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)

Git and install by pip

pip install -e .

See the examples in scripts directory.

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.