Application and effectiveness analysis of a hybrid learning model based on knowledge graph and AI teaching assistant in the course of Health Assessment

Lu Minmin; Wang Junqiao; Jia Shoumei; Chen Yu; Xie Boqin

doi:10.3760/cma.j.cn116021-20250811-02169

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Application and effectiveness analysis of a hybrid learning model based on knowledge graph and AI teaching assistant in the course of Health Assessment

Digital Intelligence Nursing Education Column | 更新时间：2026-05-02

- Application and effectiveness analysis of a hybrid learning model based on knowledge graph and AI teaching assistant in the course of Health Assessment
- Chinese Journal of Medical Education Research Vol. 25, Issue 4, Pages: 392-398(2026)
- 作者机构：
  
  复旦大学护理学院，上海 200032
- 作者简介：
  
  Lu Minmin, Email: lmm789@fudan.edu.cn
- 基金信息：
  
  Fudan University Project of Undergraduate Teaching Reform(FD2025A134)
- DOI：10.3760/cma.j.cn116021-20250811-02169
  CLC： R47
- Received：11 August 2025，
  
  Published：20 April 2026
- 稿件说明：
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陆敏敏, 王君俏, 贾守梅, 等. 基于知识图谱的AI助教混合式教学模式在《健康评估》课程中的应用及效果分析[J]. 中华医学教育探索杂志, 2026, 25(4): 392-398.

Lu Minmin, Wang Junqiao, Jia Shoumei, et al. Application and effectiveness analysis of a hybrid learning model based on knowledge graph and AI teaching assistant in the course of Health Assessment[J]. Chinese Journal of Medical Education Research, 2026, 25(4): 392-398.
陆敏敏, 王君俏, 贾守梅, 等. 基于知识图谱的AI助教混合式教学模式在《健康评估》课程中的应用及效果分析[J]. 中华医学教育探索杂志, 2026, 25(4): 392-398. DOI： 10.3760/cma.j.cn116021-20250811-02169.

Lu Minmin, Wang Junqiao, Jia Shoumei, et al. Application and effectiveness analysis of a hybrid learning model based on knowledge graph and AI teaching assistant in the course of Health Assessment[J]. Chinese Journal of Medical Education Research, 2026, 25(4): 392-398. DOI： 10.3760/cma.j.cn116021-20250811-02169.

摘要

目的

在《健康评估》课程中应用基于知识图谱的AI助教的混合式教学模式并评价其教学效果。

方法

采用历史对照研究，选取复旦大学2022级和2023级护理学院本科生作为研究对象，按年级分为研究组（64例）和对照组（63例）。研究组采用基于知识图谱的AI助教的混合式教学模式，包括课前课程资源建设、开展基于知识图谱和AI助教的线上学习、线下讨论为主的课堂学习及课后的个性化学习等，对照组仅采用线上线下的混合式教学模式。通过对比2组学生的期末成绩、课程满意度，并结合对研究组的问卷调查和半结构式访谈，评价教学效果。采用SPSS 26.0进行统计分析。

结果

在期末考试成绩上，2组差异无统计学意义；在课程满意度上，研究组[（9.08±0.82）分

]

高于对照组[（8.32±1.61）分

]

（

=3.35，

0.01）。问卷调查显示，93.75%的学生（60例）认为基于知识图谱的AI助教的混合式教学模式有助于促使主动学习；100.00%的学生（64例）认为能培养临床思维；82.81%的学生（53例）认为有助于提高知识的理解度、掌握知识点、发现知识薄弱点；87.50%的学生（56例）认为有助于组织有效复习，85.94%的学生（55例）认为能提升学习效率。半结构式访谈结果显示，受访者认为基于知识图谱的AI助教有助于理清知识点、理顺学习思路；促进主动学习，发现遗漏的知识点；加深知识的理解、思考与应用，拓展学习资料；答疑解惑；组织课程知识点复习。

结论

基于知识图谱的AI助教的混合式教学模式有助于学生主动学习，提高学习效率和效果，培养临床思维。

Abstract

Objective

To apply a hybrid learning model based on knowledge graph and artificial intelligence (AI) teaching assistant in the course of Health Assessment and evaluate the teaching effectiveness.

Methods

A historical control method was employed

involving undergraduate students from the School of Nursing

Fudan University

who were enrolled in 2022 and 2023. Students were divided into an experimental group (

=64) and a control group (

=63) based on their grades. The experimental group adopted a hybrid learning model based on knowledge graph and AI teaching assistant

including pre-class course resource construction

online learning based on knowledge graph and AI teaching assistant

classroom learning focused on offline discussion

and post-class personalized learning. The control group only received a hybrid online-offline learning model. Teaching effectiveness was evaluated by comparing the scores of the final exam and course satisfaction of two groups of students

as well as the results of questionnaire survey and semi-structured interview

with the experimental group. Statistical analysis was conducted using SPSS 26.0.

Results

There was no significant difference in the final exam score between the two groups. The score of course satisfaction of the experimental group was significantly higher than the control group [(9.08±0.82) vs. (8.32±1.61)

=3.35

0.01

]

. The questionnaire survey revealed that 93.75% (

=60) of students in the experimental group believed that the hybrid learning model based on knowledge graph and AI teaching assistant could facilitate active learning

100.00% (

=64) believed that it could cultivate clinical thinking

82.81% (

=53) believed that it could improve their understanding of knowledge

help to master knowledge points

and discover knowledge gaps

87.50% (

=56) believed it could organize effective review

and 85.94% (

=55) believed it could improve learning efficiency. The semi-structured interview showed that respondents believed that knowledge graphs and AI teaching assistants helped to clarify knowledge points

streamline learning strategies

facilitate active learning

identify overlooked knowledge points

deepen the understanding

thinking

and application of knowledge

expand learning materials

answer questions

and organize course knowledge point reviews.

Conclusions

The hybrid learning model based on knowledge graph and AI teaching assistant is helpful for students to actively learn

improve learning efficiency and effectiveness

and cultivate clinical thinking.

关键词

Keywords

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