摘要
Q矩阵在认知诊断评估中至关重要,Q矩阵可以由相关领域的专家界定,也可以根据学生的作答数据进行估计。在已有Q矩阵修正方法的基础上,研究提出了基于项目拟合统计量RMSEA的Q矩阵估计方法,通过模拟和实证研究验证了该方法的可行性、有效性及效率。结果表明:(1)基于RMSEA的CSE算法可以有效地估计新题的属性向量,且耗时较少;(2)对Q矩阵估计的成功率受属性数目和基础题个数影响甚大,尤其是当属性数目较多时,要求有较多的基础题个数;(3)该统计量对被试数量要求不高,即使被试人数为400人,只要基础题个数足够多,估计效果依然较好;(4)该方法应用于实证数据的分析,可以一定程度地优化已有的分析结果,提高模型-数据的拟合性。
Usually,cognitive diagnostic assessment(CDA)is based on a test and the corresponding cognitive diagnostic model to construct a diagnostic analysis.Many approaches need a Q-matrix which reflects how attributes are measured in each item when applying the cognitive diagnosis model into an assessment.Q-matrix plays an important role in CDA.Q-matrix can be defined by experts in related fields,and also can be estimated according to students response data.Based on the existing Q-matrix refinement methods,a Q-matrix estimation method using an item fitting statistics RMSEA is proposed.The effectiveness and efficiency of the method are verified by a simulation study.And a real data analysis is also included.The results show that:(1)the CSE algorithm based on RMSEA can effectively estimate the attribute vectors of new items,and it takes less time;(2)the success recovery rate of Q-matrix estimation is greatly affected by the number of attributes and the number of basic items,especially when the number of attributes is large,it requires more basic items to estimate the attribute vectors of new items;(3)The sample size has little effect on the performance of CSE approach and a big sample size is not necessary to implement the Q-matrix modification method.Even if the number of subjects is 400,as long as the number of basic items is enough,it can have a high recovery ratio;(4)The application of this method to the analysis of empirical data can optimize the existing analysis results to a certain extent and improve the fitting of model-data.
作者
杨亚坤
朱仕浩
刘芯伶
YANG Yakun;ZHU Shihao;LIU Xinling(Jinhua Education College,Jinhua 321004,China;College of Teacher Education,Zhejiang Normal University,Jinhua 321004,China)
出处
《心理技术与应用》
2020年第1期51-59,共9页
Psychology(Techniques and Applications)
作者简介
通讯作者:杨亚坤,E-mail:1156009749@qq.com。
