NDLI: A simplified version of the maximum information per time unit method in computerized adaptive testing

Content Provider	Springer Nature Link
Author	Cheng, Ying Diao, Qi Behrens, John T.
Copyright Year	2016
Abstract	In this article, we propose a simplified version of the maximum information per time unit method (MIT; Fan, Wang, Chang, & Douglas, Journal of Educational and Behavioral Statistics 37: 655–670, 2012), or MIT-S, for computerized adaptive testing. Unlike the original MIT method, the proposed MIT-S method does not require fitting a response time model to the individual-level response time data. It is also computationally efficient. The performance of the MIT-S method was compared against that of the maximum information (MI) method in terms of measurement precision, testing time saving, and item pool usage under various item response theory (IRT) models. The results indicated that when the underlying IRT model is the two- or three-parameter logistic model, the MIT-S method maintains measurement precision and saves testing time. It performs similarly to the MI method in exposure control; both result in highly skewed item exposure distributions, due to heavy reliance on the highly discriminating items. If the underlying model is the one-parameter logistic (1PL) model, the MIT-S method maintains the measurement precision and saves a considerable amount of testing time. However, its heavy reliance on time-saving items leads to a highly skewed item exposure distribution. This weakness can be ameliorated by using randomesque exposure control, which successfully balances the item pool usage. Overall, the MIT-S method with randomesque exposure control is recommended for achieving better testing efficiency while maintaining measurement precision and balanced item pool usage when the underlying IRT model is 1PL.
Starting Page	502
Ending Page	512
Page Count	11
File Format	PDF
ISSN	07433808
Journal	Behavior Research Methods
Volume Number	49
Issue Number	2
e-ISSN	15543528
Language	English
Publisher	Springer US
Publisher Date	2016-02-23
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Maximum information per time unit Response time Computerized adaptive testing Item exposure control Test efficiency Cognitive Psychology
Content Type	Text
Resource Type	Article
Subject	Experimental and Cognitive Psychology 3200/3201 Psychology

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