The demand for diagnostic feedback has triggered extensive research on cognitive diagnostic models (CDMs), such as the deterministic input, noisy output “and” gate (DINA) model. This study explored two Q-matrix specifications with the DINA model in a statewide large-scale mathematics assessment. The first Q-matrix was developed based on five predefined content reporting categories, and the second was based on the post hoc coding of 15 attributes by test-development experts. Total raw scores correlated strongly with the number of skills mastered, using both Q-matrices. Correlations between the DINA-model item statistics and those from the item response theory analyses were moderate to strong, but were always lower for the 15-skill model. Results highlighted the trade-off between finer-grained modeling and less precise model estimation.
COVID-19-related school closures caused unprecedented and prolonged disruption to daily life, education, and social and physical activities. This disruption in the life course affected the well-being of students from different age groups. This study proposed analyzing student well-being and determining the most influential factors that affected student well-being during the COVID-19 pandemic. With this aim, we adopted a cross-sectional study designed to analyze the student data from the Responses to Educational Disruption Survey (REDS) collected between December 2020 and July 2021 from a large sample of grade 8 or equivalent students from eight countries (n = 20,720), including Burkina Faso, Denmark, Ethiopia, Kenya, the Russian Federation, Slovenia, the United Arab Emirates, and Uzbekistan. We first estimated a well-being IRT score for each student in the REDS student database. Then, we used 10 data-mining approaches to determine the most influential factors that affected the well-being of students during the COVID-19 outbreak. Overall, 178 factors were analyzed. The results indicated that the most influential factors on student well-being were multifarious. The most influential variables on student well-being were students’ worries about contracting COVID-19 at school, their learning progress during the COVID-19 disruption, their motivation to learn when school reopened, and their excitement to reunite with friends after the COVID-19 disruption.
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