AI赋能的冶金原理沉浸式学习体系构建与实践

AI-Enabled Immersive Learning System for Metallurgical Principles: Construction and Practice

摘要: 在全球产业智能化转型与国家“新工科”建设双重驱动下，传统冶金工程教育面临深刻挑战，针对传统冶金原理课程中知识抽象性强、实践教学资源不足等问题，本文聚焦冶金工程核心基础课《冶金原理》，系统探讨人工智能(AI)技术驱动下的教学内容深度重构路径；打造基于知识图谱与虚拟仿真的可视化知识表征、创设数据驱动的探究式教学模式、建立“知识–能力–思政”多维综合评价体系，通过搭建虚实结合的实验平台、开发智能教学系统、构建数据驱动的教学评价体系，重塑为一门融合数据科学、具备动态优化能力和前沿视野的现代化课程，最终培养出能够驾驭智能时代冶金工业复杂性的复合型创新人才。

Abstract: Driven by the global shift toward intelligent industry and China’s “New Engineering” initiative, traditional metallurgical education is facing unprecedented challenges. Confronted with the abstract nature of core knowledge and the shortage of hands-on resources in conventional Metallurgical Principles courses, this paper focuses on the cornerstone subject Metallurgical Principles and systematically explores an AI-powered pathway for deep restructuring of teaching content. By building a visual-knowledge representation based on knowledge graphs and virtual simulation, creating a data-driven inquiry-based teaching model, and establishing a multi-dimensional assessment system that integrates knowledge, competence and ideological education, we aim to reshape the course into a modern, data-science-embedded program with dynamic optimization capability and frontier perspective. Through the construction of a hybrid virtual-physical experimental platform, the development of an intelligent tutoring system, and the creation of a data-driven teaching-evaluation framework, the reform will ultimately cultivate interdisciplinary innovative talents capable of mastering the complexity of metallurgical industry in the intelligent era.