01458nas a2200181   4500008004100000245008200041210006900123260001300192490000800205520080800213653000801021653001901029653003001048653003401078653004001112100001801152856010601170       2007                        eng d00aA practitioner's guide to variable-length computerized classification testing0 apractitioners guide to variablelength computerized classificatio  c7/1/20090 v12 3 aVariable-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. 10aCAT10aclassification10acomputer adaptive testing10acomputerized adaptive testing10aComputerized classification testing1 aThompson, N A  uhttp://mail.iacat.org/content/practitioners-guide-variable-length-computerized-classification-testing00710nas a2200157   4500008004100000245013900041210006900180260003200249653003400281653004000315653004100355100001200396700001200408700001200420856012000432       2004                        eng d00aAn investigation of two combination procedures of SPRT for three-category classification decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat  aSan Antonio, Texasc04/200410acomputerized adaptive testing10aComputerized classification testing10asequential probability ratio testing1 aJiao, H1 aWang, S1 aLau, CA  uhttp://mail.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-classification-decisions01599nas a2200157   4500008004100000245008200041210006900123300001100192490000700203520101400210653003401224653004001258100001601298700002401314856010301338       2000                        eng d00aComputerized adaptive testing for classifying examinees into three categories0 aComputerized adaptive testing for classifying examinees into thr  a713-340 v603 aThe 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 algorithms10acomputerized adaptive testing10aComputerized classification testing1 aEggen, Theo1 aStraetmans, G J J M  uhttp://mail.iacat.org/content/computerized-adaptive-testing-classifying-examinees-three-categories