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The Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing
ARTICLE

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Applied Psychological Measurement Volume 37, Number 1, ISSN 0146-6216

Abstract

Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be "tailored" to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends on the item parameter values. However, items are chosen on the basis of their parameter estimates, and capitalization on chance may occur. In this article, the authors investigated the effects of capitalization on chance on test length and classification accuracy in several VL-CAT simulations. The results confirm that capitalization on chance occurs in VL-CAT and has complex effects on test length, ability estimation, and classification accuracy. These results have important implications for the design and implementation of VL-CATs. (Contains 6 figures and 4 tables.)

Citation

Patton, J.M., Cheng, Y., Yuan, K.H. & Diao, Q. (2013). The Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing. Applied Psychological Measurement, 37(1), 24-40. Retrieved December 4, 2020 from .

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