@article {387,
	title = {A practitioner{\textquoteright}s guide to variable-length computerized classification testing},
	journal = {Practical Assessment, Research and Evaluation},
	volume = {12 },
	number = {1},
	year = {2007},
	month = {7/1/2009},
	chapter = {January, 2007},
	abstract = {Variable-length computerized classification tests, CCTs, (Lin \& Spray, 2000; Thompson, 2006) are a powerful and efficient approach to testing for the purpose of classifying examinees into groups. CCTs are designed by the specification of at least five technical components: psychometric model, calibrated item bank, starting point, item selection algorithm, and termination criterion. Several options exist for each of these CCT components, creating a myriad of possible designs. Confusion among designs is exacerbated by the lack of a standardized nomenclature. This article outlines the components of a CCT, common options for each component, and the interaction of options for different components, so that practitioners may more efficiently design CCTs. It also offers a suggestion of nomenclature. },
	keywords = {CAT, classification, computer adaptive testing, computerized adaptive testing, Computerized classification testing},
	author = {Thompson, N. A.}
}
@proceedings {214,
	title = {An investigation of two combination procedures of SPRT for three-category classification decisions in computerized classification test},
	journal = {annual meeting of the American Educational Research Association},
	year = {2004},
	note = {annual meeting of the American Educational Research Association, San Antonio},
	month = {04/2004},
	address = {San Antonio, Texas},
	keywords = {computerized adaptive testing, Computerized classification testing, sequential probability ratio testing},
	author = {Jiao, H. and Wang, S and Lau, CA}
}
@article {115,
	title = {Computerized adaptive testing for classifying examinees into three categories},
	journal = {Educational and Psychological Measurement},
	volume = {60},
	number = {5},
	year = {2000},
	pages = {713-34},
	abstract = {The objective of this study was to explore the possibilities for using computerized adaptive testing in situations in which examinees are to be classified into one of three categories.Testing algorithms with two different statistical computation procedures are described and evaluated. The first computation procedure is based on statistical testing and the other on statistical estimation. Item selection methods based on maximum information (MI) considering content and exposure control are considered. The measurement quality of the proposed testing algorithms is reported. The results of the study are that a reduction of at least 22\% in the mean number of items can be expected in a computerized adaptive test (CAT) compared to an existing paper-and-pencil placement test. Furthermore, statistical testing is a promising alternative to statistical estimation. Finally, it is concluded that imposing constraints on the MI selection strategy does not negatively affect the quality of the testing algorithms},
	keywords = {computerized adaptive testing, Computerized classification testing},
	author = {Theo Eggen and Straetmans, G. J. J. M.}
}
