Le test de concordance de script en formation initiale : avantages et inconvénients du test. Revue de la littérature
Bibliographic record
Abstract
Contexte : Le test de concordance de script (TCS) a ete developpe pour evaluer la competence a raisonner en situation d’incertitude en mesurant la capacite d’interpretation de donnees cliniques. Objectif : Fournir une synthese des avantages et inconvenients du TCS en formation initiale. Methode : Nous avons mene une revue systematique de la litterature a partir des bases de donnees Pedagogie medicale, Banque de Donnees en Sante Publique (BDSP), Science Direct, The Cochrane Library, Medline (PubMed), ERIC, Education research complete, Pascal, Psychology and behavioral sciences collection, Francis, et Academic search premier. Nous avons consulte les references bibliographiques disponibles sur le Centre de Pedagogie Appliquee aux Sciences de la Sante de la faculte de Montreal, et d’autres sur Google, Google scholar, le reseau SUDOC, et le site de la HAS. Les criteres d’inclusion etaient : TCS en formation initiale, articles medicaux originaux ayant etudie les qualites psychometriques du test et employant la methode de notation des scores combines, articles publies en langue anglaise ou francaise. Resultats : Sur les deux-cent-soixante-treize references incluses initialement, 64 ont ete retenues et analysees. Les etudes mettent en avant les qualites psychometriques du TCS et son utilisation comme outil d’evaluation formative et sommative. Il est utilise tout au long de la formation initiale des etudes medicales. Le TCS a ete compare aux outils standards d’evaluation et juge par les etudiants. Conclusion : Le TCS a montre de grandes qualites et de nombreuses possibilites. Quelques questions demeurent sur le systeme de notation et pour son utilisation en evaluation sommative. Il serait interessant d’etudier d’autres aspects du TCS, comme son impact educatif.
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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 | 0.215 | 0.645 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".