The Application of AI Agents and Knowledge Bases in College English Teaching Reform for Better Teacher-Student Interaction and Autonomous Learning

This study addresses college English classroom teaching reform in the AI era, aiming to overcome traditional limitations, such as weak teacher-student interaction, insufficient autonomy, and uneven proficiency levels, to meet language communication and cross-cultural needs. The reform drives competence-based, technology-enabled transformation via a customized ChatGLM “English Learning Tutor” based on authoritative knowledge bases, and the ima.copilot knowledge base, utilizing Knowledge Retrieval Enhancement (RAG) technology to reduce AI hallucinations. Results show teachers saved 70% of their time on grading and 60% of their time on exercise design; CCMC pilot students achieved 15-20% higher CET-4/6 writing/translation scores, 20-30% better group problem-solving, and enhanced personalized feedback. Prioritizing AI empowerment over technical accumulation, the new teaching model transforms teachers into “precise instruction designers” and students into “active explorers”.