人工智能赋能数字电路课程教学改革与实践研究

Research on Teaching Reform and Practice of Digital Circuit Course Empowered by Artificial Intelligence

摘要: 随着人工智能技术快速发展以及新工科建设持续推进，电子信息类专业课程教学面临知识更新加快、学习需求分化和实践场景智能化等新要求。数字电路课程是电子信息类专业的重要基础课程，对学生建立数字系统思维、掌握逻辑设计方法和形成工程实践能力具有基础性作用。针对传统教学中课程内容与智能电子技术发展衔接不足、学情分析不够精准、实验教学资源利用效率有限、过程评价不充分等问题，本文在OBE理念基础上引入学习科学和建构主义学习理论，采用文献分析、课程目标反向设计、教学流程重构和技术方案建模等方法，构建人工智能赋能数字电路课程教学改革框架。研究进一步细化学习画像、资源推荐、智能反馈和虚实融合实验等核心功能的实现路径，并从数据安全、算法偏差、教师能力和资源建设等方面讨论实施挑战与对策。研究表明，人工智能可为数字电路课程精准教学、工程实践训练和持续改进提供支撑。

Abstract: With the rapid development of artificial intelligence (AI) and the continuous advancement of emerging engineering education, digital circuit teaching faces new requirements in knowledge updating, differentiated learning support and intelligent practice scenarios. Digital circuit is a fundamental engineering course for electronic information majors, and it is essential for cultivating digital system thinking, logic design methods and engineering practice ability. In response to insufficient connection with intelligent electronic systems, imprecise learning diagnosis, limited utilization of experimental resources and weak process evaluation in traditional teaching, this study integrates outcome-based education with learning science and constructivist learning theory. Through literature analysis, reverse design of course objectives, reconstruction of teaching processes and technical scheme modeling, an AI-enabled teaching reform framework for the digital circuit course is proposed. The study further specifies the implementation logic of learning profiles, resource recommendation, intelligent feedback and virtual-real integrated experiments, and discusses challenges concerning data privacy, algorithmic bias, teacher training and resource construction. The proposed framework can support precision teaching, engineering practice training and continuous improvement in digital circuit education.