Abstract
Cognitive diagnostic assessment (CDA) approach has been increasingly applied to non-diagnostic large-scale assessments to extract fine-grained diagnostic feedback about students’ ability in a given domain and meet accountability demands for student achievement. This study aimed to diagnose the reading abilities of 4324 students from 19 European Union (EU) member countries that participated in the 2016 Progress in International Reading Literacy Study (PIRLS), one of the most comprehensive international studies that investigate students’ reading achievement. The PIRLS data were analyzed by using the Log-linear Cognitive Diagnosis Modeling (LCDM), a type of cognitive diagnostic classification model (DCM). Students’ weaknesses and strengths were identified based on a four-skill reading ability model. The results revealed that the methodology could provide more fine-grained diagnostic information about students’ reading skills than traditional aggregated-test scoring could. Such information could be utilized by teachers, school administrators, decision-makers, and students for maximizing the learning outcomes of reading programs and instruction.
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