Comparer des méthodes

	Théorie de la généralisabilité appliquée aux tests adaptatifs informatisés	Computerized adaptive test item response theory
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1972 (G-theory); CAT application 1990s–2000s	1970s–1980s
Auteur d'origine	Lee J. Cronbach (G-theory); applied to CAT by Brennan and others	Lord, F. M.; further developed by Wainer, van der Linden, and others
Type	Reliability / generalizability analysis	Adaptive measurement / sequential testing
Source fondatrice	Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826	Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113
Alias	CAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysis	CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing
Apparentées	6	4
Résumé	Generalizability theory (G-theory) applied to computerized adaptive testing (CAT) evaluates the dependability of adaptive test scores by decomposing score variance across measurement facets such as persons, items, and occasions. Unlike classical test theory, G-theory quantifies multiple simultaneous sources of measurement error, offering a richer reliability picture for adaptively administered assessments.	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.