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| Tests adaptatifs informatisés avec le modèle de Rasch (TAI-Rasch)× | Théorie de la réponse aux items (TRI)× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1960 (Rasch model); CAT integration from 1970s onward | 1952–1968 |
| Auteur d'origine≠ | Georg Rasch (measurement model); adaptive testing formalized by Wainer, van der Linden, and others | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Type≠ | Adaptive psychometric measurement | Probabilistic measurement model |
| Source fondatrice≠ | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Alias | CAT-Rasch, Rasch-based CAT, adaptive Rasch testing, computerized adaptive measurement | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Apparentées | 5 | 5 |
| Résumé≠ | Computerized adaptive testing with the Rasch model selects items in real time based on each examinee's evolving ability estimate, so that every person receives a test precisely calibrated to their proficiency level. The result is a shorter, more efficient measurement instrument that loses none of the precision of a full-length fixed-form test. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
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