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Research On Item-selection Strategy Of Computerized Adaptive Cognitive Diagnostic Testing

Posted on:2012-02-09Degree:MasterType:Thesis
Country:ChinaCandidate:Z H WuFull Text:PDF
GTID:2218330338968509Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
Traditional test only provides a test total score for examinee, computer adaptive test estimates examinee's ability. However, both two methods have not provided the relevant information for students'inner knowledge states. But cognitive diagnosis obtains students'inner knowledge structures form student answers, in other words, what knowledge the examinee master, and what knowledge did not grasp. In recent years, with the development of compute and people pay more attention on cognitive diagnosis, the computerized adaptive testing with cognitive diagnosis (CD‐CAT) has become an irreversible trend in a modern assessment.CD‐CAT adapted to examinee's knowledge states, can provide the relevant information for examinee's inner knowledge states in the efficient and accurate way. Teachers can be guided to design a test, which can identify students with cognitive errors,and in order to achieve the purpose of teach students in accordance of their aptitude.How to choose items to be administered is an important component in computerized adaptive testing with cognitive diagnosis。Meanwhile,a cognitive diagnostic test blueprint will not bring mismatch of examinees'knowledge states when the reachability matrix(RM) is included in a blueprint in the case of expected response patterns being considered。On the basis of Shannon's Entropy item‐selection strategy,in this paper four different test blueprints are adopted to examine effect on diagnostic accuracy in the process of applying RM。The results of Monte Carlo simulation show that choosing all the corresponding items of RM plays an important role to improve the diagnostic accuracy in CD‐CAT,and it is also important reference to formulate item‐selection strategy in CD‐CAT. In the process of CD‐CAT choosing more corresponding items of RM can obviously increase the pattern match rate(PMR), items quality has little effect on the results, and when item pool does not contain or have less corresponding items of RM, item quality has great influence on PMR。Using RM is benefit to construct test and item‐selection strategy for cognitive diagnosis purpose。...
Keywords/Search Tags:Cognitive Diagnosis, Computerized Adaptive Testing, Item‐selection Strategy, Reachability Matrix
PDF Full Text Request
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