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| 컴퓨터화된 적응형 검사(CAT)의 수렴 타당도× | 문항반응이론(IRT) 기반 컴퓨터 적응 검사 (CAT-IRT)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1989–2000 | 1970s–1980s |
| 창시자≠ | Samuel Messick (validity framework); Wainer and colleagues (CAT context) | Lord, F. M.; further developed by Wainer, van der Linden, and others |
| 유형≠ | Validity evidence / construct validation | Adaptive measurement / sequential testing |
| 원전 | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 |
| 별칭 | CAT convergent validity, adaptive test construct validation, CAT validity evidence, convergent validity in CAT | CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing |
| 관련≠ | 5 | 4 |
| 요약≠ | 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. | 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. |
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