@article {73,
	title = {Controlling item exposure and test overlap on the fly in computerized adaptive testing},
	journal = {British Journal of Mathematical and Statistical Psychology},
	volume = {61},
	number = {2},
	year = {2008},
	note = {Chen, Shu-YingLei, Pui-WaLiao, Wen-HanResearch Support, Non-U.S. Gov{\textquoteright}tEnglandThe British journal of mathematical and statistical psychologyBr J Math Stat Psychol. 2008 Nov;61(Pt 2):471-92. Epub 2007 Jul 23.},
	month = {Nov},
	pages = {471-92},
	edition = {2007/07/26},
	abstract = {This paper proposes an on-line version of the Sympson and Hetter procedure with test overlap control (SHT) that can provide item exposure control at both the item and test levels on the fly without iterative simulations. The on-line procedure is similar to the SHT procedure in that exposure parameters are used for simultaneous control of item exposure rates and test overlap rate. The exposure parameters for the on-line procedure, however, are updated sequentially on the fly, rather than through iterative simulations conducted prior to operational computerized adaptive tests (CATs). Unlike the SHT procedure, the on-line version can control item exposure rate and test overlap rate without time-consuming iterative simulations even when item pools or examinee populations have been changed. Moreover, the on-line procedure was found to perform better than the SHT procedure in controlling item exposure and test overlap for examinees who take tests earlier. Compared with two other on-line alternatives, this proposed on-line method provided the best all-around test security control. Thus, it would be an efficient procedure for controlling item exposure and test overlap in CATs.},
	keywords = {*Decision Making, Computer-Assisted, *Models, Psychological, Humans},
	isbn = {0007-1102 (Print)0007-1102 (Linking)},
	author = {Chen, S-Y. and Lei, P. W. and Liao, W. H.}
}
@article {249,
	title = {Computerized adaptive testing: a mixture item selection approach for constrained situations},
	journal = {British Journal of Mathematical and Statistical Psychology},
	volume = {58},
	number = {2},
	year = {2005},
	note = {Leung, Chi-KeungChang, Hua-HuaHau, Kit-TaiEnglandBr J Math Stat Psychol. 2005 Nov;58(Pt 2):239-57.},
	month = {Nov},
	pages = {239-57},
	edition = {2005/11/19},
	abstract = {In computerized adaptive testing (CAT), traditionally the most discriminating items are selected to provide the maximum information so as to attain the highest efficiency in trait (theta) estimation. The maximum information (MI) approach typically results in unbalanced item exposure and hence high item-overlap rates across examinees. Recently, Yi and Chang (2003) proposed the multiple stratification (MS) method to remedy the shortcomings of MI. In MS, items are first sorted according to content, then difficulty and finally discrimination parameters. As discriminating items are used strategically, MS offers a better utilization of the entire item pool. However, for testing with imposed non-statistical constraints, this new stratification approach may not maintain its high efficiency. Through a series of simulation studies, this research explored the possible benefits of a mixture item selection approach (MS-MI), integrating the MS and MI approaches, in testing with non-statistical constraints. In all simulation conditions, MS consistently outperformed the other two competing approaches in item pool utilization, while the MS-MI and the MI approaches yielded higher measurement efficiency and offered better conformity to the constraints. Furthermore, the MS-MI approach was shown to perform better than MI on all evaluation criteria when control of item exposure was imposed.},
	keywords = {*Computer-Aided Design, *Educational Measurement/methods, *Models, Psychological, Humans, Psychometrics/methods},
	isbn = {0007-1102 (Print)0007-1102 (Linking)},
	author = {Leung, C. K. and Chang, Hua-Hua and Hau, K. T.}
}
