Statistical Applications to Cognitive Diagnostic Testing

Susu Zhang, Jingchen Liu, Zhiliang Ying

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)651-675
Number of pages25
JournalAnnual Review of Statistics and Its Application
Volume10
DOIs
StatePublished - Mar 2023

Keywords

  • adaptive learning
  • classification
  • clustering
  • cognitive diagnosis
  • diagnostic classification
  • educational measurement
  • latent class analysis
  • psychometrics
  • statistical learning
  • supervised learning
  • unsupervised learning

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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