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Lin, Chuan-Ju; Chang, Hua-Hua – Educational and Psychological Measurement, 2019
For item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized…
Descriptors: Test Items, Selection Criteria, Computer Assisted Testing, Adaptive Testing
Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua – Journal of Educational Measurement, 2017
The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Test Items
Cui, Ying; Gierl, Mark J.; Chang, Hua-Hua – Journal of Educational Measurement, 2012
This article introduces procedures for the computation and asymptotic statistical inference for classification consistency and accuracy indices specifically designed for cognitive diagnostic assessments. The new classification indices can be used as important indicators of the reliability and validity of classification results produced by…
Descriptors: Classification, Accuracy, Cognitive Tests, Diagnostic Tests
Chen, Ping; Xin, Tao; Wang, Chun; Chang, Hua-Hua – Psychometrika, 2012
Item replenishing is essential for item bank maintenance in cognitive diagnostic computerized adaptive testing (CD-CAT). In regular CAT, online calibration is commonly used to calibrate the new items continuously. However, until now no reference has publicly become available about online calibration for CD-CAT. Thus, this study investigates the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Diagnostic Tests, Cognitive Tests
Wang, Chun; Chang, Hua-Hua; Huebner, Alan – Journal of Educational Measurement, 2011
This paper proposes two new item selection methods for cognitive diagnostic computerized adaptive testing: the restrictive progressive method and the restrictive threshold method. They are built upon the posterior weighted Kullback-Leibler (KL) information index but include additional stochastic components either in the item selection index or in…
Descriptors: Test Items, Adaptive Testing, Computer Assisted Testing, Cognitive Tests