中文摘要：

CD-CAT是CDA同CAT的相结合的产物,适用于课堂教学,是教师补救教学、学生自我学习的重要工具。作为CD-CAT重要组成部分的初始阶段项目选取方法是影响测验判准率的重要因素。本文基于现有研究和CDA的项目区分度提出了四种新的初始阶段项目选取方法：CTTID法、CDI法、CTTIDR＊法和CDIR＊法。通过模拟研究发现,在定长的CD-CAT下,题库质量是HD-HV下,初始阶段结束时,CTTIDR＊法的PCCR比现有的T阵法高了.2999,比PWKL高了.1707,其它题库下趋势相同。整个测验结束时CTTIDR＊法的判准率仍然是最高的。在变长的CD-CAT下,最大后验概率大于.7、.8、.9下,CTTIDR＊法的被试平均测验长度比T阵法分别缩短了2.6170、2.2347、1.7470道题。

英文摘要：

Cognitive Diagnostic Computerized Adaptive Testing is a new testing mode which combines Computerized Adaptive Testing with Cognitive Diagnosis. It has the characteristics of adaptive and cognitive diagnosis, which can use less items and less time to evaluate knowledge state. It is applicable to classroom instruction because of its capacity for timely and immediately evaluation. It is the basis of remedial teaching and students＇ self-learning. It was presented by Thompson that CD-CAT had five important components： the parameter-calibrated and attribute-identified item bank, the initial stage item selection methods, an item selection strategy, a knowledge stage estimation method and a stopping rules. Of which the initial stage item selection methods can influence the pattern classification correct rate. The literature review revealed that Tu et al. （2013） studied the initial stage item selection method, and presented the ＂T matrix-method＂, which selected initial items from R-matrix. The other initial stage item selection method was a random method, which means to select first stage items from the item bank randomly. This method does not consider item parameters or attributes. It is easy and fast. The research showed that the T-matrix method had higher PCCR than the random method. The four initial stage item selection methods are based on the discrimination of Cognitive Diagnosis, which are the CTTID method, the CDI method, the CTTIDR ＊ method and the CDIR ＊ method. （1） CTTID calculates discrimination based on identification index of Classical Test Theory, and the fundamental question is ＂How well does this item help me differentiate between respondents who have mastered ＂more＂ attributes and those who have mastered ＂fewer＂ attributes？＂ In the DINA model, high discriminatory items are the items with smaller slipping and guessing parameters. （2） The CDI method is presented by Henson and Douglas （2005）, which is a weighted average of the elements in D where the KLI values as