人工智能背景下《涂装工艺学》教学改革研究

Research on the Teaching Reform of Coating Technology under the Background of Artificial Intelligence

摘要: 人工智能技术的迅猛发展正推动着高等教育领域的教学改革，尤其在《涂装工艺学》这类与制造业紧密相关的课程中，其影响更为显著。本教改论文立足于人工智能背景，针对当前《涂装工艺学》教学中理论与实践脱节、教学手段单一等问题，提出了一系列教学改革方案。论文内容聚焦于教学内容、教学方法及教学评价体系的全面革新。在教学内容上，首次构建了“AI + 涂装工艺”的三维教学改革模型，将机器学习算法、虚拟仿真技术等人工智能工具深度嵌入课程体系，并联合企业搭建“数字孪生”实训平台，实现理论与实践的深度融合。教学方法上，引入虚拟现实技术构建沉浸式实践操作环境，开发智能教学支持系统以实现个性化学习路径规划，通过多源数据采集与智能分析，提升教学效率与精准度。教学评价体系则构建了基于物联网与人工智能的数据采集系统，融合监督学习与深度学习技术，形成多维度、动态化的评价指标体系，确保评价结果的科学性与时效性。

Abstract: The rapid development of artificial intelligence (AI) technology is driving pedagogical reforms in higher education, particularly in courses closely related to manufacturing, such as Coating Technology. This educational reform paper, grounded in AI, addresses the current disconnect between theory and practice and the monotony of teaching methods in Coating Technology by proposing a series of reform proposals. The paper focuses on comprehensive innovations in teaching content, teaching methods, and the teaching evaluation system. Regarding teaching content, it constructs a three-dimensional AI + Coating Technology teaching reform model, deeply embedding AI tools such as machine learning algorithms and virtual simulation technology into the curriculum. Furthermore, it collaborates with enterprises to build a “digital twin” training platform, achieving a deep integration of theory and practice. Regarding teaching methods, it introduces virtual reality technology to create an immersive practical environment, develops an intelligent teaching support system to enable personalized learning path planning, and improves teaching efficiency and accuracy through multi-source data collection and intelligent analysis. The teaching evaluation system incorporates a data collection system based on the Internet of Things and AI, integrating supervised learning and deep learning techniques to form a multi-dimensional, dynamic evaluation index system to ensure the scientific and timely evaluation results.