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| Computerized adaptive test item response theory× | Теория на отговора на елемент (ТОЕ)× | |
|---|---|---|
| Област | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Година на възникване≠ | 1970s–1980s | 1952–1968 |
| Създател≠ | Lord, F. M.; further developed by Wainer, van der Linden, and others | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Тип≠ | Adaptive measurement / sequential testing | Probabilistic measurement model |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Свързани≠ | 4 | 5 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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