Abstract
Traditional test only provides a total score and computer adaptive test (CAT) not only provides examinee's score but also estimates examinee's ability. However, both two methods have not studied students' knowledge states. Cognitive diagnostic assessment (CDA) is designed to measure specific knowledge structures and processing skills in students so as to provide information about their cognitive strengths and weaknesses. A good diagnostic test is one that goes beyond estimation of individuals' overall ability levels. How to combine an attribute hierarchy and the reachability matrix with Henson and Douglas's item selection strategy to construct an effective test for cognitive diagnosis in order to improve the accuracy is discussed in this paper. When compared to randomly constructed tests from the same item bank, classification rates are improved significantly.
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