Title: A Locally Deployed RAG-Based Academic Advising System for Course Selection

Original: arXiv:2606.02983v1 Announce Type: new

Abstract: Establishing the proper order of classes within a curriculum, governed by course prerequisites, is essential for students to build a comprehensive foundation of knowledge and skills. Yet, when learners attempt to map out this progression independently, they often face constraints in their ability to discern requirements and suffer from information overload, resulting in significant confusion. At the same time, educational institutions struggle to offer sufficient academic guidance regarding these sequences due to resource constraints. To tackle these issues, we introduce a privacy-preserving academic advising system that operates locally and utilizes Retrieval-Augmented Generation (RAG) technology based on syllabus data. This approach integrates large language models with the retrieval of structured syllabus information to assist with course selection, clarify prerequisite relationships, and facilitate personalized study planning.

Source: arXiv Generated at: 2026-06-03 00:00:00 UTC