人工智能背景下计算机网络课程教学改革路径探索

Exploring Teaching Reform Pathways for Computer Network Courses in the Context of Artificial Intelligence

摘要: 随着人工智能技术的快速迭代与行业应用的全面渗透，数字经济发展对计算机类技术技能人才的培养提出了全新要求。计算机网络课程作为计算机类相关专业的核心基础课程，其传统教学模式已难以适配人工智能时代的岗位能力需求与人才培养目标。本文立足于人工智能与教育教学深度融合的时代背景，首先系统审视了当前计算机网络课程教学中存在的内容与岗位脱节、教学模式固化、师资能力不足、评价体系滞后等核心问题，进而分析了人工智能技术为课程改革带来的底层逻辑重构、资源边界拓展、评价体系优化等全新机遇。在此基础上，本文结合淮南师范学院计算机网络课程的改革实践，以“基于机器学习的流量识别”实验模块为例，详细介绍了整合AI技术的教学模块的设计思路、分层实施过程、学生实践成果与教学效果，同时结合学习科学与AIED领域的相关理论，深化了对AI赋能教学改革的理论认知。研究最后提炼了课程改革的核心原则，探索了适配人工智能发展趋势的改革方向，旨在为新时代计算机网络课程教学质量提升提供理论参考与实践借鉴，为培养符合数字经济发展需求的高素质复合型技术技能人才提供支撑。

Abstract: With the rapid iteration of artificial intelligence technologies and their full penetration into industry applications, the development of the digital economy has set entirely new requirements for the cultivation of technical and skilled talents in computer-related fields. As a core foundational course for computer-related majors, the traditional teaching model of the Computer Network course can no longer meet the job competency demands and talent cultivation objectives of the AI era. Against the backdrop of the deep integration of AI with education and teaching, this paper first systematically examines the core problems existing in current computer network course teaching, such as the disconnect between course content and job requirements, rigid teaching models, insufficient faculty capabilities, and lagging evaluation systems. Then it analyzes the new opportunities brought by AI technology for curriculum reform, including the reconstruction of underlying logic, expansion of resource boundaries, and optimization of evaluation systems. On this basis, combined with the reform practice of computer network course in Huainan Normal University, this paper takes the experimental module of “Machine Learning-based Traffic Identification” as an example, introduces in detail the design ideas, layered implementation process, students’ practical achievements and teaching effects of the teaching module integrating AI technology. Meanwhile, combined with relevant research in learning science and AIED field, it deepens the theoretical cognition of AI-enabled teaching reform. Finally, the research extracts the core principles of curriculum reform, explores the reform direction adapting to the development trend of artificial intelligence, aiming to provide theoretical reference and practical reference for improving the teaching quality of computer network courses in the new era, and provide support for cultivating high-quality compound technical and skilled talents meeting the needs of digital economy development.