人工智能赋能《智能装备与建筑机器人》课程教学改革研究

Research on AI-Enabled Teaching Reform for the Course Intelligent Equipment and Construction Ro-Botics

摘要: 《智能装备与建筑机器人》课程具有多学科交叉与工程实践依赖度高的特点，其教学面临人工智能技术与专业内容衔接不足、实践资源受限、学习支持缺乏差异化以及产教协同不充分等问题。本文结合相关文献与课程任务分析，旨在构建涵盖教学方法、教学工具、教学场景和教学评价的AI赋能改革框架。以知识图谱关联课程知识与工程任务，利用虚拟仿真支持方案试验，通过理论、虚拟、模拟和工地四个课堂组织递进式学习，并以过程证据支持学习诊断与教学调整。该框架着重设计同一工程任务在不同场景中的成果传递与反馈机制，为专业知识向工程应用能力的转化提供课程设计思路。

Abstract: Intelligent Equipment and Construction Robotics is an interdisciplinary course with a strong emphasis on engineering practice. Its delivery is constrained by the insufficient integration of artificial intelligence (AI) with disciplinary content, limited resources for practical training, inadequate differentiated learning support, and weak collaboration between universities and industry. Drawing on the relevant literature and an analysis of course tasks, this study develops an AI-enabled instructional reform framework encompassing teaching methods, instructional tools, learning environments, and assessment. The framework employs a knowledge graph to connect disciplinary knowledge with engineering tasks, uses virtual simulation to support solution testing, and organizes progressive learning across four interconnected settings: theoretical instruction, virtual experimentation, simulated practical training, and construction-site learning. It also incorporates process-based evidence to inform learning diagnosis and instructional adjustment. Particular emphasis is placed on the transfer of task outputs and feedback generated by the same engineering project across different learning settings. The proposed framework provides a structured approach to curriculum design that facilitates the transformation of disciplinary knowledge into engineering application competencies.