Diagnosing Primary Students’ Reading Progression: Is Cognitive Diagnostic Computerized Adaptive Testing the Way Forward?

阅读(过程) 计算机化自适应测验 形成性评价 计算机科学 阅读理解 考试(生物学) 认知 优势和劣势 多样性(控制论) 认知心理学 分类 理解力 心理学 人工智能 数学教育 自然语言处理 情报检索 心理测量学 发展心理学 社会心理学 语言学 古生物学 哲学 神经科学 生物 程序设计语言
作者
Yan Li,Chao Huang,Jia Liu
出处
期刊:Journal of Educational and Behavioral Statistics [SAGE Publishing]
卷期号:48 (6): 842-865 被引量:8
标识
DOI:10.3102/10769986231160668
摘要

Cognitive diagnostic computerized adaptive testing (CD-CAT) is a cutting-edge technology in educational measurement that targets at providing feedback on examinees’ strengths and weaknesses while increasing test accuracy and efficiency. To date, most CD-CAT studies have made methodological progress under simulated conditions, but little has applied CD-CAT to real educational assessment. The present study developed a Chinese reading comprehension item bank tapping into six validated reading attributes, with 195 items calibrated using data of 28,485 second to sixth graders and the item-level cognitive diagnostic models (CDMs). The measurement precision and efficiency of the reading CD-CAT system were compared and optimized in terms of crucial CD-CAT settings, including the CDMs for calibration, item selection methods, and termination rules. The study identified seven dominant reading attribute mastery profiles that stably exist across grades. These major clusters of readers and their variety with grade indicated some sort of reading developmental mechanisms that advance and deepen step by step at the primary school level. Results also suggested that compared to traditional linear tests, CD-CAT significantly improved the classification accuracy without imposing much testing burden. These findings may elucidate the multifaceted nature and possible learning paths of reading and raise the question of whether CD-CAT is applicable to other educational domains where there is a need to provide formative and fine-grained feedback but where there is a limited amount of test time.
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