The Impact of Artificial Intelligence Applications on Teaching Models in Higher Education

摘要

Abstract

Artificial intelligence has been applied to higher education activities such as the generation of teaching resources, intelligent question answering, personalized learning, and assignment feedback, driving a transition from the traditional teacher student dyadic structure toward a collaborative teaching structure involving teachers, students, and intelligent tools. Although artificial intelligence can expand the supply of educational resources and support differentiated learning, its application also raises concerns regarding inaccurate information, academic integrity, overdependence, and data security. This article analyzes the effects of artificial intelligence on teaching content, classroom organization, learning approaches, educational assessment, and teachers’ roles. It proposes clarifying the boundaries of AI use, redesigning learning tasks, reforming assessment methods, and improving institutional safeguards.