分类视角下认知诊断测验项目区分度指标及应用  

An Item Discrimination Index and Its Application in Cognitive Diagnostic Assessment on a ClassificationOriented View

作　　者：汪文义[1] 宋丽红[2] 丁树良[1] Wang Wenyi, Song Lihong2, Diog Shulian(1.School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, 530022） （2Elementary Educational College, Jiangxi Normal University, Nanchang, 330022)

机构地区：[1]江西师范大学计算机信息工程学院,南昌330022 [2]江西师范大学初等教育学院,南昌330022

出　　处：《心理科学》2018年第2期475-483,共9页Journal of Psychological Science

基　　金：国家自然科学基金项目(31500909;31360237;31160203);全国教育科学规划教育部重点课题(DHA150285);江西省自然科学基金项目(20161BAB212044);江西省教育科学2013年度一般课题(13YB032);江西省社会科学规划项目(17JY10);国家社会科学基金项目(16BYY096);江西师范大学青年成长基金;江西师范大学博士启动基金的资助

摘　　要：在认知诊断中还没有指标能在无作答数据情况下直接评价项目的属性分类准确率或属性判准率。项目水平上的属性分类准确率,与项目属性向量、项目参数、先验分布和作答反应等有关。综合各个影响因素定义了项目水平上的属性期望分类准确率指标,并将其用于组卷。模拟研究显示:新指标可十分准确地评价项目的属性判准率,新指标对于项目筛选十分重要;以模式分类准确率为评价指标,基于新指标的组卷方法与经典的组卷方法表现相当。The existing studies suggested that item quality is closely relevant to the number of attributes required by an item, item parameters, and the prior distribution of attribute patterns in cognitive diagnostic assessment. Several studies focused on the design of Q-matrix and showed that items required only one attribute are important for classification. There are some works that provided two basic sets of item discrimination index to measure discriminatory power of an item. The first one is based on descriptive measures from classical test theory, such as the global item discrimination index, and the second index is based on information measures from item response theory, including cognitive diagnosis index （CDI）, attribute discrimination index （ADI）, modified CDI and ADI. Results showed a strong relationship between these indices and the average correct classification rates of attributes. But their relationship to the indices may change as a function of the distribution of attributes. There lacks an item quality index as a measure of item＇s correct classification rates of attributes. The purpose of this study was to propose an item discrimination index as a measure of correct classification rate of attributes based on Q-matrix, item parameters, and the distribution of attributes. Firstly, an attribute-specific item discrimination index, called item expected attribute matched rate （EAMR）, was introduced. Secondly, a heuristic method was presented using EAMR for test construction. The first simulation study was conducted to evaluate the performance of EAMR under the deterministic input noisy ＂and＂ gate （DINA） model. Several factors were manipulated for five independent attributes in this study. Four levels of correlation between latent attributes, p=.00, p=.50, p=.75, and p=.95, were considered. Items were categorized into five groups according to the number of attributes measured by each item. Item discrimination power was set at three levels, high, medium, and low. High level meant relative

关 键 词：分类准确率 项目属性期望分类准确率 组卷 确定性输入噪音与门模型 

分 类 号：B842.1[哲学宗教—基础心理学]