Generative AI and Knowledge Graph Empowered Digital-Intelligent Collaborative Teaching System

The rapid development of artificial intelligence (AI) and digital transformation is driving higher education to shift from mass education to personalized education. However, current digital and intelligent technologies are primarily applied to teaching without fully exploring their potential. Thus, based on generative AI and knowledge graphs, a digital-intelligent collaborative teaching system is proposed to construct a novel intelligent teaching environment that supports active learning and collaborative teaching. The system focuses on the cultivation of talents in electronic information fields. Specifically, it leverages large models to develop a three-dimensional knowledge graph for professional courses, enabling the recommendation of personalized learning paths for students. Meanwhile, an intelligent formula derivation engine is designed to facilitate human-machine collaborative problem setting and solving, while establishing connections between knowledge and application based on the given problems. Moreover, a wireless communication agent incorporating teacher knowledge base is constructed to provide students with professional companion learning tools. The proposed system implemented over one semester in three classes with 144 students significantly enhances teaching quality and learning effectiveness, earning positive recognition from students. This provides a low-cost, high-efficiency digital-intelligent education model for new engineering education.