手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| コンピュータ適応型テスト（CAT）における構成概念妥当性× | 項目応答理論における項目特性曲線（ICC）の差× | |
|---|---|---|
| 分野 | 心理測定学 | 心理測定学 |
| 系統 | Latent structure | Latent structure |
| 提唱年≠ | 1989–2000s | 1970s–1993 |
| 提唱者≠ | 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 |
| 種類≠ | Validity evaluation / psychometric evidence gathering | Item-level bias detection |
| 原典≠ | 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 |
| 別名 | 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 |
| 関連≠ | 6 | 5 |
| 概要≠ | 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. |
| ScholarGateデータセット ↗ |
|
|