基于混合模型(Mixed-CDMs)视角的CD-CAT及其应用研究  

Study on CD-CAT based on the Perspective of Mixed CDMs

作　　者：高旭亮[1] 汪大勋 蔡艳[1] 涂冬波[1] Gao Xuliang;Wang Daxun;Cai Yan;Tu Dongbo(Research Center of Psychological Health Education,School of Psychology,Jiangxi Normal University,Nanchang,330022)

机构地区：[1]江西师范大学心理健康教育研究中心江西师范大学心理学院,南昌330022

出　　处：《心理科学》2019年第1期194-201,共8页Journal of Psychological Science

基　　金：国家自然科学基金(31660278;31760288);江西省社会科学规划项目(17JY12);江西省教育厅人文社科重点项目(JD17077);江西省教育厅科学技术研究项目青年项目(GJJ170230)的资助

摘　　要：传统CD-CAT通常选择一个认知诊断模型(Cognitive Diagnosis Model, CDM)标定题库参数,但在实际应用中一个CDM很难完全拟合题库中所有的题目。本文提出了一种基于混合模型(Mixed-CDMs)建立CD-CAT的方法,该方法通过Wald检验为题库中每一题目选择一个恰当的CDM,并通过模拟研究和实际数据的应用分别比较了基于传统单一CDM(G-DINA, DINA, DINO,A-CDM, LLM, RRUM)和Mixed-CDMs建立CD-CAT的效果,选题策略包括SHE和MPWKL,终止规则采用了定长的方式。结果发现:基于Mixed-CDMs建立的CD-CAT在模式判准率和题库安全性的表现要全面优于传统方法,因此本文提出的基于Mixed-CDMs的CD-CAT具有较强的理论和实用价值。Cognitive Diagnostic Computerized Adaptive Testing(CD-CAT) combines the advantages of both cognitive diagnosis and CAT, which can make adaptive diagnosis for different individuals, and provide more detailed diagnostic information on the knowledge competence of the examinees. Currently, CD-CAT has been a promising research area and gained more and more attention.The first step in the implementation of CD-CAT is to build a high-quality item bank. One difficulty that practitioners face is that of how to select the most appropriate cognitive diagnostic model(CDM) from such a large number of models. A wide array of CDMs has been developed based on different assumptions, for example, some reduced CDMs include the Deterministic Inputs, Noisy and Gate(DINA) model, the Deterministic Inputs, Noisy or Gate(DINO) model, the Additive Cognitive Diagnostic Model(A-CDM), the Linear Logistic Model(LLM) and the Reduced Reparametrized Unified Model(RRUM). Apart from these reduced CDMs, some generalized models have also been developed, including the Generalized DINA(G-DINA) model, the General Diagnostic Model(GDM), and the Log-linear CDM(LCDM). Compared with the reduced CDMs, generalized CDMs are more complex and require a larger sample size to yield accurate estimates. In addition, compared with the complex generalized model, using reduced models can improve the accuracy of diagnostic test and lead to more straightforward and meaningful interpretations. However, almost all the research and application of CD-CAT has been conducted using only one CDM to estimate the item parameters. Analyses of real test data indicate that no single reduced model can be expected to satisfactorily fit all the items. The Wald test is developed as an item-level statistical test to examine whether the G-DINA model can be replaced by a reduced CDM without losing model data fit significantly in order to select an appropriate CDM for each item. Based on this, the study developed a new selecting model method, namely, mixed CDMs(Mixed-CDMs) method, to the con

关 键 词：CD-CAT 认知诊断模型 混合模型 WALD检验 

分 类 号：B841[哲学宗教—基础心理学]