Abstract: In response to the multiple predicaments faced by traditional automotive-related professional course teaching, such as the disconnection between theory and practical application,the slow timeliness of teaching resources, outdated versions of internship and training equipment, and insufficient cultivation of students' innovative thinking abilities,this article forms a course knowledge graph by reconstructing the teaching elements of automotive professional courses based on the empowerment of artificial intelligence (AI), and decomposes the complex elements of courses into sub-tasks with the technology of large-scale artificial intelligence models. To cultivate comprehensively and systematically students' abilities in the knowledge domain, personalized development and innovative consciousness by adopting a task-driven approach with the support of digital teaching platforms and AI-assisted teaching systems, forming a teaching model of "digital platform+AI empowerment+task-driven". Based on the comprehensive assessment results of three cohorts of students before and after the reform of the Engine Principle course, it can be seen that the teaching reform of this course has achieved remarkable and positive effects. Compared with the situation before the reform, it has achieved significant achievements in multiple dimensions, precisely adapted to the talent cultivation and the demand for automotive industry talents, and provided continuous talent support for the high-quality development of the automotive industry.

Key words: artificial intelligence; task-driven; Engine Principle; knowledge graph

摘要： 针对传统汽车类专业课程教学面临的理论与实践应用脱节、教学资源时效性缓慢、实 习实训设备版本老旧以及学生创新思维能力培养不足等多重困境，文章基于人工智能（AI） 赋能，通过重构汽车专业课程教学要素形成课程知识图谱，利用人工智能大模型技术将课程 教学复杂要素拆解成子任务，并在数字化教学平台与 AI 辅助教学系统支持下，以任务驱动的 方式系统全面培养学生知识层面、个性化发展与创新意识方面的能力，形成“数字化平台+AI 赋能+任务驱动”三位一体教学模式。根据发动机原理课程改革前后三届学生的综合考核成绩 可知，该研究的课程教学改革教学效果显著向好，较改革前取得了多维度突出成效，精准地 适配人才培养与汽车产业链人才需求，为汽车产业高质量发展提供持续人才支持。

关键词: 人工智能；任务驱动；发动机原理；知识图谱