Application and reflection of Artificial Intelligence Generated Content in empowering Immunology education
10.3969/j.issn.1000-484X.2025.06.011
- VernacularTitle:生成式人工智能赋能免疫学教学的应用与反思
- Author:
Yanli NIU
1
;
Liying MENG
;
Pengtao WANG
;
Lihui CHAI
;
Lingyun LIU
Author Information
1. 河南大学基础医学院,开封 475004
- Publication Type:Journal Article
- Keywords:
Artificial Intelligence Generated Content;
Teaching design;
Immunology
- From:
Chinese Journal of Immunology
2025;41(6):1328-1332
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the application effectiveness of Artificial Intelligence Generated Content(AIGC)in immuno-logy education and optimize teaching models to enhance students'clinical thinking and self-directed learning abilities.Methods:A questionnaire survey was conducted to analyze the current application status of AIGC among 105 university teachers.Taking"TypeⅠHypersensitivity"as an example,integrating AI tools to generate dynamic case scenarios and multimodal resources.Teaching effective-ness was evaluated through classroom practices and student questionnaires.Results:88.32%of teachers recognized AIGC's role in im-proving preparation efficiency,and 61.54%of students reported significantly improved learning outcomes.However,71.43%of teach-ers expressed concerns about increased student dependency,and 55.84%of teachers emphasized challenges in content quality control.Conclusion:AIGC effectively enhances teaching interactivity and personalized learning.Future efforts should focus on optimizing con-tent authority,establishing ethical guidelines,and promoting the development of human-AI collaborative educational models.
