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Application of Optimal Designs to Item Calibration

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  • Hung-Yi Lu

Abstract

In computerized adaptive testing (CAT), examinees are presented with various sets of items chosen from a precalibrated item pool. Consequently, the attrition speed of the items is extremely fast, and replenishing the item pool is essential. Therefore, item calibration has become a crucial concern in maintaining item banks. In this study, a two-parameter logistic model is used. We applied optimal designs and adaptive sequential analysis to solve this item calibration problem. The results indicated that the proposed optimal designs are cost effective and time efficient.

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  • Hung-Yi Lu, 2014. "Application of Optimal Designs to Item Calibration," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-8, September.
    • Handle: RePEc:plo:pone00:0106747
    DOI: 10.1371/journal.pone.0106747
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    Cited by:

    1. Mahmood Ul Hassan & Frank Miller, 2019. "Optimal Item Calibration for Computerized Achievement Tests," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 1101-1128, December.
    2. Ul Hassan, Mahmood & Miller, Frank, 2021. "An exchange algorithm for optimal calibration of items in computerized achievement tests," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    3. Yinhong He & Ping Chen, 2020. "Optimal Online Calibration Designs for Item Replenishment in Adaptive Testing," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 35-55, March.

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