@article {412,
	title = {Evaluation of selection procedures for computerized adaptive testing with polytomous items},
	journal = {Applied Psychological Measurement},
	volume = {26},
	number = {4},
	year = {2002},
	note = {References .Sage Publications, US},
	pages = {393-411},
	abstract = {In the present study, a procedure that has been used to select dichotomous items in computerized adaptive testing was applied to polytomous items. This procedure was designed to select the item with maximum weighted information. In a simulation study, the item information function was integrated over a fixed interval of ability values and the item with the maximum area was selected. This maximum interval information item selection procedure was compared to a maximum point information item selection procedure. Substantial differences between the two item selection procedures were not found when computerized adaptive tests were evaluated on bias and the root mean square of the ability estimate. },
	keywords = {computerized adaptive testing},
	author = {van Rijn, P. W. and Theo Eggen and Hemker, B. T. and Sanders, P. F.}
}
@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.}
}
