数智赋能下“虚实联动·数据驱动”教学模式创新与实践——以《机械设计基础》为例

Innovation and Practice of the “Virtual-Real Linkage ∙ Data-Driven” Teaching Model Empowered by Digital Intelligence—Taking “Fundamentals of Mechanical Design” as an Example

摘要: 在新工科建设与产业数字化转型背景下，《机械设计基础》课程面临教学可视化不足、虚实实践脱节、产教协同数字化程度浅等问题，制约应用型人才培养。本文以“问题导向–技术赋能–产教协同–成果推广”为主线，提出“虚实联动·数据驱动”教学创新思路。通过构建虚实联动三阶递进式教学体系，运用三维建模与仿真技术实现机械原理可视化教学，培养学生系统思维；借助学习通、雨课堂等平台，建立数据驱动的“采集–评估–优化”教学决策闭环，推动教学精准化；打造产教协同数字化资源共享平台，通过共建案例库、搭建云端平台、打通数据接口，弥合教学与企业需求差距。该模式能够提升学生的工程设计与创新能力，为地方应用型高校工科课程数字化转型提供可复制的解决方案。未来将深化人工智能应用，强化校企协同，完善资源共享，推动人才培养与产业数字化协同发展。

Abstract: Against the backdrop of new engineering education construction and industrial digital transformation, the course Fundamentals of Mechanical Design faces challenges such as insufficient teaching visualization, disconnection between virtual and real practice, and shallow digital integration of industry-education collaboration, which restrict the cultivation of applied talents. This paper proposes an innovative teaching approach of “Virtual-Real Linkage ∙ Data-Driven” guided by the main line of “problem orientation - technology empowerment - industry-education collaboration - achievement promotion”. It constructs a three-stage progressive teaching system of virtual-real linkage, using 3D modeling and simulation technologies to visualize mechanical principles and cultivate students’ systematic thinking. By leveraging platforms like Xuexitong and Yutang, a data-driven teaching decision-making loop of “collection-evaluation-optimization” is established to promote precise teaching. A digital resource-sharing platform for industry-education collaboration is created through co-building case libraries, establishing cloud-based collaboration platforms, and connecting data interfaces, bridging the gap between teaching content and enterprise needs. This model would enhance students’ engineering design and innovation capabilities, providing a replicable solution for the digital transformation of engineering courses in local applied universities. In the future, efforts will be made to deepen the application of artificial intelligence, strengthen industry-education collaboration, improve resource sharing, and promote the coordinated development of talent cultivation and industrial digitization.