Comparer des méthodes

	Computerized adaptive test item response theory	Théorie de la réponse aux items (TRI)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1970s–1980s	1952–1968
Auteur d'origine	Lord, F. M.; further developed by Wainer, van der Linden, and others	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Type	Adaptive measurement / sequential testing	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.
Alias	CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing	IRT, latent trait theory, item characteristic curve theory, modern test theory
Apparentées	4	5
Résumé	Computerized adaptive testing based on item response theory is a sequential measurement procedure in which a computer algorithm selects successive test items tailored to each examinee's estimated ability level. Drawing on IRT to model item characteristics and ability estimation, CAT delivers precise scores with far fewer items than fixed-length tests, making it efficient for high-stakes assessments, clinical screening, and large-scale surveys.	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.