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Exploring Within-Rater Category Ordering: A Simulation Study Using Adjacent-Categories Mokken Scale Analysis.

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Summary

This study shows that adjacent-categories Mokken scale analysis (ac-MSA) models can effectively identify disordered rating scales in educational performance assessments. These models help ensure accurate interpretation of student achievement ratings.

Keywords:
Mokken scalingnonparametric IRTperformance assessmentratersrating scales

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Area of Science:

  • Educational measurement
  • Psychometrics
  • Statistics

Background:

  • Educational performance assessments rely on ordered rating scales for accurate interpretation.
  • Empirical verification of rating scale order is crucial but often overlooked.
  • Traditional models may impose unintended ordering constraints.

Purpose of the Study:

  • To evaluate adjacent-categories Mokken scale analysis (ac-MSA) models for assessing rating scale category ordering in performance assessments.
  • To determine the sensitivity of ac-MSA models to disordered rating scales at the individual rater level.
  • To provide a method for verifying rating scale assumptions in educational measurement.

Main Methods:

  • Application of adjacent-categories formulation of polytomous Mokken scale analysis (ac-MSA) models.
  • Utilized simulated data for rigorous testing of the ac-MSA models.
  • Built upon preliminary real-data analysis of ac-MSA in performance assessments.

Main Results:

  • ac-MSA models demonstrated sensitivity to disordered rating scale categories within individual raters.
  • The study confirmed the utility of ac-MSA for identifying deviations from expected rating scale order.
  • Simulated data analysis supported the findings from preliminary real-data applications.

Conclusions:

  • ac-MSA models offer a viable statistical approach to empirically verify rating scale assumptions in educational performance assessments.
  • These models can help researchers and practitioners identify and address potential biases introduced by disordered rating scales.
  • The findings have implications for improving the reliability and validity of rater-mediated assessments.