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adaptivetesting is a Python package that can be used to simulate and evaluate custom CAT scenarios as well as implement them in real-world testing scenarios from a single codebase

Project description

adaptivetesting

Unittests Deploy to PyPi

adaptivetesting is a Python package for computer-aided adaptive testing that can be used to simulate and implement custom adaptive tests in real-world testing scenarios.

Getting Started

Required Python version: >= 3.11 (other versions may work, but they are not officially supported)

pip install git+https://github.com/condecon/adaptivetesting

Other dependencies:

  • numpy

Features

  • Rasch Model
  • fast Maximum Likelihood Estimation of the current ability
  • Item selection with Urry's rule
  • Fully customizable testing behavior

The package comes with two testing procedures:

  • Default implementation
  • Semi-Adaptive implementation

Custom testing procedures can be implemented by implementing the abstract class AdaptiveTest. Any existing functionality can be overridden while still retaining full compatability with the packages' functionality. For more information, please consult the documentation for the AdaptiveTest class (AdaptiveTest documentation).

Implementations

Default implementation

Schematic overview of the Default implementation

Semi-Adaptive implementation

Schematic overview of the Semi-Adaptive implementation

Documentation

Extensive documentation of all programm code is available at /documentation.

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