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Three Psychometric-Model-Based Option-Scored Multiple Choice Item Design Principles that Enhance Instruction by

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  • 1University of Illinois at Urbana-Champaign: (Statistics: Emeritus), Champaign, USA. w-stout1@illinois.edu.

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|December 13, 2022
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Summary

Three item design principles improve student diagnostic classification on classroom quizzes using diagnostic-classification-modeling (DCM)-based multiple-choice (MC) items. Adhering to these principles boosts correct classification rates for skills and misconceptions, enhancing learning.

Keywords:
Extended RUM (ERUM)Generalized Diagnostic Classifcation Modeling (GDCM)Optimal multiple choice (MC) item (question) designformative assessmentoptimal student diagnostic classificationskills and misconceptions diagnosis

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Cognitive Science

Background:

  • Classroom quizzes often lack precision in diagnosing student skills and misconceptions.
  • Traditional multiple-choice (MC) item design may not fully leverage psychometric models for diagnostic purposes.
  • Diagnostic Classification Models (DCM) offer a framework for understanding item-level attribute mastery.

Purpose of the Study:

  • To propose and validate three item design principles for multiple-choice (MC) items within a diagnostic-classification-modeling (DCM) framework.
  • To enhance the accuracy of student diagnostic classification in classroom assessments.
  • To increase the instructional utility of short MC quizzes by improving attribute diagnosis.

Main Methods:

  • Development of three psychometrically-informed item design principles based on DCM.
  • Application of maximum likelihood estimation for student classification.
  • Demonstration of principles using example MC items and analysis of correct classification rates (CCRs).

Main Results:

  • Adherence to the proposed item design principles significantly increases correct classification rates (CCRs) for attributes, including misconceptions.
  • Simple formulas are provided to calculate the necessary item CCRs for effective diagnosis.
  • The study demonstrates improved diagnostic accuracy for student skills and misconceptions.

Conclusions:

  • The three DCM-based item design principles enhance the diagnostic accuracy of MC quizzes.
  • These principles facilitate the accurate diagnosis of student skills and misconceptions, even with short assessments.
  • Wider adoption of these psychometrically driven item design principles can improve the instructional usefulness of MC quizzes and enhance classroom learning.