摘要
作为认知诊断与计算机化自适应测验相结合的产物,认知诊断计算机化自适应测验(Cognitive Diagnostic Computerized Adaptive Testing,CD-CAT)是对被试知识状态的自适应。它既有传统CAT所面临的普遍性问题,也有在认知诊断中遇到的特殊问题:由于认知诊断中涉及属性这一概念,CD-CAT与传统CAT有很大的差别。本文紧紧围绕属性引起的差异,分别从认知诊断模型、题库建设、起始规则、选题策略、被试知识状态估计和终止规则等几部分详细介绍CD-CAT的研究进展和存在的问题。
Combining cognitive diagnosis with computerized adaptive testing, cognitive diagnostic computerized adaptive testing （CD-CAT） aims to more efficiently and more accurately diagnose examinees＇ mastery status of a group of discretely defined skills, or attributes than paper ＆ pencil tests. Because cognitive diagnosis involves in the concepts of attribute or knowledge state, CD-CAT is quite different from the ordinary CAT. In fact, the components of CD-CAT including the bank building, measurement model, starting rule, item selection strategy, stopping rule, and even the estimate method are very different from those of traditional CAT. In this paper, the researches and problems on these components of CD-CAT are discussed in details.
出处
《心理科学进展》
CSSCI
CSCD
北大核心
2012年第4期616-626,共11页
Advances in Psychological Science
基金
国家自然科学基金(30860084
31160203
31100756)
国家教育科学规划项目(CCA110109)
教育部人文社科项目(09JJCXLX012
10YJCXLX049
11YJC190002)
江西省教育厅科技计划项目(GJJ11385
GJJ10238)
全国教育考试科研规划课题(2009JKS2009)
江西省研究生创新专项资金项目(YC10A039)的资助
