@article {2604, title = {Factors Affecting the Classification Accuracy and Average Length of a Variable-Length Cognitive Diagnostic Computerized Test}, journal = {Journal of Computerized Adaptive Testing}, volume = {6}, year = {2018}, pages = {1-14}, doi = {10.7333/1802-060101}, url = {http://iacat.org/jcat/index.php/jcat/article/view/55/30}, author = {Huebner, Alan and Finkelman, Matthew D. and Weissman, Alexander} } @article {2167, title = {A Stochastic Method for Balancing Item Exposure Rates in Computerized Classification Tests}, journal = {Applied Psychological Measurement}, volume = {36}, number = {3}, year = {2012}, pages = {181-188}, abstract = {

Computerized classification tests (CCTs) classify examinees into categories such as pass/fail, master/nonmaster, and so on. This article proposes the use of stochastic methods from sequential analysis to address item overexposure, a practical concern in operational CCTs. Item overexposure is traditionally dealt with in CCTs by the Sympson-Hetter (SH) method, but this method is unable to restrict the exposure of the most informative items to the desired level. The authors\’ new method of stochastic item exposure balance (SIEB) works in conjunction with the SH method and is shown to greatly reduce the number of overexposed items in a pool and improve overall exposure balance while maintaining classification accuracy comparable with using the SH method alone. The method is demonstrated using a simulation study.

}, doi = {10.1177/0146621612439932}, url = {http://apm.sagepub.com/content/36/3/181.abstract}, author = {Huebner, Alan and Li, Zhushan} } @article {2110, title = {A Stochastic Method for Balancing Item Exposure Rates in Computerized Classification Tests}, journal = {Applied Psychological Measurement}, volume = {36}, number = {3}, year = {2012}, pages = {181-188}, abstract = {

Computerized classification tests (CCTs) classify examinees into categories such as pass/fail, master/nonmaster, and so on. This article proposes the use of stochastic methods from sequential analysis to address item overexposure, a practical concern in operational CCTs. Item overexposure is traditionally dealt with in CCTs by the Sympson-Hetter (SH) method, but this method is unable to restrict the exposure of the most informative items to the desired level. The authors\’ new method of stochastic item exposure balance (SIEB) works in conjunction with the SH method and is shown to greatly reduce the number of overexposed items in a pool and improve overall exposure balance while maintaining classification accuracy comparable with using the SH method alone. The method is demonstrated using a simulation study.

}, doi = {10.1177/0146621612439932}, url = {http://apm.sagepub.com/content/36/3/181.abstract}, author = {Huebner, Alan and Li, Zhushan} } @article {2204, title = {Restrictive Stochastic Item Selection Methods in Cognitive Diagnostic Computerized Adaptive Testing}, journal = {Journal of Educational Measurement}, volume = {48}, number = {3}, year = {2011}, pages = {255{\textendash}273}, abstract = {

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.\&$\#$39;s (2008) progressive method and proportional method.

}, issn = {1745-3984}, doi = {10.1111/j.1745-3984.2011.00145.x}, url = {http://dx.doi.org/10.1111/j.1745-3984.2011.00145.x}, author = {Wang, Chun and Chang, Hua-Hua and Huebner, Alan} }