Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Constructvaliditeit in Computerized Adaptive Testing (CAT)× | Computerized Adaptive Testing gebaseerd op Item Response Theory (CAT-IRT)× | |
|---|---|---|
| Vakgebied | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Jaar van ontstaan≠ | 1989–2000s | 1970s–1980s |
| Grondlegger≠ | Samuel Messick (unified validity framework); CAT application formalized by Wainer, van der Linden, and colleagues | Lord, F. M.; further developed by Wainer, van der Linden, and others |
| Type≠ | Validity evaluation / psychometric evidence gathering | Adaptive measurement / sequential testing |
| Oorspronkelijke bron≠ | Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational Measurement (3rd ed., pp. 13–103). American Council on Education / Macmillan. link ↗ | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 |
| Aliassen | CAT construct validity, adaptive test construct validation, CAT validity evidence, construct validity evidence in CAT | CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing |
| Verwant≠ | 6 | 4 |
| Samenvatting≠ | 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. | 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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