OptimalCAT

OptimalCAT is a production-grade Computer Adaptive Testing (CAT) engine designed for both psychometricians running simulations and IT engineers deploying to production.

It builds on the shadow-test approach and leverages state-of-the-art Mathematical Programming solvers to deliver tailored, optimal tests to every student. It ensures that test blueprints and constraints are always met, and measurement accuracy is maximized.

The engine is built as a microservice with a REST API interface. It can integrate seamlessly into test delivery systems.

shadow-test approach

We believe every student deserves the most accurate measurement.
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Latest Version:  OptimalCAT-2.5-windows.zip (Manual)

    
Core Team:         Jie Li, PhD
                            Wim J. van der Linden, PhD
                            Richard J. Patz, PhD


Support:              OptimalCAT@outlook.com

CSEM of shadow test vs. theoretical limit