Graph-Enhanced Multi-Activity Knowledge Tracing (GMKT)

Code for our paper:

S. Zhao and S. Sahebi. TGraph-Enhanced Multi-Activity Knowledge Tracing. In Proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023.

If you have any questions, please email szhao2@albany.edu

GMKT Network Architecture:

Prerequisit

numpy
torch
scipy
sklearn
pickle
more_itertools
easydict
matplotlib

How to install and run

git clone https://github.com/persai-lab/ECML-PKDD-GMKT
cd 2023-ECML-PKDD-GMKT
conda env create -f environment.yml
source init_env.sh
python run.py

Cite:

Please cite our paper if you use this code in your own work:

@inproceedings{zhao2023GMKT,
  title={Graph-Enhanced Multi-Activity Knowledge Tracing},
  author={Zhao, Siqian and Sahebi,Shaghayegh},
  booktitle={European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023},
  pages={},
  year={2023},
  organization={Springer}
}

Collarators:

Siqian Zhao: szhao2@albany.edu
Sherry Sahebi: ssahebi@albany.edu

Acknowledgement:

This paper is based upon work supported by the National Science Foundation under Grant No. 2047500.