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。
| 基于Rasch模型的计算机化自适应测试（CAT-Rasch）× | 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≠ | 1960 (Rasch model); CAT integration from 1970s onward | 1952–1968 |
| 提出者≠ | Georg Rasch (measurement model); adaptive testing formalized by Wainer, van der Linden, and others | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 类型≠ | Adaptive psychometric measurement | 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-Rasch, Rasch-based CAT, adaptive Rasch testing, computerized adaptive measurement | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 相关 | 5 | 5 |
| 摘要≠ | Computerized adaptive testing with the Rasch model selects items in real time based on each examinee's evolving ability estimate, so that every person receives a test precisely calibrated to their proficiency level. The result is a shorter, more efficient measurement instrument that loses none of the precision of a full-length fixed-form test. | 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 ↗ |
|
|