AI-EMPOWERED TEACHING REFORM OF OPERATIONS RESEARCH ORIENTED TOWARD DIGITAL TALENT DEVELOPMENT

Abstract

Against the backdrop of the deepening digital economy and the pervasive penetration of artificial intelligence (AI) into all sectors, social demand for versatile digital talent continues to rise. Operations research (OR), a core foundational course for majors such as management science and engineering and business administration, plays an irreplaceable role in cultivating students' systematic optimization thinking and quantitative decision-making capabilities. Driven jointly by the rapid advancement of AI and the national digital talent strategy, traditional OR teaching has become increasingly inadequate in content provision, methods and tools, practical integration, and evaluation systems. Seizing the historic opportunity of AI-empowered education and anchored in the core objectives of digital talent cultivation, this paper systematically analyzes the existing pain points of current OR teaching, explores pathways for the deep integration of AI and OR instruction, and proposes a systematic reform framework encompassing five interlocking components: reconstructing an integrated OR+AI curriculum system, updating teaching content with intelligent optimization and data-driven methods, innovating project-based and generative-AI-assisted teaching approaches, building blended virtual-physical practice platforms, and constructing multi-dimensional dynamic evaluation. Implementation outcomes drawn from university reform practices are discussed, offering a reference for the high-quality development of OR courses in the era of the digital economy.