In order to solve the core problem of the disconnect between the practical teaching system of mechanical majors and industry demand under the background of intelligent transformation of manufacturing industry, and to improve the quality of talent cultivation, this study focuses on the integration and empowerment value of artificial intelligence and digital twin technology, and carries out research on the reconstruction of the practical teaching system of mechanical majors. Using mixed research methods such as questionnaire surveys, in-depth interviews, and field investigations, this study systematically analyzes the existing problems of the traditional practical teaching system in terms of objectives, content, resources, modes, and evaluation, and clarifies the feasibility and necessity of technological integration. Based on the principles of demand-oriented and technology integration, we will construct a comprehensive framework for the reconstruction of the "four layer and three-level" practical teaching system, and complete the precise design of the five core modules of teaching objectives, content, resources, modes, and evaluation. The research results provide theoretical support and feasible implementation paradigms for the practical teaching reform of mechanical majors, which can effectively enhance the ability of talents to apply new technologies and engineering innovation, and help higher education better adapt to the high-quality development needs of the manufacturing industry.

Yuxian Xu. Research on the Reconstruction of Practical Teaching System for Mechanical Majors Based on Artificial Intelligence and Digital Twin Technology. International Journal of New Developments in Education (2026), Vol. 8, Issue 2: 77-82. https://doi.org/10.25236/IJNDE.2026.080211.

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