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| 基于项目反应理论的计算机自适应测试 (CAT-IRT)× | 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≠ | 1970s–1980s | 1952–1968 |
| 提出者≠ | Lord, F. M.; further developed by Wainer, van der Linden, and others | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 类型≠ | Adaptive measurement / sequential testing | 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-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 相关≠ | 4 | 5 |
| 摘要≠ | Computerized adaptive testing based on item response theory is a sequential measurement procedure in which a computer algorithm selects successive test items tailored to each examinee's estimated ability level. Drawing on IRT to model item characteristics and ability estimation, CAT delivers precise scores with far fewer items than fixed-length tests, making it efficient for high-stakes assessments, clinical screening, and large-scale surveys. | 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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