To run: python run.py -w <directory> {config,train,test,stat,...}
If this code helps with your studies, please kindly cite the following publication:
@article{liu2019ekt,
title={EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction},
author={Liu, Qi and Huang, Zhenya and Yin, Yu and Chen, Enhong and Xiong, Hui and Su, Yu and Hu, Guoping},
journal={IEEE Transactions on Knowledge and Data Engineering},
year={2019},
publisher={IEEE}
}
Also, visit https://base.ustc.edu.cn for more of our works.
python run.py -w ws/test config EKTA -h # check parameters available
python run.py -w ws/test config EKTA <arguments>
Specify dataset to train (no dataset publicly available, but demo dataset is on the way)
python run.py -w ws/test train -d full -N 1
Test predicting result on sequeence #10000:
python run.py -w ws/test test -d full_test -s 0.10000
Results are under ws/test/results. To evaluate:
python run.py stat ws/test/results/school.0.10000