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.

认知诊断评估 (CDA) 方法越来越多地应用于非诊断性大规模评估，以提取有关学生在特定领域能力的细粒度诊断反馈，并满足对学生成绩的问责要求。本研究旨在诊断来自 19 个欧盟 (EU) 成员国的 4324 名学生的阅读能力，这些学生参加了 2016 年国际阅读素养研究进展 (PIRLS)，这是调查学生阅读成绩的最全面的国际研究之一。PIRLS 数据通过使用对数线性认知诊断模型 (LCDM)，一种认知诊断分类模型 (DCM) 进行分析。基于四技能阅读能力模型确定学生的弱点和强项。结果表明，与传统的综合测试评分相比，该方法可以提供关于学生阅读技能的更细粒度的诊断信息。教师、学校管理人员、决策者和学生可以利用这些信息来最大限度地提高阅读计划和教学的学习成果。