Research and Practice on the Reform of Experiment Teaching in Software Engineering Courses Empowered by AI Agents

Abstract

With the rapid development of artificial intelligence technology, AI agents, as intelligent systems capable of autonomous perception, decision-making, and task execution, are changing teaching models. In response to the issues in traditional software engineering course laboratory teaching, such as insufficient practical skills development, low student participation, and lack of personalized guidance, propose an AI agent-based experimental teaching reform scheme. It constructs a teacher-student-AI agent collaborative teaching model, deeply integrating AI agents into the entire experimental teaching process, including core aspects such as intelligent code generation, real-time error diagnosis, automated code review, and personalized learning support. By comparing the effects of two rounds of experimental teaching, it was found that students’ project completion, code quality, team collaboration skills, and satisfaction with the teaching model were all significantly improved. This study provides a reference teaching reform path and practical scheme for software engineering course experimental teaching in the AI era.