植物学报 ›› 2026, Vol. 61 ›› Issue (4): 705-714.DOI: 10.11983/CBB25150

• 教学研讨 • 上一篇    

基于AI的植物生物学课程知识图谱建设与应用

赵慧, 杨晓瑞, 韩洁, 陈四龙*()   

  1. 河北科技大学 食品与生物学院 , 石家庄 050018
  • 收稿日期:2025-08-16 接受日期:2025-12-06 出版日期:2026-07-10 发布日期:2025-12-16
  • 通讯作者: 陈四龙
  • 基金资助:
    河北省高等教育教学改革研究与实践项目(2023GJJG704)

Construction and Application of Knowledge Graph for Plant Biology Course Based on AI

Hui Zhao, Xiaorui Yang, Jie Han, Silong Chen*()   

  1. College of Food Science and Biology, Hebei University of Science and Technology , Shijiazhuang 050018, China
  • Received:2025-08-16 Accepted:2025-12-06 Online:2026-07-10 Published:2025-12-16
  • Contact: Silong Chen

摘要: 在教育数智化变革背景下, 作为新型数字化技术的典型代表, 知识图谱与教育教学的深度融合正成为教育领域的热点。该研究基于学习通智慧教育平台和人工智能(AI)技术, 系统构建了植物生物学课程知识图谱并开展应用实践, 以探究其在教育教学中的实质作用。应用实践表明, 课程知识图谱有助于学生梳理知识点之间的关系、拓宽知识面、构建系统化的知识体系, 并辅助学生制定个性化学习路径, 提高学习能力; 对于教师而言, 课程知识图谱是高效管理教学资源的有力工具, 个性化学习数据帮助教师精准把握学生个体差异, 提供针对性指导, 持续提升教学质量。这种教师-知识图谱-学生三方协同的学习生态, 为教育数智化变革提供了极具价值的实践范式。

关键词: 植物生物学, 知识图谱, 学习通, 人工智能, 个性化学习

Abstract: Under the background of the digital and intelligent transformation in education, knowledge graphs, as a typical representative of new digital technologies, are deeply integrated with teaching and learning, becoming a hotspot in the field of education. Leveraging Xuexitong smart education platform and artificial intelligence (AI) technologies, a systematic knowledge graph for the course of plant biology was constructed in this study, and teaching practices were conducted to explore its substantive role in teaching and learning. The application results indicate that the course knowledge graph not only helps students organize the relationships between learning points, broaden their knowledge horizons, and thus build a systematic knowledge system, but also assists students in formulating personalized learning paths to improve learning abilities. For teachers, the course knowledge graph serves as a powerful tool for efficiently managing teaching resources. Personalized learning data drives teachers to clearly grasp individual student differences, provide precise guidance, and continuously enhance teaching quality. This tripartite collaborative learning ecosystem of teacher-knowledge graph-student provides a highly valuable practical model for the digital and intelligent transformation of education.

Key words: plant biology, knowledge graph, Xuexitong, artificial intelligence, personalized learning