Improving Item-Exposure Control in Adaptive Testing

Wim J. van der Linden, Seung W. Choi

    Research output: Contribution to journalArticleAcademicpeer-review

    7 Citations (Scopus)


    One of the methods of controlling test security in adaptive testing is imposing random item-ineligibility constraints on the selection of the items with probabilities automatically updated to maintain a predetermined upper bound on the exposure rates. Three major improvements of the method are presented. First, a few modifications to improve the initialization of the method and accelerate the impact of its feedback mechanism on the observed item-exposure rates are introduced. Second, the case of conditional item-exposure control given the uncertainty of examinee's ability parameter is addressed. Third, although rare for a well-designed item pool, when applied in combination with the shadow-test approach to adaptive testing the method may meet occasional infeasibility of the shadow-test model. A big M method is proposed that resolves the issue. The practical advantages of the improvements are illustrated using simulated adaptive testing from a real-world item pool under a variety of conditions.

    Original languageEnglish
    Pages (from-to)405-422
    JournalJournal of educational measurement
    Issue number3
    Publication statusPublished - 1 Sep 2020


    • n/a OA procedure


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