Research on the Intelligent Reform Pathway of Higher Education Empowered by Generative Artificial Intelligence

Abstract

The rapid advancement of generative artificial intelligence (GAI) has reshaped university teaching models and learning practices, emerging as a central force in instructional innovation and driving the broader digital transformation of higher education. Centered on teaching reform, this paper conducts a systematic analysis of how GAI enhances instructional processes through multimodal resource generation, dynamic learning-support services, adaptive assessment, and data-driven student feedback. It further examines GAI's contribution to constructing intelligent and interconnected teaching ecosystems, strengthening personalized learning pathways, and improving instructional efficiency across diverse disciplinary contexts. Building on an extensive literature-based examination, the study introduces a comprehensive four-dimensional, drive-oriented framework for promoting intelligent university teaching reform-Technology Support, Scenario Integration, Intelligent Feedback, and Competency Development-emphasizing how these dimensions interact to optimize pedagogical decisions, cultivate learner autonomy, and support evidence-based instructional improvement. The proposed framework aims to provide a theoretical foundation and actionable guidance for universities seeking to achieve sustainable, high-quality educational digital transformation in the evolving landscape of the new era.