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Dual-Objective Item Selection Methods in Computerized Adaptive Test Using the Higher-Order Cognitive Diagnostic

Chongqin Xi1, Dongbo Tu1, Yan Cai1

  • 1School of Psychology, Jiangxi Normal University, Nanchang, China.

Applied Psychological Measurement
|July 11, 2022
PubMed
Summary
This summary is machine-generated.

New item selection methods for higher-order cognitive diagnostic computerized adaptive testing (CD-CAT) improve the accuracy of estimating both general abilities and cognitive profiles. These methods enhance precision by considering the interplay between general abilities and attribute profiles.

Keywords:
cognitive diagnostic computerized adaptive testingdual-objectivehigher-order cognitive diagnostic modelsitem selection method

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Area of Science:

  • Educational Measurement and Psychometrics
  • Cognitive Psychology
  • Computerized Adaptive Testing (CAT)

Background:

  • Higher-order cognitive diagnostic computerized adaptive testing (CD-CAT) aims to assess general abilities and detailed cognitive profiles efficiently using a single model and calibration process.
  • Existing item selection methods in higher-order CD-CAT primarily focus on attribute profiles, potentially compromising the precision of general ability estimation.

Purpose of the Study:

  • To develop and evaluate novel item selection methods for higher-order CD-CAT that simultaneously consider general abilities and attribute profiles.
  • To enhance the accuracy of estimating both general abilities and cognitive profiles within a higher-order CD-CAT framework.

Main Methods:

  • Proposed two new item selection methods for higher-order CD-CAT, integrating general abilities and attribute profiles.
  • These methods are based on Shannon entropy and the generalized deterministic, inputs, noisy "and" gate (G-DINA) model discrimination index (GDI).
  • Evaluated method performance through simulation studies.

Main Results:

  • The proposed methods demonstrated superior accuracy in estimating both general abilities and cognitive profiles compared to existing methods.
  • The new methods also showed significant advantages in efficient item pool utilization.
  • Item responses were found to be influenced by a combination of general abilities and attribute profiles.

Conclusions:

  • The developed item selection methods offer a more precise and efficient approach for higher-order CD-CAT.
  • These methods effectively address the limitations of existing approaches by considering the combined influence of general abilities and attribute profiles.
  • The findings support the advancement of higher-order CD-CAT for comprehensive cognitive assessment.