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Developing Multistage Tests Using D-Scoring Method.

Kyung Chris T Han1, Dimiter M Dimitrov2, Faisal Al-Mashary3

  • 1Graduate Management Admission Council®, Reston, VA, USA.

Educational and Psychological Measurement
|September 7, 2019
PubMed
Summary
This summary is machine-generated.

The D-scoring method, combining item response theory and classical test theory, shows promise for adaptive testing. Multistage testing (MST) with D-scoring improves measurement precision and efficiency compared to linear tests.

Keywords:
item calibrationmultistage testingscoringsimulationtest construction

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Psychological Measurement

Background:

  • The D-scoring method integrates item-level difficulty from Item Response Theory (IRT) with the simplicity of Classical Test Theory (CTT).
  • It offers advantages like item difficulty information and score computation reflecting item difficulties, while maintaining CTT's ease of use and relaxed sample size requirements.
  • Its unique blend of features has led to rapid adoption in educational and psychological measurement.

Purpose of the Study:

  • To develop and evaluate Multistage Testing (MST) mechanisms utilizing the D-scoring method.
  • To propose and implement a novel framework for conducting MST simulations under the D-scoring approach.
  • To assess the score recovery performance and comparability of D-scoring within MST designs.

Main Methods:

  • Development and comparison of multiple MST algorithms tailored for the D-scoring method.
  • Implementation of a new simulation framework specifically designed for D-scoring based MST.
  • Evaluation of score comparability across different MST routes and measurement precision/efficiency.

Main Results:

  • Promising score recovery performance was observed for MST employing the D-scoring method.
  • Score comparability was successfully maintained across various MST paths.
  • MST utilizing the D-scoring method demonstrated enhanced measurement precision and efficiency compared to linear D-scoring tests.

Conclusions:

  • The D-scoring method is well-suited for adaptive testing designs like MST due to its inherent item-level difficulty information.
  • The developed MST framework provides a viable approach for simulating and evaluating D-scoring based adaptive tests.
  • MST with D-scoring offers significant advantages in measurement precision and efficiency, outperforming traditional linear tests.