大语言模型赋能研究生教育质量提升——基于“双师制”创新模式的资源配置与个性化培养路径

Large Language Models Empower the Improvement of Postgraduate Education Quality—Resource Allocation and Personalized Cultivation Path Based on the Innovative “Dual-Mentor” Model

摘要: 研究生教育作为高等教育的重要组成部分，面临着规模化培养与个性化指导之间的矛盾，传统“一对一”导师制受限于师资配比与时间成本，难以满足日益增长的学术训练需求。如何将LLM嵌入研究生培养体系，构建人机协同的“双师制”模式，成为破解传统困境的关键。文章创新性构建“人类导师–LLM副导师–研究生”三角协同框架，提出“LLM副导师”角色分工机制，通过任务解耦与资源重组，实现教育供给侧的范式变革。

Abstract: Postgraduate education, as an important part of higher education, is confronted with the contradiction between large-scale cultivation and individualized guidance. The traditional “one-to-one” mentorship system is restricted by the ratio of teachers to students and time cost, making it difficult to meet the growing demand for academic training. How to integrate LLM into the postgraduate training system and build a human-machine collaborative “dual-mentor” model has become the key to breaking through the traditional predicament. This paper innovatively constructs a triangular collaborative framework of “human mentor-LLM dual-mentor-postgraduate”, and proposes a role division mechanism of “LLM dual-mentor”. Through task decoupling and resource reorganization, it realizes a paradigm shift in the supply side of education.