在医学生的培养过程中,基础医学教育阶段学生的学习效率和个性化学习是亟需关注的问题。知识图谱能够表达知识间复杂逻辑关系的本质特征,为解决这些问题提供了方法。为了提升学生的学习效率和学习效果,满足个性化学习的需求,本文基于树结构,采用领域专家的方式构建模式和关系,进行数据提取、数据精炼和数据融合,在超星学习平台上构建了基础医学教育阶段核心课程知识图谱。本文介绍了基础医学教育阶段核心课程知识图谱的构建过程,并在天津医科大学2021级申请转专业的45名学生中加以应用,结果表明,经常使用知识图谱的学生的笔试成绩[(177.7±23.3)分]高于不经常使用的学生[(147.9±20.3)分],其差异具有统计学意义(P<0.001)。知识图谱能够帮助学生随时随地进行学习,有助于提高学生的学习效率和学习效果,并为个性化学习提供了支持。
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.
[1] 潘克清, 邓婧, 袁昌青, 等. 基于岗位胜任力的口腔医学专业本科生教学改革探索[J].中华医学教育杂志,2022,42(11):1020-1023. DOI: 10.3760/cma.j.cn115259-20220330-00405.
[2] 张进, 李庆林, 杨立斌, 等. 医学院校课程整合改革实践与思考[J].中华医学教育探索杂志,2020,19(10):1131-1134. DOI: 10.3760/cma.j.cn116021-20191127-00260.
[3] EhrlingerL , Wolfram W . Towards a definition of knowledge graphs[C/OL]//12th International Conference on Semantic Systems and 1st International Workshop on Semantic Change & Evolving Semantics, Leipzig, 2016 [2023-02-26]. https://ceur-ws.org/Vol-1695/paper4.pdf.
[4] 史宇坤, 许姝艺, 董少春. 基于知识图谱的增强型混合式学习的教学实践与思考[J].高校地质学报,2022,28(3):387-393. DOI: 10.16108/j.issn1006-7493.2021085.
[5] Cope B, Kalantzis M, Zhai C, et al. Bioinformational philosophy and postdigital knowledge ecologies[M]. Cham: Springer, 2022: 133-159.
[6] 施江勇, 唐晋韬, 王勇军,等. 基于知识图谱的新兴领域课程教学资源建设[J]. 高等工程教育研究, 2022 (3): 15-20.
[7] 齐浩, 董少春, 张丽丽, 等. 地球科学知识图谱的构建与展望[J].高校地质学报,2020,26(1):2-10. DOI: 10.16108/j.issn1006-7493.2019099.
[8] Wu X, Duan J, Pan Y, et al. Medical knowledge graph: data sources, construction, reasoning, and applications[J]. Big Data Mining and Analytics, 2023, 6(2): 201-217. DOI: 10.26599/BDMA.2022.9020021.
[9] Li Z, Zhang Y, Huang R, et al. Construction of depression knowledge graph based on biomedical literature[C]//Proceedings of IEEE international conference on bioinformatics and biomedicine, Houston, USA, 2021. New York: IEEE, 2021: 1849-1855.
[10] 周倩, 魏涛, 胡紫宜, 等. 国内外临床教学中应用3D打印模型相关研究的知识图谱分析[J].中华医学教育杂志,2021,41(1):40-43. DOI: 10.3760/cma.j.cn115259-20200721-01092.
[11] World Federation for Medical Education. Basic medical education WFME global standards for quality improvement (the 2020 Revision) [EB/OL]. (2021-01-02) [2023-09-21]. https://wfme.org/wp-content/uploads/2020/12/WFME-BME-Standards-2020-1.pdf.
