Q矩阵包含错误的诊断测验分类准确性比较  

Compare the Diagnostic Assessment Classification Accuracy When the Q-Matrix Contains Error

作　　者：喻晓锋[1,2] 罗照盛[1] 高椿雷[1] 秦春影[2] 

机构地区：[1]江西师范大学心理学院,南昌330022 [2]亳州师范高等专科学校,亳州236800

出　　处：《心理科学》2014年第6期1478-1484,共7页Journal of Psychological Science

基　　金：国家自然科学基金(31160203;31100756;31360237);国家社会科学基金(12BYY055);教育部人文社会科学研究青年基金项目(13YJC880060);安徽省高校省级优秀青年人才基金重点项目(2013SQRL127ZD);安徽省自然科学研究项目(KJ2010B123;KJ2013B151);高等学校博士学科点专项科研基金(20113604110001);江西省研究生创新专项基金(YC2013-B024);安徽省哲学社会科学规划项目(AHSKY2014D102)的资助

摘　　要：Q矩阵是认知诊断测验的重要组成部分之一,围绕Q矩阵构建的诊断模型对Q矩阵中包含的错误较敏感。贝叶斯网分类模型是基于网络结点之间的关系构建的模型,将朴素贝叶斯网作为诊断模型,与DINA模型进行比较。模拟实验结果表明:Q矩阵中是否包含可达矩阵和错误界定的项目数量对DINA模型影响较大,对贝叶斯网模型影响较小;项目数量对DINA和贝叶斯网模型影响都较大;样本大小对贝叶斯网模型影响较大,对DINA模型影响较小。模拟研究结果显示,当Q矩阵中不包含可达阵、包含5个以上错误项目或样本数较大时,贝叶斯网分类模型优于DINA模型;而当Q矩阵中包含可达阵和5个(以下)错误项目时,DINA模型优于贝叶斯分类模型。In recent years, cognitive diagnostic assessment is an area of research that has attracted widespread attention. As we all know, one of the important components in cognitive diagnosis is Q-matrix, because Q-matrix reflects the design of the assessment instrument and is the core element that determines the quality of the diagnostic feedback for the instrument. At present, there are some researches about classification accuracy in D1NA model with error existed in Q-matrix. These studies indicate that the quality of the Q-matrix has a great influence on the diagnostic accuracy rate, and also indicate that cognitive diagnosis models constructed around Q-matrix are sensitive to the accuracy of Q-matrix, greatly influenced by Q-matrix, and mostly, the starting point of these research are ＂if the Q-matrix contains errors, how does it affect the accuracy of parameters estimation and classification accuracy＂. Up to now, the most problem is that we haven＇t an effective method for validating the Q-matrix at hand. Different diagnostic models have different diagnostic classification accuracy rate, and affected by factors that are not the same. Bayesian networks is one of a widespread concerned model, it has strong processing capacity to uncertainly problem. Starting from another perspective view, uses Bayesian network model which less affected by Q-matrix as diagnosis classification model. Compares Bayesian network with the D1NA model in cognitive diagnostic classification accuracy on the base of a Q-matrix which contains errors. Bayesian network classification model is less affected by the Q-matrix than D1NA model. Then, two simulation studies are carried out. The first is to study the performance of DINA and Bayesian network classification model when the Q-matrix contains error items, the data is generated under D1NA model. To be fair, the data generated in the second research doesn＇t base on any specified models, adopts the method introduced by Leighton, Gierl ＆ Hunka（2004）. Investigates the effect of d

关 键 词：认知诊断 Q矩阵 贝叶斯网 可达矩阵 DINA模型 

分 类 号：B842.1[哲学宗教—基础心理学]