AI-empowered smart teaching reform of embedded system courses for disciplinary competitions and industrial needs

Abstract

Against the background of AI-empowered education, to better implement the Ministry of Education’s guideline of adopting a student-centered philosophy and comprehensively enhance talent cultivation capacity, this paper takes the course Principles and Applications of Embedded Systems for the electronic information engineering major at Dongguan City University as a case study, and explores a smart hierarchical project-based teaching reform path guided by disciplinary competitions and aligned with cutting-edge industrial demands. Since 2022, the original teaching content has been optimized by designing graded project tasks, using intelligent-assisted learning tools, and implementing dynamic process assessment. Classroom practice demonstrates that the updated teaching content and mode can effectively stimulate students' learning enthusiasm. Achievements from the National Undergraduate Embedded Chip and System Design Competition (China) further verify that this teaching reform can better adapt to the demands of the embedded industry and the requirements of disciplinary competitions. It significantly improves students' engineering practice ability as well as innovative thinking and teamwork competence. This research also provides a valuable reference for the AI-empowered teaching reform of embedded system courses in similar private undergraduate universities.