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| 计算机化自适应测验的聚合效度× | 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≠ | 1989–2000 | 1952–1968 |
| 提出者≠ | Samuel Messick (validity framework); Wainer and colleagues (CAT context) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 类型≠ | Validity evidence / construct validation | Probabilistic measurement model |
| 开创性文献≠ | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 别名 | CAT convergent validity, adaptive test construct validation, CAT validity evidence, convergent validity in CAT | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 相关 | 5 | 5 |
| 摘要≠ | Convergent validity assessment for computerized adaptive tests (CATs) examines whether the ability or trait estimates produced by an adaptive algorithm correlate substantially with scores from other measures of the same construct. Because each examinee receives a different subset of items in a CAT, demonstrating that the resulting scores still converge with theoretically related external measures is a critical step in establishing construct validity evidence. | 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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