Abstract
Cognitive diagnostic assessment (CDA) provides precise insights into students’ cognitive strengths and weaknesses. This systematic literature review analyzed 56 Scopus-indexed articles (2015-2025) using the theory-context-method framework. CDA is predominantly applied in mathematics, science, and language education, with significant contributions from China, USA, and Malaysia. While classical DINA and G-DINA models remain prevalent, recent studies integrate machine learning for Q-matrix validation. Quantitative approaches dominate (76.8%), revealing a gap between technical sophistication and practical implementation. The review emphasizes CDA’s potential for personalized learning and evidence-based policy, recommending future research to adopt longitudinal designs, expand interdisciplinary integration, and bridge diagnostic insights with pedagogical practice.
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Article Type: Review Article
EURASIA J Math Sci Tech Ed, Volume 22, Issue 2, February 2026, Article No: em2775
https://doi.org/10.29333/ejmste/17827
Publication date: 02 Feb 2026
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