文章基本信息

标题：Scoring and Classifying Examinees Using Measurement Decision Theory
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作者：Lawrence M. Rudner ; Graduate Management Admission Council
期刊名称：Practical Assessment, Research and Evaluation
印刷版ISSN：1531-7714
电子版ISSN：1531-7714
出版年度：2009
卷号：14
出版社：ERIC: Clearinghouse On Assessment and Evaluation
摘要：This paper describes and evaluates the use of measurement decision theory (MDT) to classify examinees based on their item response patterns. The model has a simple framework that starts with the conditional probabilities of examinees in each category or mastery state responding correctly to each item. The presented evaluation investigates: (1) the classification accuracy of tests scored using decision theory; (2) the effectiveness of different sequential testing procedures; and (3) the number of items needed to make a classification. A large percentage of examinees can be classified accurately with very few items using decision theory. A Java Applet for self instruction and software for generating, calibrating and scoring MDT data are provided.