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Theorems and Methods of a Complete Q Matrix With Attribute Hierarchies Under Restricted Q-Matrix Design

机译:约束Q矩阵设计下具有属性层次的完整Q矩阵的定理和方法

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The design of test Q matrix can directly influence the classification accuracy of a cognitive diagnostic assessment. In this paper, we focus on Q matrix design when attribute hierarchies are known prior to test development. A complete Q matrix design is proposed and theorems are presented to demonstrate that it is a necessary and sufficient condition to guarantee the identifiability of ideal response patterns. A simulation study is also conducted to detect the effects of the proposed design on a family of conjunctive diagnostic models. The results revealed that the proposed Q matrix design is the key condition for guaranteeing classification accuracy. When only one type of item pattern in R matrix is missing from the associated test Q matrix, the related attribute-wise agreement rate will decrease dramatically. When the entire R matrix is missing, both the pattern-wise and attribute-wise agreement rates will decrease sharply. This indicates that the proposed procedures for complete Q matrix design with attribute hierarchies can serve as guidelines for test blueprint development prior to item writing in a cognitive diagnostic assessment.
机译:测试Q矩阵的设计可以直接影响认知诊断评估的分类准确性。在本文中,当测试开发之前已知属性层次结构时,我们专注于Q矩阵设计。提出了一个完整的Q矩阵设计,并给出了定理以证明这是保证理想响应模式可识别性的必要条件。还进行了仿真研究,以检测提出的设计对一系列联合诊断模型的影响。结果表明,提出的Q矩阵设计是保证分类精度的关键条件。当关联的测试Q矩阵中仅缺少R矩阵中的一种类型的项目模式时,相关的按属性达成协议的比率将大大降低。当整个R矩阵丢失时,模式和属性方面的协议率都将急剧下降。这表明具有属性层次结构的完整Q矩阵设计的拟议程序可以用作在认知诊断评估中编写项目之前测试蓝图开发的准则。

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