Based on the traditional cognitive diagnosis models (CMDs), this study developed two new cognitive diagnosis models, PA-rRUM and PA-DINA model respectively, to handle the polytomous attributes. Through Monte Carlo simulation, it indicated that:
The parameters in the models could be identified, and robustness of the parameter estimation is relatively strong. Furthermore, the correct match ratios and accuracies of parameter estimation are decent. All these findings verified that the models are feasible for ploytomous attribute cognitive diagnosis.
It also found that the precision of might be influenced by the sample size and the number of replications for the RP*matrix. The larger the sample size is, or the greater the number of replications is, the more precise they might be. The results suggested that the Q matrix should include the RP* matrix while the attribute is polytomous.
In conclusion, the models overcame the shortcomings stemmed from dichotomous attribute models, thus they might provide a richer diagnostic result and more flexible models.
蔡艳;涂冬波. 属性多级化的认知诊断模型拓展及其Q矩阵设计[J]. 心理学报, 10.3724/SP.J.1041.2015.01300.
CAI Yan; TU Dongbo. Extension of Cognitive Diagnosis Models Based on the Polytomous Attributes Framework and Their Q-matrices Designs. Acta Psychologica Sinica, 2015, 47(10): 1300-1308.