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Cai, Liuhan; Albano, Anthony D.; Roussos, Louis A. – Measurement: Interdisciplinary Research and Perspectives, 2021
Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…
Descriptors: Adaptive Testing, Test Items, Item Response Theory, Test Construction
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Bao, Yu; Bradshaw, Laine – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…
Descriptors: Test Items, Selection, Adaptive Testing, Computer Assisted Testing
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Frey, Andreas; Carstensen, Claus H. – Measurement: Interdisciplinary Research and Perspectives, 2009
On a general level, the objective of diagnostic classifications models (DCMs) lies in a classification of individuals regarding multiple latent skills. In this article, the authors show that this objective can be achieved by multidimensional adaptive testing (MAT) as well. The authors discuss whether or not the restricted applicability of DCMs can…
Descriptors: Adaptive Testing, Test Items, Classification, Psychometrics