DeepSeek融入地理信息系统课程教学改革研究

Teaching Reform Research on Integrating DeepSeek into GIS Courses

摘要: 随着生成式人工智能技术的快速发展，以DeepSeek为代表的大语言模型正在深刻影响高等教育各学科的教学模式。地理信息系统课程作为测绘地理信息技术专业的核心课程，长期面临理论抽象难理解、软件操作门槛高、教学资源更新滞后等突出问题。本文在分析GIS课程教学困境与DeepSeek技术特征的基础上，构建了“智能辅助–协同探究–能力内化”三阶融合模型，并从课程设计、教学资源、实践教学、评价体系四个维度提出了DeepSeek融入地理信息系统课程的具体路径。以《地理信息系统技术应用》课程为实践案例，详细阐述了DeepSeek在情境创设、参数验证、报告生成等教学环节中的应用场景与实施效果。实践表明，DeepSeek的合理融入能够有效提升教学效率、促进个性化学习，但也需警惕学生过度依赖、结果可信度等风险，应建立“教师主导 + 系统辅助”的人机协同机制。

Abstract: With the rapid development of generative artificial intelligence, large language models such as DeepSeek are profoundly transforming teaching models across disciplines in higher education. As a core course in surveying and geospatial information technology programs, Geographic Information Systems (GIS) has long faced significant challenges, including abstract and difficult-to-understand theories, high barriers to software operation, and outdated teaching resources. Based on an analysis of the current difficulties in GIS instruction and the technical characteristics of DeepSeek, this paper proposes a three-stage integrated model—“intelligent assistance, collaborative inquiry, and competency internalization”—and outlines specific pathways for integrating DeepSeek into GIS courses across four dimensions: curriculum design, teaching resources, practical instruction, and assessment systems. Using the course “Applications of Geographic Information Systems Technology” as a practical case, the paper elaborates on DeepSeek’s applications and implementation outcomes in teaching stages such as scenario creation, parameter validation, and report generation. Practice shows that appropriate integration of DeepSeek can effectively enhance teaching efficiency and promote personalized learning; however, risks such as student over-reliance and concerns about result credibility must be addressed. A human-machine collaboration mechanism guided by teachers and supported by the system should be established.