电路教学与人工智能融合：现状、实践与发展方向

Integration of Circuit Teaching and Artificial Intelligence: Current Status, Practices, and Development Directions

摘要: 电路教学作为工程教育的核心基础课程，传统教学模式面临教学效率低、学生学习差异大、实验条件受限等问题。近年来，人工智能(Artificial Intelligence, AI)技术的发展为电路教学提供了新的解决方案。本文系统综述了2000~2025年国内外电路教学与AI融合的研究进展，从AI赋能电路课程教学、虚拟仿真实验技术、智能辅导系统、大语言模型应用等四个维度进行深度分析。研究表明：1) AI技术在课程演示、虚拟仿真、故障诊断等方面已展现出显著优势；2) 基于AI的自适应学习系统能够实现个性化教学和精准评价；3) 虚实融合的混合教学模式已成为发展趋势。最后，本文指出了当前研究的主要局限，提出了AI与电路教学融合的关键发展方向：建立学科特色的AI教学系统、加强教师AI能力培养、深化人机协同的教学模式创新。

Abstract: As a core foundational course in engineering education, circuit teaching faces challenges such as low teaching efficiency, significant differences in student learning, and limited experimental conditions in traditional teaching models. Recent advances in Artificial Intelligence (AI) technology have provided novel solutions for circuit education. This review systematically examines the progress of integrating AI with circuit teaching from 2000 to 2025 at home and abroad, analyzing four key dimensions: AI-enhanced circuit course instruction, virtual simulation experiments, intelligent tutoring systems, and large language model applications. The findings indicate that: 1) AI technologies have demonstrated significant advantages in course demonstrations, virtual simulations, and fault diagnosis; 2) AI-based adaptive learning systems enable personalized instruction and precision assessment; 3) hybrid teaching models combining virtual and physical experiments have become a development trend. Finally, this review identifies current research limitations and proposes key directions for AI-circuit education integration: developing subject-specific AI teaching systems, strengthening teacher AI capabilities, and deepening innovations in human-machine collaborative teaching models.