应用型高校融合人工智能和大数据的车辆工程学科建设改革探究

Exploration on Curriculum Reform of Vehicle Engineering Subject Integrated with Artificial Intelligence and Big Data in Applied Universities

摘要: 随着人工智能和大数据技术的迅速发展，传统的车辆工程学科教育面临着转型和升级的需求。尤其是在应用型本科高校中，车辆工程课程体系与现代技术的需求之间存在较大差距，亟需进行课程改革。本文首先分析了当前车辆工程学科课程设置的现状，指出课程内容和教学方法的局限性，讨论了人工智能和大数据在车辆工程中的多项应用。在此基础上，提出了具体的改革路径和方法，包括强化技术融合、推动多学科交叉、培养学生的创新与实践能力，以及采用智能化教育手段等。此外，改革还应加强教师队伍建设、创新教学方法，并结合实际案例和行业实践，增强学生的实际操作能力。

Abstract: With the rapid development of artificial intelligence and big data technologies, the traditional discipline of automotive engineering education faces a need for transformation and upgrading. Particularly in application-oriented undergraduate universities, there is a significant gap between the current vehicle engineering curriculum system and the demands of modern technology, necessitating urgent curriculum reform. This paper first analyzes the current state of curriculum design in the automotive engineering discipline, highlighting the limitations in course content and teaching methodologies, and discusses various applications of AI and big data in vehicle engineering. Building on this analysis, specific reform pathways and methods are proposed. These include strengthening the integration of new technologies, promoting interdisciplinary approaches, cultivating students’ innovative and practical abilities, and adopting intelligent educational tools. Furthermore, the reform should enhance faculty development, innovate teaching methods, and incorporate real-world case studies and industry practices to strengthen students’ hands-on operational capabilities.