AI-Driven Integration of Educational Resources and Intelligent Questions and Answers Systems

This research presents an innovative educational resource integration and intelligent Questions and Answers (Q&A) system for Sichuan University-Pittsburgh Institute (SCUPI), combining Retrieval-Augmented Generation (RAG) technology with Large Language Models (LLMs). Through controlled experiments with admission-related queries, our system demonstrates significant advantages over baseline models in three aspects: response accuracy through knowledge integration, information boundary management, and contextual awareness in multi-turn conversations. The findings provide valuable insights for implementing AI consultation systems in international higher education programs, particularly in managing admission inquiries.