Educhat: A Large-scale Language Model-based Chatbot System For Intelligent Education

Dan Yuhao, Lei Zhikai, Gu Yiyang, Li Yong, Yin Jianghao, Lin Jiaju, Ye Linhao, Tie Zhiyan, Zhou Yougen, Wang Yilei, Zhou Aimin, Zhou Ze, Chen Qin, Zhou Jie, He Liang, Qiu Xipeng. Arxiv 2023

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Applications Fine Tuning Has Code Pretraining Methods Prompting Reinforcement Learning Tools Training Techniques

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 prepare a demonstration of its capabilities online (https://vimeo.com/851004454). This initiative aims to promote research and applications of LLMs for intelligent education.

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