@conference {2639, title = {A Simulation Study to Compare Classification Method in Cognitive Diagnosis Computerized Adaptive Testing}, booktitle = {IACAT 2017 Conference}, year = {2017}, month = {08/2017}, publisher = {Niigata Seiryo University}, organization = {Niigata Seiryo University}, address = {Niigata, Japan}, abstract = {

Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) combines the strengths of both CAT and cognitive diagnosis. Cognitive diagnosis models that can be viewed as restricted latent class models have been developed to classify the examinees into the correct profile of skills that have been mastered and those that have not so as to get more efficient remediation. Chiu \& Douglas (2013) introduces a nonparametric procedure that only requires specification of Q-matrix to classify by proximity to ideal response pattern. In this article, we compare nonparametric procedure with common profile estimation method like maximum a posterior (MAP) in CD-CAT. Simulation studies consider a variety of Q-matrix structure, the number of attributes, ways to generate attribute profiles,\ and item quality. Results indicate that nonparametric procedure consistently gets the higher pattern and attribute recovery rate in nearly all conditions.

References

Chiu, C.-Y., \& Douglas, J. (2013). A nonparametric approach to cognitive diagnosis by proximity to ideal response patterns. Journal of Classification, 30, 225-250. doi: 10.1007/s00357-013-9132-9

Session Video

}, url = {https://drive.google.com/open?id=1jCL3fPZLgzIdwvEk20D-FliZ15OTUtpr}, author = {Jing Yang and Jian Tao and Hua-Hua Chang and Ning-Zhong Shi} }