摘要
人工智能与统计物理的深度融合正重塑电子科学与技术行业发展范式,传统电科专业人才培养面临课程体系与前沿脱节、思政教育与专业割裂、教学模式固化、学科壁垒等挑战。该文立足科技前沿进课堂、课程思政、案例式教学、学科交叉四大核心维度,构建“理论重构—价值塑造—实践赋能—交叉融合”的转型路径,通过融入统计物理中化工行业建模、AI优化算法等前沿内容,挖掘专业领域思政元素,设计化工工业真实场景案例,打破学科边界,为培养具备跨学科思维、创新能力和社会责任感的复合型电科人才提供改革方案。
The in-depth integration of artificial intelligence(AI)and statistical physics is reshaping the development paradigm of the electronic science and technology industry.Talent training in traditional electronic science and technology majors faces challenges such as disconnection between curriculum systems and cutting-edge developments,separation of ideological and political education from professional teaching,rigid teaching models,and disciplinary barriers.Based on four core dimensions:integrating cutting-edge science and technology into classrooms,curriculum-based ideological and political education,case-based teaching,and interdisciplinary integration,this paper constructs a transformation path of"theoretical reconstruction-value shaping-practical empowerment-interdisciplinary integration".By incorporating cutting-edge content such as chemical industry modeling in Statistical Physics and AI optimization algorithms,exploring ideological and political elements in professional fields,designing real-scenario cases in the chemical industry,and breaking disciplinary boundaries,this study provides a reform plan for cultivating interdisciplinary electronic science and technology talents with cross-disciplinary thinking,innovative capabilities,and social responsibility.
出处
《高教学刊》
2025年第36期151-154,共4页
Journal of Higher Education
基金
2024年度教育部高等学校大学物理课程教学指导委员会大中物理教育衔接工作委员会资助项目“‘物理学现象的程序模拟’-面向社会公众的物理科学研究与实践”(WX202448)。
关键词
人工智能
统计物理
电科专业
人才培养
转型路径
Artificial Intelligence(AI)
Statistical Physics
electronic science and technology major
talent training
transformation paths
