An empirical Q-matrix validation method for the sequential generalized DINA model |
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Authors: | Wenchao Ma Jimmy de la Torre |
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Affiliation: | 1. Department of Educational Studies in Psychology, Research Methodology and Counseling, University of Alabama, Tuscaloosa, Alabama, USA;2. Faculty of Education, University of Hong Kong, Hong Kong |
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Abstract: | As a core component of most cognitive diagnosis models, the Q-matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q-matrix empirically because a misspecified Q-matrix could result in erroneous attribute estimation. Most existing Q-matrix validation procedures are developed for dichotomous responses. However, in this paper, we propose a method to empirically detect and correct the misspecifications in the Q-matrix for graded response data based on the sequential generalized deterministic inputs, noisy ‘and’ gate (G-DINA) model. The proposed Q-matrix validation procedure is implemented in a stepwise manner based on the Wald test and an effect size measure. The feasibility of the proposed method is examined using simulation studies. Also, a set of data from the Trends in International Mathematics and Science Study (TIMSS) 2011 mathematics assessment is analysed for illustration. |
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Keywords: | cognitive diagnosis discrimination index G-DINA Q-matrix validation sequential G-DINA stepwise Trends in International Mathematics and Science Study Wald test |
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