Chinese Journal of Medical Education ›› 2024, Vol. 44 ›› Issue (3): 176-179.DOI: 10.3760/cma.j.cn115259-20230301-00192

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Construction and application of knowledge graph of core courses in basic medical education stage

Yan Jingrui1, Deng Weimin1, Zhang Shijie2, Mo Jing3, Wen Ke2, Yu Li4   

  1. 1Teaching Office, School of Basic Medicine, Tianjin Medical University, Tianjin 300070, China;
    2Department of Pharmacology, School of Basic Medicine, Tianjin Medical University, Tianjin 300070, China;
    3Teaching and Research Section of Pathology, School of Basic Medicine, Tianjin Medical University, Tianjin 300070, China;
    4Teaching and Research Section of Computer, School of Basic Medicine, Tianjin Medical University, Tianjin 300070, China
  • Received:2023-03-01 Online:2024-03-01 Published:2024-03-06
  • Contact: Yu Li, Email: yuli@tmu.edu.cn
  • Supported by:
    Project of the Ministry of Education's Industry-Academic Cooperation Collaborative Education (220503924191616); Chinese Medical Association Medical Education Branch and China Higher Education Society Medical Education Specialized Committee 2020 Medical Education Research Project(2020A-N06018)

Abstract: In the process of training medical students, the learning efficiency and personalized learning of students in the stage of basic medical education are issues that need urgent attention. Knowledge graphs can express the essential characteristics of complex logical relationships between knowledge, paving ways to solve these problems. In order to improve students' learning effectiveness and efficiency, and meet the needs of personalized learning, this article is based on a tree structure and adopts the method of domain experts to build schemas and relationships, perform data extraction, data refinement, and data fusion, and construct the knowledge graph of core courses in basic medical education stage on the Chaoxing learning platform. The construction process of the knowledge graph is presented for the core courses of basic medical education stage in this paper. Through application in 45 students who applied to change majors at Tianjin Medical University in grade 2021 with a statistical method, the results showed that the scores of students who often use the knowledge graph [(177.7±23.3) points] were higher than those who did not use it frequently [(147.9±20.3) points], and it was statistically significant (P<0.001). Therefore, knowledge graphs can help improve students' learning effectiveness and efficiency, and provide support for personalized learning as well.

Key words: Computer-assisted instruction, Knowledge graph, Basic medical education, Construction, Application

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