具身智能技术赋能职业教育：应用场景、挑战与应对策略
Embodied Intelligence Technology Enabling Vocational Education: Application Scenarios, Challenges, and Response Strategies

随着第四次工业革命的深入推进，职业教育领域正面临着技能迭代速度显著加快、产教融合壁垒日益凸显等多重挑战。在此背景下，具身智能技术(Embodied Artificial Intelligence)作为一种能够与环境进行深度交互，并依据环境变化自主做出决策和执行相应行动的前沿技术，为破解职业教育发展困境提供了创新性的解决方案。本研究采用文献研究法，系统探讨了具身智能技术的基本概念体系、关键支撑技术及其在职业教育领域的具体应用场景。研究发现，其应用主要体现在三个维度：在感知能力层面，可支持沉浸式技能训练系统的构建与多模态学习体验的实现；在决策能力层面，能够实现个性化学习路径的动态规划与智能评估反馈机制的建立；在行动能力层面，则可促进机器人辅助教学系统的开发与人机协作学习模式的创新。具身智能技术在职业教育领域应用面临技术成熟度不足、教育模式适应性不足及伦理风险挑战，本研究针对性提出应对策略。展望未来，具身智能技术将在职业教育数字化转型进程中发挥更为重要的作用，推动教育范式从传统的“知识传递”向现代的“能力生成”转变，为培养适应新时代要求的高素质技术技能人才提供强有力的智能支持。
With the deepening of the Fourth Industrial Revolution, the field of vocational education is facing multiple challenges, including significantly accelerated skill iteration and increasingly prominent barriers to industry-education integration. In this context, Embodied Artificial Intelligence (Embodied AI), as an advanced technology capable of deep interaction with the environment and autonomously making decisions and executing corresponding actions based on environmental changes, provides an innovative solution to address the development dilemmas of vocational education. This study employs a literature review approach to systematically explore the fundamental conceptual framework, key supporting technologies, and specific application scenarios of embodied intelligence technology in the field of vocational education. The research findings indicate that its applications are primarily manifested in three dimensions: at the perceptual level, it supports the construction of immersive skill training systems and the realization of multimodal learning experiences; at the decision-making level, it enables dynamic planning of personalized learning paths and the establishment of intelligent evaluation and feedback mechanisms; and at the action level, it promotes the development of robot-assisted teaching systems and the innovation of human-machine collaborative learning models. The application of embodied intelligence technology in vocational education faces challenges including insufficient technological maturity, inadequate adaptability of educational models, and ethical risks. This study proposes targeted strategies to address these issues. Looking ahead, embodied intelligence technology will play a more significant role in the digital transformation of vocational education, driving the shift in educational paradigms from traditional “knowledge transmission” to modern “competency generation”, and providing robust