AI Empowered College Classroom:The Role of DeepSeek in Teaching

Abstract

The evolution of generative artificial intelligence technology offers new possibilities for the digital transformation of higher education classrooms. This study takes the domestic intelligent model DeepSeek as the research object to explore its functional positioning, application value, and potential challenges in the teaching scenarios of colleges and universities. Through literature analysis and theoretical construction, combined with observations of teaching practices, it proposes that DeepSeek assumes three roles in classroom teaching: as an intelligent lesson preparation assistant for teachers, a personalized learning support tool for students, and a medium that enhances interaction between teachers and students. The research reveals that DeepSeek can promote the intelligent reconstruction of the teaching process and the transformation of the "student-centered" classroom ecology through functions such as real-time knowledge retrieval, adaptive question-and-answer feedback, and multi-modal resource generation. However, its application also encounters problems such as technical reliability limitations, academic ethical disputes, and insufficient digital literacy adaptation among teachers and students. The study suggests that colleges and universities need to establish a "technology-teaching-ethics" collaborative framework, clarify the auxiliary boundaries of artificial intelligence tools, and achieve the deep integration of DeepSeek and classroom teaching through institutionalized training and normative guidance. This study provides theoretical references and practical inspirations for the teaching reform driven by generative AI in colleges and universities.