Using country-specific Q-matrices for cognitive diagnostic assessments with international large-scale data
نویسندگان
چکیده
Abstract In cognitive diagnosis assessment (CDA), the impact of misspecified item-attribute relations (or “Q-matrix”) designed by subject-matter experts has been a great challenge to real-world applications. This study examined parameter estimation CDA with expert-designed Q-matrix and two refined Q-matrices for international large-scale data. Specifically, G-DINA model was used analyze TIMSS data Grade 8 five selected countries separately; need specific country investigated. The results suggested that fitted better than Q-matrix, stepwise validation method performed nonparametric classification method, resulting in substantively different students attribute mastery patterns item estimates. confirmed use country-specific based on led fit compared universal Q-matrix.
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ژورنال
عنوان ژورنال: Large-scale Assessments in Education
سال: 2022
ISSN: ['2196-0739']
DOI: https://doi.org/10.1186/s40536-022-00138-4