Optimizing the Curriculum and Innovating Teaching Models for the Digital Economy Major through Artificial Intelligence

Abstract

The rapid development of artificial intelligence (AI) technology has brought new opportunities and challenges to talent cultivation in the digital economy era. At present, the curriculum system of digital economy programs in Chinese universities faces prominent issues such as outdated content, insufficient interdisciplinary integration, and monotonous teaching models, which severely hinder the quality of talent training. Drawing on the theoretical logic of AI-empowered education in digital economy programs, this study explores the specific mechanisms and practical pathways of AI in curriculum system optimization and teaching model innovation. It proposes an AI-based optimization framework for the digital economy curriculum system, featuring a modular interdisciplinary structure, dynamic content updating, and an intelligent teaching evaluation system. Furthermore, the study conducts an in-depth analysis of AI-driven teaching models, including flipped classrooms, blended teaching, and personalized learning path design, with effectiveness evaluations based on practical cases from representative universities at home and abroad. In addition, it systematically examines the challenges related to technology, resources, faculty, and ethics encountered in AI-empowered education, and puts forward corresponding strategic recommendations. The findings of this research hold significant theoretical and practical value for improving the quality of digital economy talent cultivation in China, deepening higher education reform, and promoting the deep integration of AI and education