Online education platforms, leveraging the internet to distribute education
resources, seek to provide convenient education but often fall short in
real-time communication with students. They often struggle to offer
personalized education resources due to the challenge of addressing the diverse
obstacles students encounter throughout their learning journey. Recently, the
emergence of large language models (LLMs), such as ChatGPT, offers the
possibility for resolving this issue by comprehending individual requests.
Although LLMs have been successful in various fields, creating an LLM-based
education system is still challenging for the wide range of educational skills
required. This paper reviews the recently emerged LLM researches related to
educational capabilities, including mathematics, writing, programming,
reasoning, and knowledge-based question answering, with the aim to explore
their potential in constructing the next-generation intelligent education
system. Based on the current development status, we further outline two
approaches for an LLM-based education system: a unified approach and a
mixture-of-expert (MoE) approach. Finally, we explore the challenges and future
directions, providing new research opportunities and perspectives on adapting
LLMs for education.

基于大型语言模型的教育系统研究，评估其在教育能力方面的潜力，并提出统一和专家混合两种方法构建下一代智能教育系统，同时探讨了挑战和未来发展方向。