A Multi-Agent AI Framework for Personalized Academic Advising and Graduation Pathway Recommendation
Fayeeza Shaikh
Department of Computer Science
Faculty Supervisor: Sara El Alaoui
Current academic advising and degree audit systems are largely static, unable to adapt to evolving degree requirements across catalog years or provide transparent reasoning for course recommendations. This project presents an AI-driven academic advising system that analyzes student Degree Progress Reports (DPRs) against official university bulletin requirements and generates personalized graduation pathways. The system encodes degree requirements for select undergraduate majors within the College of Science and Engineering at San Francisco State University, spanning six catalog years (2020–2026). This work explores how AI can deliver personalized, explainable academic advising to provide students with initial guidance and triage support, which can then be reinforced by human advisors for smoother transitions and a more effective advising workflow.