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 language | English (US) |
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Pages (from-to) | 651-675 |
Number of pages | 25 |
Journal | Annual Review of Statistics and Its Application |
Volume | 10 |
DOIs | |
State | Published - 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