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| CAT Generalizability Theory× | Teoria generalizowalności (G-Theory)× | |
|---|---|---|
| Dziedzina | Psychometria | Psychometria |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | 1972 (G-theory); CAT application 1990s–2000s | 1963–1972 |
| Twórca≠ | Lee J. Cronbach (G-theory); applied to CAT by Brennan and others | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam |
| Typ≠ | Reliability / generalizability analysis | Variance-components reliability model |
| Źródło pierwotne≠ | Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826 | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ |
| Inne nazwy≠ | CAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysis | G-theory, G-study / D-study framework, variance components reliability |
| Pokrewne≠ | 6 | 4 |
| Podsumowanie≠ | 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. | Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions. |
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