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Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model

Author

Listed:
  • Minjeong Jeon

    (University of California, Los Angeles)

  • Paul De Boeck

    (Ohio State University KU Leuven)

  • Wim van der Linden

    (Pacific Metrics)

Abstract

We present a novel application of a generalized item response tree model to investigate test takers’ answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated with large-scale mathematics test items. We also describe how the estimated results can be used to study the benefits of answer change and to further detect potential academic cheating.

Suggested Citation

  • Minjeong Jeon & Paul De Boeck & Wim van der Linden, 2017. "Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model," Journal of Educational and Behavioral Statistics, , vol. 42(4), pages 467-490, August.
    • Handle: RePEc:sae:jedbes:v:42:y:2017:i:4:p:467-490
    DOI: 10.3102/1076998616688015
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    References listed on IDEAS

    as
    1. De Boeck, Paul & Partchev, Ivailo, 2012. "IRTrees: Tree-Based Item Response Models of the GLMM Family," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(c01).
    2. Daniel Segall, 1996. "Multidimensional adaptive testing," Psychometrika, Springer;The Psychometric Society, vol. 61(2), pages 331-354, June.
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