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BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing

This is an official repository of the paper BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing to be presented at IJCAI 2021.

In this paper, we propose BOBCAT, a Bilevel Optimization-Based framework for CAT to directly learn a data-driven question selection algorithm from training data. We show that BOBCAT outperforms existing CAT methods (sometimes significantly) at reducing test length.

Environment Setup

This repository uses the following packages in Python3.

torch==1.7.1

Training

You can download the preprocessed datasets from Google Drive in /data/ folder. Preprocessing scirpts can be found in utils/ folder.

python train.py\
    --dataset {eedi-1 or eedi-3 or assit2009 or junyi or ednet}
    --model {base-sampling where base is binn/biirt and sampling is random/active/unbiased/biased}\ 
    --n_query {1, 3, 5, or 10}
    --cuda

Hyperparameter ranges are:

hyperparameters = [
    [('dataset',), ['ednet', 'eedi-1', 'eedi-3', 'assist2009', 'junyi']],
    [('model',), ['biirt-active', 'biirt-random', 'biirt-unbiased','biirt-biased', 'binn-active', 'binn-random', 'binn-unbiased','binn-biased']],
    [('fold',), [ 1, 2, 3, 4, 5 ]],
    [('hidden_dim'), [256]],
    [('lr',), [ 1e-3 ]],
    [('inner_lr',), [ 2e-1, 1e-1, 5e-2]],
    [('meta_lr',), [ 1e-4 ]],
    [('inner_loop',), [ 5 ]],
    [('policy_lr',), [2e-3,  2e-4]],
    [('n_query',), [1, 3, 5, 10]]
]

Citation

If you find this code useful in your research then please cite

@inproceedings{ghosh-bobcat,
  title     = {BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing},
  author    = {Ghosh, Aritra and Lan, Andrew},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Zhi-Hua Zhou},
  pages     = {2410--2417},
  year      = {2021},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2021/332},
  url       = {https://doi.org/10.24963/ijcai.2021/332},
}

Contact: Aritra Ghosh (aritraghosh.iem@gmail.com).

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