方法对比
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| 计算机化自适应测验可推广性理论× | 概化理论（G-Theory）× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1972 (G-theory); CAT application 1990s–2000s | 1963–1972 |
| 提出者≠ | Lee J. Cronbach (G-theory); applied to CAT by Brennan and others | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam |
| 类型≠ | Reliability / generalizability analysis | Variance-components reliability model |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | CAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysis | G-theory, G-study / D-study framework, variance components reliability |
| 相关≠ | 6 | 4 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
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