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Annual Review of Statistics and Its Application

Volume 10, 2023

Statistical Applications to Cognitive Diagnostic Testing

  • Susu Zhang1, Jingchen Liu2 and Zhiliang Ying2
  • 1Departments of Psychology and Statistics, University of Illinois Urbana-Champaign, Champaign, Illinois, USA 2Department of Statistics, Columbia University, New York, New York, USA; email: [email protected]
  • Vol. 10:651-675 (Volume publication date March 2023)
  • First published as a Review in Advance on November 09, 2022
  • Copyright © 2023 by the author(s).
    This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third-party material in this article for license information

Abstract

Diagnostic classification tests are designed to assess examinees’ discrete mastery status on a set of skills or attributes. Such tests have gained increasing attention in educational and psychological measurement. We review diagnostic classification models and their applications to testing and learning, discuss their statistical and machine learning connections and related challenges, and introduce some contemporary and future extensions.

Keyword(s): adaptive learning, classification, clustering, cognitive diagnosis, diagnostic classification, educational measurement, latent class analysis, psychometrics, statistical learning, supervised learning, unsupervised learning
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2023-03-10
2025-06-19
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