CAT Generalizability Theory
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Brennan, R. L. (2001). Generalizability Theory. Springer. · ISBN 978-0387952826
- Van der Linden, W. J., & Glas, C. A. W. (2000). Computerized adaptive testing: Theory and practice. Kluwer Academic Publishers. · URL
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.