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ERIC Number: EJ940999
Record Type: Journal
Publication Date: 2011
Pages: 19
Abstractor: As Provided
Reference Count: 47
ISBN: N/A
ISSN: ISSN-0022-0655
Restrictive Stochastic Item Selection Methods in Cognitive Diagnostic Computerized Adaptive Testing
Wang, Chun; Chang, Hua-Hua; Huebner, Alan
Journal of Educational Measurement, v48 n3 p255-273 Fall 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 the item selection procedure. Simulation studies show that both methods are successful at simultaneously suppressing overexposed items and increasing the usage of underexposed items. Compared to item selection based upon (1) pure KL information and (2) the Sympson-Hetter method, the two new methods strike a better balance between item exposure control and measurement accuracy. The two new methods are also compared with Barrada et al.'s (2008) progressive method and proportional method.
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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