Practice of the Artificial Intelligence-Empowered Industry-Education Integration Teaching Model in Mechanical Engineering: Taking Corporate Project-Based Teaching as a Case Study

Abstract

The acceleration of technological innovation and industrial upgrading in the field of mechanical engineering has placed profound demands for transformation in the cultivation models of specialized talents. This study, using corporate project-based teaching as a vehicle, explores systematic pathways for artificial intelligence technology to empower the industry-education integration teaching model in mechanical engineering. The research constructs a comprehensive theoretical framework spanning technological integration pathways, teaching model implementation, and effectiveness evaluation: first, it analyzes how artificial intelligence achieves deep integration with specialized instruction through constructing intelligent intermediary layers, restructuring knowledge networks, and establishing dynamic digital twins coupling; second, it elaborates an implementation framework guided by corporate projects, comprising the organization of intelligent resources, the restructuring of human-machine collaborative processes, and cross-scenario data feedback; finally, it proposes effectiveness evaluation methods based on technology integration mapping, analysis of alignment with industrial demands, and an adaptive evaluation system. The study aims to provide theoretical reference and practical guidance for establishing a new paradigm in mechanical engineering education that responds to real-time industrial needs, is driven by data intelligence, and possesses self-evolution capability.