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…

Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…

In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…

Item selection is a core component in computerized adaptive testing (CAT). Several studies have evaluated new and classical selection methods; however, the few that have applied such methods to the use of polytomous items have reported conflicting results. To clarify these discrepancies and further investigate selection method properties, six…

A method is presented for incorporating a large number of constraints on adaptive item selection in the construction of computerized adaptive tests. The method, which emulates practices of expert test specialists, is illustrated for verbal and quantitative measures. Its foundation is application of a weighted deviations model and algorithm. (SLD)

To determine which produced the most accurate item parameter estimates, four methods of item response theory were evaluated: (1) heuristic estimates; (2) the ANCILLES program; (3) the LOGIST program; and (4) the ASCAL program. LOGIST and ASCAL produced estimates of superior and essentially equivalent accuracy. (SLD)