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CAT

Computerized Adaptive Testing Package, including the following models and strategies.

  • Item Response Theory (IRT)

    • MaximumFisherInformation (MFI) strategy
    • Kullback-Leibler Information (KLI) strategy
    • Model-Agnostic Adaptive Testing (MAAT) strategy
    • Bounded Ability Estimation Adaptive Testing (BECAT) strategy
    • Bilevel Optimization-Based Computerized Adaptive Testing (BOBCAT) strategy
    • Neural Computerized Adaptive Testing (NCAT) strategy
  • Multidimensional Item Response Theory (MIRT)

    • D-Optimality (D-opt) strategy
    • Multivariate Kullback-Leibler Information (MKLI) strategy
    • Model-Agnostic Adaptive Testing (MAAT) strategy
    • Bilevel Optimization-Based Computerized Adaptive Testing (BOBCAT) strategy
    • Neural Computerized Adaptive Testing (NCAT) strategy
  • Neural Cognitive Diagnosis (NCD)

    • Model-Agnostic Adaptive Testing (MAAT) strategy
    • Bounded Ability Estimation Adaptive Testing (BECAT) strategy

BECAT strategy comes from paper A Bounded Ability Estimation for Computerized Adaptive Testing(https://nips.cc/virtual/2023/poster/70224)

Installation

Git and install by pip

pip install -e .

Quick Start

See the examples in scripts directory.

utils

Visualization

By default, we use tensorboard to help visualize the reward of each iteration, see demos in scripts and use

tensorboard --logdir /path/to/logs

to see the visualization result.

Release files for EduCAT 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for EduCAT 0.0.1
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Table of built distributions (wheels) for EduCAT 0.0.1
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EduCAT-0.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 31.2 kB

Release files / EduCAT-0.0.1.tar.gz

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