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Enhancing Effort-Moderated Item Response Theory Models by Evaluating a Two-Step Estimation Method and

Bowen Wang1, Corinne Huggins-Manley1, Huan Kuang2

  • 1University of Florida, Gainesville, USA.

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Summary
This summary is machine-generated.

Rapid guessing in tests can skew results. This study shows the two-step effort-moderated item response theory (EM-IRT) model accurately estimates abilities, outperforming traditional methods even with varied guessing patterns.

Keywords:
effort-moderated item response theorymultidimensionalityparameter estimationrapid-guessing behavior

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Area of Science:

  • Psychometrics
  • Educational Measurement
  • Cognitive Psychology

Background:

  • Rapid-guessing behavior compromises accurate estimation of item and person parameters in testing.
  • Unbiased ability estimates require effective modeling of rapid-guessing patterns.

Purpose of the Study:

  • To propose and evaluate alternative modeling approaches for analyzing response data with rapid-guessing patterns.
  • To compare the performance of these models against the traditional effort-moderated item response theory (EM-IRT) model.

Main Methods:

  • Proposed and evaluated three alternative models: a two-step EM-IRT model and two effort-moderated multidimensional models (EM-MIRT) with between-item and within-item structures.
  • Compared parameter recovery accuracy of these models with the traditional EM-IRT model under various simulated conditions.

Main Results:

  • The two-step EM-IRT and between-item EM-MIRT models consistently outperformed the traditional EM-IRT model.
  • The two-step EM-IRT model demonstrated the best performance, particularly for ability and item difficulty parameter estimation.
  • Different rapid-guessing patterns did not impact the two-step EM-IRT model's performance.

Conclusions:

  • The two-step EM-IRT model is accurate and efficient for estimating ability in the presence of rapid-guessing responses.
  • The between-item EM-MIRT model offers an alternative when no significant mean ability difference exists between rapid-guessers and non-rapid-guessers.