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ERIC Number: EJ1143126
Record Type: Journal
Publication Date: 2017
Pages: 19
Abstractor: As Provided
ISSN: ISSN-0022-0655
Dual-Objective Item Selection Criteria in Cognitive Diagnostic Computerized Adaptive Testing
Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua
Journal of Educational Measurement, v54 n2 p165-183 Sum 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 status and overall test performance. The new procedure is based on the Jensen-Shannon (JS) divergence, a symmetrized version of the Kullback-Leibler divergence. We show that the JS divergence resolves the noncomparability problem of the dual information index and has close relationships with Shannon entropy, mutual information, and Fisher information. The performance of the JS divergence is evaluated in simulation studies in comparison with the methods available in the literature. Results suggest that the JS divergence achieves parallel or more precise recovery of latent trait variables compared to the existing methods and maintains practical advantages in computation and item pool usage.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A