@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 = {<p>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\&rsquo; 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.</p>
},
	doi = {10.1177/0146621612439932},
	url = {http://apm.sagepub.com/content/36/3/181.abstract},
	author = {Huebner, Alan and Li, Zhushan}
}
@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 = {<p>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\&rsquo; 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.</p>
},
	doi = {10.1177/0146621612439932},
	url = {http://apm.sagepub.com/content/36/3/181.abstract},
	author = {Huebner, Alan and Li, Zhushan}
}
