Exploration of the "Learning-Research-Application" Integrated Practice Teaching Model in the Field of Education in the Age of AI

Abstract

This paper primarily explores the construction and optimization of the "Learning-Research-Application" integrated practice teaching model in the field of education within the context of the AI era. It aims to address issues prevalent in teacher education, such as the disconnect between theory and practice, the fragmentation of research and teaching, and the lag in internship guidance. Starting from a reconceptualization of the connotations of "Learning-Research-Application," this paper discusses the functional mechanisms of AI technology in reshaping learning contexts, data-driven scientific research, and intelligent internship management. It proposes practical pathways for intelligent learning, data-based research, and precise internships. By empowering the deep integration of coursework learning, scientific research training, and educational practice with AI, this model effectively enhances the classroom teaching ability, scientific research inquiry capability, and digital literacy of student teachers. Consequently, it promotes the development of educational internships towards a more scientific, traceable, and iterative direction.