Research on Intelligent Teaching in <i>Signals and Systems</i> Driven by Large Language Models

《信号与系统》作为电子信息类专业的核心课程，其需要较强的数学理论知识，长期以来主要以教师讲授为主，在教学过程中存在学生理解困难、应用能力不足等问题。随着人工智能技术，尤其是大语言模型的迅猛发展，为高校课程教学模式的改革带来了新的契机。本文探讨将大语言模型(如DeepSeek)引入《信号与系统》教学的可行路径，结合课堂实际，设计融合大模型能力的教学活动，以提升学生对核心概念的理解和应用能力。以“傅里叶变换”教学内容为例，具体分析其在课堂教学中的应用方式，进一步验证其在构建智慧课堂和提升教学质量方面的潜力。Signals and Systems, as a core course in electronic information-related disciplines, requires a strong foundation in mathematical theory. It traditionally has been predominantly taught through instructor-led teachers, which often leads to difficulties in student comprehension and inadequate application abilities. With the rapid development of artificial intelligence technologies, particularly large language models (LLMs)—new opportunities have emerged for reforming teaching models in higher education. This paper explores the feasibility of integrating large language models (DeepSeek) into the teaching of Signals and Systems. By aligning with classroom practice, it proposes the design of instructional activities that leverage the capabilities of LLMs to enhance the understanding of key concepts of students and their ability to apply them. Taking the topic of “Fourier Transform” as a teaching case, the study analyzes how LLMs can be effectively utilized in classroom instruction, further demonstrating their potential in building intelligent classrooms and improving teaching quality.