EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education
Yuhao Dan, Zhikai Lei, Yiyang Gu, Yong Li, Jianghao Yin, Jiaju Lin,, Linhao Ye, Zhiyan Tie, Yougen Zhou, Yilei Wang, Aimin Zhou, Ze Zhou, Qin, Chen, Jie Zhou, Liang He, Xipeng Qiu

TL;DR
EduChat is an open-source large-scale language model chatbot designed for personalized, fair, and compassionate education, supporting teachers, students, and parents with educational functions guided by psychological and educational theories.
Contribution
It introduces domain-specific pre-training and system prompt fine-tuning to enhance educational capabilities of LLMs, integrating psychological and educational principles.
Findings
Supports open question answering, essay assessment, Socratic teaching, and emotional support.
Available online with code, data, and models for research and application.
Demonstrates potential for advancing intelligent education through LLMs.
Abstract
EduChat (https://www.educhat.top/) is a large-scale language model (LLM)-based chatbot system in the education domain. Its goal is to support personalized, fair, and compassionate intelligent education, serving teachers, students, and parents. Guided by theories from psychology and education, it further strengthens educational functions such as open question answering, essay assessment, Socratic teaching, and emotional support based on the existing basic LLMs. Particularly, we learn domain-specific knowledge by pre-training on the educational corpus and stimulate various skills with tool use by fine-tuning on designed system prompts and instructions. Currently, EduChat is available online as an open-source project, with its code, data, and model parameters available on platforms (e.g., GitHub https://github.com/icalk-nlp/EduChat, Hugging Face https://huggingface.co/ecnu-icalk ). We also…
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Taxonomy
TopicsAI in Service Interactions · Topic Modeling · Online Learning and Analytics
