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Summary
This summary is machine-generated.

This study introduces a new unfolding model to evaluate rater accuracy in performance assessments. The hyperbolic cosine model (HCM) offers a promising framework for assessing rating quality in rater-mediated evaluations.

Keywords:
hyperbolic cosine modelrater accuracyrater-mediated assessmentsunfolding models

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Assessment Quality

Background:

  • Increasing global performance assessments necessitate improved rater quality evaluation methods.
  • Current methods for assessing rater accuracy require further development.
  • Ensuring reliable ratings is crucial for valid performance assessments.

Purpose of the Study:

  • To introduce and evaluate an unfolding model for examining rater accuracy.
  • To define accuracy based on the difference between observed and expert ratings.
  • To explore the utility of the hyperbolic cosine model (HCM) in this context.

Main Methods:

  • Developed an unfolding model to categorize accuracy into three latent levels: inaccurate below, accurate, and inaccurate above expert ratings.
  • Utilized dichotomous accuracy ratings (0 = inaccurate, 1 = accurate).
  • Applied the hyperbolic cosine model (HCM) to analyze accuracy data from a statewide writing assessment.

Main Results:

  • The unfolding model successfully categorized rater accuracy into distinct latent levels.
  • The hyperbolic cosine model (HCM) demonstrated effectiveness in analyzing dichotomous accuracy ratings.
  • Results suggest HCM is a viable statistical approach for rater accuracy assessment.

Conclusions:

  • The proposed unfolding model, utilizing HCM, is a promising method for evaluating rater accuracy.
  • HCM provides a valuable interpretive framework for understanding rating quality in rater-mediated assessments.
  • This approach can enhance the overall quality and validity of performance assessments.