基于本地部署的RAG系统，帮学生智能选课并理解课程依赖关系。
A Locally Deployed RAG-Based Academic Advising System for Course Selection
- 用大模型结合结构化课程大纲检索，实现精准课程推荐。
- 支持个性化学习规划，帮助学生理清课程先后顺序。
- 本地部署保障隐私，适合高校教学管理部门使用。
根据课程间的先修要求合理安排课程顺序，对学生的知识与技能全面发展至关重要。然而，学生独立制定课程计划时常受限于认知能力与信息过载，导致困惑。同时，教育机构因资源有限，难以提供充分的学术指导。为此，我们提出一种基于课程大纲信息的本地部署RAG学术指导系统。通过将大语言模型与结构化课程数据检索相结合，该系统旨在以保护隐私的方式支持课程选择、先修条件理解及个性化学习规划。
原文摘要 · Abstract (English)
The correct sequence of courses in the curriculum based on prerequisites between courses is of great importance for students to develop their knowledge and skills holistically. However, students crafting this sequence in isolation frequently struggle with recognition limitations and information overload that leads to confusion. Simultaneously, education institutions encounter difficulties in providing adequate academic advice for the correct sequence due to limited education resources. To address these challenges, we propose a locally deployed RAG-based academic advising system grounded in syllabus information. By combining large language models with retrieval from structured syllabus data, the system is designed to support course selection, prerequisite understanding, and personalized study planning in a privacy-preserving manner.
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