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Introduction to the LIVECAT web-based computerized adaptive testing platform.

Dong Gi Seo1,2, Jeongwook Choi2

  • 1Department of Psychology, College of Social Sciences & Hallym Applied Psychology Institute, Hallym University, Chuncheon, Korea.

Journal of Educational Evaluation for Health Professions
|January 5, 2021
PubMed
Summary
This summary is machine-generated.

LIVECAT is a new web-based platform for computerized adaptive testing (CAT). It offers flexible test creation and management, enabling easy implementation of item response theory (IRT) models for various institutions.

Keywords:
Computerized adaptive testingItem response theoryLikelihood functionsPsychometricsSoftware

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Area of Science:

  • Educational Technology
  • Psychometrics
  • Computer Science

Background:

  • Computerized adaptive testing (CAT) offers personalized assessment experiences.
  • Existing platforms may lack flexibility or require specialized expertise.
  • There is a need for accessible and comprehensive CAT solutions.

Purpose of the Study:

  • Introduce LIVECAT, a web-based platform for computerized adaptive testing.
  • Provide a user-friendly environment for test creation, item banking, and administration.
  • Support various item response theory (IRT) models and scoring methods.

Main Methods:

  • Developed a web-based platform using Amazon Linux, nginx, Apache Tomcat, MariaDB, JAVA8, HTML5/CSS, Javascript, and jQuery.
  • Implemented dichotomous IRT models (Rasch, 1-, 2-, 3-parameter logistic).
  • Integrated maximum likelihood estimation and expected a posteriori scoring, with maximum Fisher information item selection.

Main Results:

  • LIVECAT demonstrated equal or superior performance compared to conventional testing platforms.
  • The platform supports multimedia content integration within test items.
  • Users without psychometric expertise can easily implement CAT.

Conclusions:

  • LIVECAT provides a flexible and accessible solution for computerized adaptive testing.
  • The platform facilitates the implementation of IRT models for diverse institutions.
  • Future updates will include polytomous models and advanced CAT features.