Application of the artificial intelligence-assisted World Café teaching model in clinical pharmacology graduate course: a pilot study
Background: To investigate the application effectiveness of an artificial intelligence (AI)-assisted World Café teaching model in graduate-level clinical pharmacology course and to evaluate its impact on facilitating students' acquisition and integration of professional knowledge, developing clinical decision-making competencies, and enriching the teaching-learning experience. Methods: A pilot study was conducted involving 56 first-year master's students enrolled in a clinical pharmacology course at Kunming Medical University. Instruction was organized around a complex comprehensive clinical case of depression. Students participated in a structured five-stage seminar using the World Café format, supported by AI tools to facilitate group discussions and learning. A multi-method assessment strategy was employed, integrating a teaching effectiveness perception questionnaire, a specialized knowledge test, and a comparative analysis of AI-generated versus instructor-generated scores on case discussion records. Results: > 0.05). Conclusion: The AI-assisted World Café model effectively promotes the assimilation of complex knowledge and fosters higher-order clinical decision-making abilities among clinical pharmacology graduate students. It facilitates a pedagogical shift from passive knowledge transmission toward active capacity building. Furthermore, AI demonstrated reliability and promising utility as a tool for formative assessment, offering empirical support for innovative human-computer collaborative teaching approaches.
Authors
- Lan Chun Zhang
- Qi Li (ORCID: https://orcid.org/0000-0001-8776-8730)
- Wei Yan Hu
- Yun Xia Xiong
- Hao Fei Yu
- Jian Ping Xie
- Hai Yun Luo
- Ying Guo
Institutions
- Minzu University of China (CN)
- Yunnan University (CN)
- Kunming Medical University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2026-04-24
- DOI
- https://doi.org/10.3389/fpubh.2026.1805521
- Primary Topic
- Simulation-Based Education in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00