方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 计算机化自适应测验可推广性理论× | 项目反应理论 (IRT)× | |
|---|---|---|
| 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 | 1952–1968 |
| 提出者≠ | Lee J. Cronbach (G-theory); applied to CAT by Brennan and others | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 类型≠ | Reliability / generalizability analysis | Probabilistic measurement model |
| 开创性文献≠ | Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 别名 | CAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 相关≠ | 6 | 5 |
| 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. | 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. |
| ScholarGate数据集 ↗ |
|
|