目的 研究知识图谱在流行病学教学中的应用及其促进深度学习效果、提升教学质量的影响,为推进数智化课程改革提供参考。方法 采用横断面调查研究设计。2024年9—12月,采用整群抽样方法,选取2022级卫生检验与检疫专业86名本科学生为研究对象,在流行病学课程教学中使用线上知识图谱教学模块辅助开展教学。设计调查问卷调查学生的学分绩点、学习习惯、学习目的等信息和知识图谱助力学生深度学习的效果。通过多元线性回归分析学生深度学习效果以及过程性、终结性考核成绩的影响因素。结果 研究对象的知识图谱学习效果评分为90.0(12.5)分,深度学习效果自评评分为36.0(7.2)分,过程性考核成绩为88.0(10.5)分,终结性考核成绩为71.5(32.5)分。单因素分析发现,具备每天课后复习时间长、上学期学分绩点高、探索能力和学以致用能力强等学习特征的学生流行病学知识图谱的学习效果更好(均P<0.05)。多元线性回归分析结果表明,学生的知识图谱学习效果是其深度学习自评的正向因素(P=0.010)。在教学质量评价中,知识图谱学习效果评分是过程性考核成绩和终结性考核成绩的正向影响因素(P<0.001;P=0.042)。学生的探索能力强对提高过程性成绩、终结性成绩有促进作用(P=0.021;P=0.032)。结论 将知识图谱融入流行病学课程教学,引导学生培养深度学习能力、探索能力等个性化学习特征,可以有效提升数智化课程改革的深度学习效果和教学质量效果。

Objective To investigate the application and teaching effects of Knowledge Graph (KG) in promoting deep learning in epidemiology course, and to provide references for mathematical intelligence curriculum reform. Methods From September 2024 to December 2024, undergraduate students majoring in health inspection and quarantine enrolled in 2022 were selected as the research participants. An online KG teaching module was used to assist in the teaching process of Epidemiology course. Information including grade point averages, learning attitudes, learning habits, as well as the learning effects of KG on their deep learning were collected through online questionnaires. Multiple linear regression analysis was used to study the influencing factors of students′ deep learning effects and the process and final assessment scores. Results The KG learning effect score of was 90.0 (12.5), and the self-assessment score of deep learning effect was 36.0 (7.2). The process assessment score was 88.0 (10.5), and the final assessment score was 71.5 (32.5). Univariate analysis found that students with characteristics such as long daily review time after class, high grade point average in the previous semester, strong exploration ability, and strong ability to apply knowledge to practice had better learning effects with the knowledge graph (all P<0.05). Multiple linear regression analysis indicated that students′ knowledge graph learning effect was a positive factor for their self-assessment of deep learning (P=0.010). The knowledge graph learning effect score was a positive influencing factor for process assessment scores and final assessment scores (P<0.001; P=0.042). Strong exploration ability of students promoted the improvement of process assessment scores and final assessment scores (P=0.021; P=0.032). Conclusions Integrating KG into the teaching of Epidemiology courses could guide the students to cultivate personalized learning characteristics, including deep learning abilities and exploration abilities, and enhance the deep learning effects and teaching quality in mathematical intelligence curriculum reforms.