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Summary
This summary is machine-generated.

This study simultaneously modeled item position and domain order effects in computerized tests, finding both significantly impact student responses. Domain order effects strongly moderated item position effects, crucial for assessment design.

Keywords:
domain order effectsgeneralized linear mixed modelsitem context effectsitem position effectsmultidimensional item response theory

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Computerized Adaptive Testing

Background:

  • Item context effects influence test responses beyond measured abilities.
  • Previous research often examined single context effects, overlooking simultaneous influences.
  • Computerized tests present unique contextual factors impacting item response theory (IRT) models.

Purpose of the Study:

  • To simultaneously model multiple item context effects in a multidimensional computerized test.
  • To investigate the interplay between item position effects and domain order effects.
  • To provide a more comprehensive understanding of contextual influences on examinee responses.

Main Methods:

  • Utilized a generalized linear mixed model (GLMM) parameterization.
  • Applied the multidimensional Rasch model to data from 1,632 students.
  • Modeled within-block and block position effects, domain order effects, and their interactions.

Main Results:

  • Both item position effects and domain order effects were found to significantly impact item responses.
  • Domain order effects demonstrated a strong moderating influence on item position effects.
  • The simultaneous modeling approach revealed complex interactions between context variables.

Conclusions:

  • Item context effects, including position and domain order, are critical considerations in test design and analysis.
  • Findings have direct implications for the planning and application of mixed domain assessment designs.
  • A more holistic approach to modeling context effects is necessary for accurate psychometric evaluations.