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Teoria da Generalizabilidade para Testes Adaptativos Computadorizados×Teoria de Resposta ao Item (TRI)×
ÁreaPsicometriaPsicometria
FamíliaLatent structureLatent structure
Ano de origem1972 (G-theory); CAT application 1990s–2000s1952–1968
Autor originalLee J. Cronbach (G-theory); applied to CAT by Brennan and othersFrederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
TipoReliability / generalizability analysisProbabilistic measurement model
Fonte seminalBrennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗
Outros nomesCAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysisIRT, latent trait theory, item characteristic curve theory, modern test theory
Relacionados65
ResumoGeneralizability 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.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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ScholarGateComparar métodos: CAT Generalizability Theory · Item Response Theory. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare