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| 컴퓨터화 적응형 검사 일반화 가능성 이론× | 문항반응이론(IRT) 기반 컴퓨터 적응 검사 (CAT-IRT)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1972 (G-theory); CAT application 1990s–2000s | 1970s–1980s |
| 창시자≠ | Lee J. Cronbach (G-theory); applied to CAT by Brennan and others | Lord, F. M.; further developed by Wainer, van der Linden, and others |
| 유형≠ | Reliability / generalizability analysis | Adaptive measurement / sequential testing |
| 원전≠ | Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826 | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 |
| 별칭 | CAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysis | CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing |
| 관련≠ | 6 | 4 |
| 요약≠ | Generalizability theory (G-theory) applied to computerized adaptive testing (CAT) evaluates the dependability of adaptive test scores by decomposing score variance across measurement facets such as persons, items, and occasions. Unlike classical test theory, G-theory quantifies multiple simultaneous sources of measurement error, offering a richer reliability picture for adaptively administered assessments. | 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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