Computerized adaptive testing for forced-choice ipsative items

Xuelan QIU, Wen Chung WANG

Research output: Contribution to conferencePaper

Abstract

There are some developments in IRT models for ipsative tests. Among them, the Rasch ipsative model appears the most promising. To facilitate its applications, in this study we developed computerized adaptive testing algorithms under this model, and conducted simulations to evaluate their performance. The simulation results showed that using the Fisher information criterion for item selection could achieve precise latent traits estimates; and the longer the test, the more precise the estimates would be. In addition, a procedure was proposed to control statement exposure within examinees and the results showed that the procedure could control the statement exposure successfully and yield comparably accurate latent trait estimates.
Original languageEnglish
Publication statusPublished - Apr 2014

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Citation

Qiu, X.-L., & Wang, W.-C. (2014, April). Computerized adaptive testing for forced-choice ipsative items. Paper presented at the 2014 AERA Annual Meeting, Philadelphia, Pennsylvania.