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Estimating Raw Items Parameter in CAT

Author: YouXiaoFeng
Tutor: DingShuLiang
School: Jiangxi Normal University
Course: Software and Theory
Keywords: Original title CAT Item Response Theory Monte Carlo simulation
CLC: TP399-C1
Type: Master's thesis
Year: 2008
Downloads: 127
Quote: 0
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In recent years, with the development of computer technology and the increase of demand of personalized learning computerized adaptive testing (Computerized Adaptive Testing) by more and more attention , at the same time , the security of Adaptive Testing facing new challenges. Questions are repeatedly used and affected candidates questions sharing and many other factors such adaptive test security , fairness and effectiveness , and therefore how to build a large , high-quality CAT exam to become a computer adaptive test important topic. CAT exam of construction are generally given by Proposition experts questions, and then find a group of test quiz reaction was the answer , then the item parameter estimation , model data fit test , then select the parameters of good questions , together with the project together with storage. However, this method , there are several problems : the first is the need to find a large number of subjects for tests , time-consuming and costly ; second were quiz may also make the process of question leaks , especially to build a large-scale difficult to guarantee security , quality exam also questions equivalents, the technology is complex , and too many intermediate links . Equivalents may use to ANCHOR ANCHOR reused more easily be leaked . Computer adaptive testing process to insert the original title (Raw Items, that has not been the project parameter estimation ) , and at the same time the original title of the project parameters to estimate its significance for the construction of a large-scale , high-quality CAT Exam self-evident. Research in this area , domestic publications have not been reported , not many foreign research . In this study, the exploring implantable original question in the CAT test process and estimated project parameters . Case study of this article , the original title of the project parameters estimated for the single- parameter and two-parameter model using Monte Carlo simulation , experimental results .

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