With the development of Artificial Intelligence (AI) technology, AI-empowered education has become the core driving force for the digital and intelligent transformation of education. As a backbone course for the cultivation of talents in the semiconductor industry, semiconductor physics is characterized by its abstractness, dryness, and high knowledge threshold. The emergence of AI has brought both opportunities and challenges to the teaching of this course. This paper first analyzes the challenges brought by AI to teaching, including reduced classroom efficiency, decreased concentration, and fragmented knowledge. Based on this, it explores the pathways for integrating AI into teaching reforms. The results show that this teaching reform helps improve students’ learning outcomes. At the same time, the paper also examines the existing pain points in teaching, such as the potential for AI to mislead information, and looks forward to the in-depth integration of AI and education in the future, providing references for the teaching reform of semiconductor physics.
YI et al. (Sun,) studied this question.