setting Procedures for an OSCE in Undergraduate Medical Education
Bibliographic record
Abstract
PURPOSE: To compare four standard-setting procedures for an objective structure clinical examination (OSCE). METHODS: A 12-station OSCE was administered to 84 students in each of the final (fourth-) year medical classes of 1996 and 1997 at Dalhousie University Faculty of Medicine. Four standard-setting procedures (Angoff, borderline, relative, and holistic) were applied to the data to establish a cutoff score for a pass/fail decision. RESULTS: The procedures yielded highly inconsistent results. The Angoff and borderline procedures gave similar results; however, the relative and holistic methods gave widely divergent results. The Angoff procedure yielded results reliable enough to use in decision making for a high-stakes examination, but would have required more judges or more stations. CONCLUSIONS: The Angoff and borderline procedures provide reasonable and defensible approaches to standard setting and are practical to apply by non-psychometricians in medical schools. Further investigation of the other procedures is needed.
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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 | 0.056 | 0.238 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".