EduStudio

<p float="left"> <img src="https://img.shields.io/badge/python-v3.8+-blue"> <img src="https://img.shields.io/badge/pytorch-v1.10+-blue"> <img src="https://img.shields.io/badge/License-MIT-blue"> <img src="https://img.shields.io/github/issues/HFUT-LEC/EduStudio.svg"> <a href="https://journal.hep.com.cn/fcs/EN/10.1007/s11704-024-40372-3"> <img src="https://img.shields.io/badge/Paper-EduStudio-blue" alt="Paper EduStudio Badge"> </a> </p>

EduStudio is a Unified Library for Student Cognitive Modeling including Cognitive Diagnosis(CD) and Knowledge Tracing(KT) based on Pytorch.

Navigation

| Resource Name | Description | | ------------------------------------------------------------ | ------------------------------------------------------------ | | Eco-Repository | A repository containing resources about student cognitive modeling: papers, datasets, conferences&journals | | Eco-Leaderboard | A leaderboard demonstrating performance of implemented models | | EduStudio Documentation | The document for EduStudio usage | | Reference Table | The reference table demonstrating the corresponding templates of each model |

Description

EduStudio first decomposes the general algorithmic workflow into six steps: configuration reading, data prepration, model implementation, training control, model evaluation, and Log Storage. Subsequently, to enhance the reusability and scalability of each step, we extract the commonalities of each algorithm at each step into individual templates for templatization.

<p align="center"> <img src="assets/framework.png" alt="EduStudio Architecture" width="600"> <br> <b>Figure</b>: Overall Architecture of EduStudio </p>

Quick Start

Install EduStudio:

pip install -U edustudio

Example: Run NCDM model:

from edustudio.quickstart import run_edustudio

run_edustudio(
    dataset='FrcSub',
    cfg_file_name=None,
    traintpl_cfg_dict={
        'cls': 'GeneralTrainTPL',
    },
    datatpl_cfg_dict={
        'cls': 'CDInterExtendsQDataTPL'
    },
    modeltpl_cfg_dict={
        'cls': 'NCDM',
    },
    evaltpl_cfg_dict={
        'clses': ['PredictionEvalTPL', 'InterpretabilityEvalTPL'],
    }
)

To find out which templates are used for a model, we can find in the Reference Table

Citation

@article{Le WU:198342,
author = {Le WU, Xiangzhi CHEN, Fei LIU, Junsong XIE, Chenao XIA, Zhengtao TAN, Mi TIAN, Jinglong LI, Kun ZHANG, Defu LIAN, Richang HONG, Meng WANG},
title = {EduStudio: towards a unified library for student cognitive modeling},
publisher = {Front. Comput. Sci.},
year = {2025},
journal = {Frontiers of Computer Science},
volume = {19},
number = {8},
eid = {198342},
numpages = {0},
pages = {198342},
keywords = {open-source library;student cognitive modeling;intelligence education},
url = {https://journal.hep.com.cn/fcs/EN/abstract/article_47994.shtml},
doi = {10.1007/s11704-024-40372-3}
}

License

EduStudio uses MIT License.