面向AI与大数据时代的《计算材料学》课程教学改革与实践

Teaching Innovation and Practice of “Computational Materials Science” in the AI and Big Data Era

摘要: 当下我们正处于人工智能与大数据技术深度变革材料科学的时代，传统的《计算材料学》课程授课教学模式因此面临着新一轮革新需求。本文紧密围绕工程教育专业认证标准的核心要求，深入探索人工智能与大数据技术在课程教学改革中的多渠道融合路径。通过教学内容体系重新架构、智能化实践平台线上建设、教学方法机制深度创新以及课堂课下评价体系多维度优化，进而全面提升学生运用现代计算工具解决复杂材料设计问题的综合能力，强化数据驱动思维，为培养符合新材料产业新时代高质量发展需求的复合型工程人才提供教育支撑。

Abstract: We are currently witnessing a profound transformation in materials science driven by artificial intelligence (AI) and big data technologies. Against this backdrop, the traditional teaching model of the “Computational Materials Science” course faces an urgent need for reform. This study closely aligns with the core requirements of engineering education accreditation standards and systematically explores multiple integration pathways of AI and big data into curriculum reform. By reconstructing the course content framework, developing intelligent online practice platforms, innovating teaching methodologies, and optimizing multidimensional assessment systems both inside and outside the classroom, this reform aims to comprehensively enhance students’ ability to apply modern computational tools to address complex problems in materials design. Moreover, it seeks to strengthen data-driven thinking and provide educational support for cultivating interdisciplinary engineering professionals who meet the demands of high-quality development in the emerging materials industry.