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(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.