AI empowers the teaching reform of vocational education: Practical paths and future development prospects
AI赋能职业教育教学改革：实践路径与未来发展展望

摘要

为适应数字经济与产业智能化转型对技术技能人才的迫切需求，职业教育亟需借助人工智能技术推动教学体系系统性变革。本文以AI与职业教育深度融合为研究核心，运用文献研究法、案例分析法、实践调研法与比较研究法，系统剖析AI赋能职业教育教学改革的时代背景、核心价值与现实困境，围绕课程体系重构、教学模式创新、智能实训建设、多元评价优化、师资能力提升五大维度构建完整实践路径，并结合技术发展趋势与职教规律，对未来智能化、个性化、协同化发展方向进行全面展望。研究发现，AI能够有效破解传统职业教育教学同质化、实训成本高、产教对接不畅、评价精准度不足等突出问题，通过构建“人机协同、虚实融合、数据驱动”的新型教学生态，实现规模化因材施教与高质量育人。未来应进一步完善技术标准、数据安全、伦理规范与制度保障体系，推动AI从辅助工具走向深度融合，全面提升职业教育人才培养质量，为现代产业体系建设与技能型社会发展提供有力支撑。

Abstract

To meet the urgent demand for technical and skilled talents in the digital economy and industrial intelligent transformation, vocational education urgently needs to promote the systematic reform of the teaching system with the help of artificial intelligence technology. Taking the in-depth integration of AI and vocational education as the research core, this paper systematically analyzes the background, core values and practical dilemmas of AI empowering vocational education teaching reform by using methods of literature research, case analysis, practical investigation and comparative research. It constructs a complete practical path around five dimensions: curriculum system reconstruction, teaching mode innovation, intelligent practical training construction, diversified evaluation optimization, and teacher ability improvement. Combined with technological development trends and vocational education laws, this paper makes a comprehensive prospect for the future intelligent, personalized and collaborative development direction. The study finds that AI can effectively solve the prominent problems in traditional vocational education, such as homogeneous teaching, high practical training costs, poor integration of industry and education, and insufficient evaluation accuracy. By building a new teaching ecology of “human-machine collaboration, virtual-real integration and data-driven”, it can realize large-scale personalized education and high-quality talent training. In the future, we should further improve the technical standards, data security, ethical norms and institutional guarantee system, promote AI from auxiliary tools to in-depth integration, comprehensively improve the quality of talent training in vocational education, and provide strong support for the construction of modern industrial system and the development of skilled society.