How to construct and implement script concordance tests: insights from a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Programmes of assessment should measure the various components of clinical competence. Clinical reasoning has been traditionally assessed using written tests and performance-based tests. The script concordance test (SCT) was developed to assess clinical data interpretation skills. A recent review of the literature examined the validity argument concerning the SCT. Our aim was to provide potential users with evidence-based recommendations on how to construct and implement an SCT. METHODS: A systematic review of relevant databases (MEDLINE, ERIC [Education Resources Information Centre], PsycINFO, the Research and Development Resource Base [RDRB, University of Toronto]) and Google Scholar, medical education journals and conference proceedings was conducted for references in English or French. It was supplemented by ancestry searching and by additional references provided by experts. RESULTS: The search yielded 848 references, of which 80 were analysed. Studies suggest that tests with around 100 items (25-30 cases), of which 25% are discarded after item analysis, should provide reliable scores. Panels with 10-20 members are needed to reach adequate precision in terms of estimated reliability. Panellists' responses can be analysed by checking for moderate variability among responses. Studies of alternative scoring methods are inconclusive, but the traditional scoring method is satisfactory. There is little evidence on how best to determine a pass/fail threshold for high-stakes examinations. CONCLUSIONS: Our literature search was broad and included references from medical education journals not indexed in the usual databases, conference abstracts and dissertations. There is good evidence on how to construct and implement an SCT for formative purposes or medium-stakes course evaluations. Further avenues for research include examining the impact of various aspects of SCT construction and implementation on issues such as educational impact, correlations with other assessments, and validity of pass/fail decisions, particularly for high-stakes examinations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.174 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it