Source code and data set for the paper Monitoring Student Progress for Learning Process-consistent Knowledge Tracing.
The code is the implementation of LPKT and LPKT-S model, and the data set is the public data set ASSIST2012-2013.
If this code helps with your studies, please kindly cite the following publication:
@ARTICLE{9950313,
author={Shen, Shuanghong and Chen, Enhong and Liu, Qi and Huang, Zhenya and Huang, Wei and Yin, Yu and Su, Yu and Wang, Shijin},
journal={IEEE Transactions on Knowledge and Data Engineering},
title={Monitoring Student Progress for Learning Process-Consistent Knowledge Tracing},
year={2022},
volume={},
number={},
pages={1-15},
doi={10.1109/TKDE.2022.3221985}}
- python >= 3.7
- tesorflow-gpu >= 2.0
- numpy
- tqdm
- utils
- pandas
- sklearn
First, download the data file: 2012-2013-data-with-predictions-4-final.csv, then put it in the folder 'data/'
Then, run data_pre.py to preprocess the data set, and run data_save.py {sequence length} to divide the original data set into train set, validation set and test set.
python data_pre.py
python data_save.py 50
Train the model:
python train_lpkt_s.py {fold}
For example:
python train_lpkt_s.py 1 or python train_lpkt_s.py 2
Test the trained the model on the test set:
python test.py {model_name}