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| Computerized adaptive test construct validity× | Διαφορική Λειτουργία Αντικειμένου (DIF)× | |
|---|---|---|
| Πεδίο | Ψυχομετρία | Ψυχομετρία |
| Οικογένεια | Latent structure | Latent structure |
| Έτος προέλευσης≠ | 1989–2000s | 1970s–1993 |
| Δημιουργός≠ | Samuel Messick (unified validity framework); CAT application formalized by Wainer, van der Linden, and colleagues | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| Τύπος≠ | Validity evaluation / psychometric evidence gathering | Item-level bias detection |
| Θεμελιώδης πηγή≠ | Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational Measurement (3rd ed., pp. 13–103). American Council on Education / Macmillan. link ↗ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| Εναλλακτικές ονομασίες | CAT construct validity, adaptive test construct validation, CAT validity evidence, construct validity evidence in CAT | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| Συναφείς≠ | 6 | 5 |
| Σύνοψη≠ | Construct validity in computerized adaptive testing evaluates whether the latent trait estimates produced by a CAT instrument genuinely measure the intended psychological or educational construct. Because adaptive algorithms select items individually for each examinee, the validity evidence gathered must account for the variable item exposure and the IRT-based scoring that are unique to CAT administrations. | Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development. |
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