An Empirical Evaluation of the Slip Correction in the Four Parameter Logistic Models With Computerized Adaptive Testing

Yung Chin Yen, Rong Guey Ho*, Wen Wei Laio, Li Ju Chen, Ching Chin Kuo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

In a selected response test, aberrant responses such as careless errors and lucky guesses might cause error in ability estimation because these responses do not actually reflect the knowledge that examinees possess. In a computerized adaptive test (CAT), these aberrant responses could further cause serious estimation error due to dynamic item administration. To enhance the robust performance of CAT against aberrant responses, Barton and Lord proposed the four-parameter logistic (4PL) item response theory (IRT) model. However, most studies relevant to the 4PL IRT model were conducted based on simulation experiments. This study attempts to investigate the performance of the 4PL IRT model as a slip-correction mechanism with an empirical experiment. The results showed that the 4PL IRT model could not only reduce the problematic underestimation of the examinees' ability introduced by careless mistakes in practical situations but also improve measurement efficiency.

Original languageEnglish
Pages (from-to)75-87
Number of pages13
JournalApplied Psychological Measurement
Volume36
Issue number2
DOIs
Publication statusPublished - 2012 Mar

Keywords

  • computerized adaptive testing (CAT)
  • four-parameter logistic (4PL) IRT model
  • item response theory (IRT)
  • upper-asymptote parameter

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Psychology (miscellaneous)

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