评估临床医学学生接受大型语言模型的评估:基于技术接受模型
Fuze Liu1, Xiao Chang1, Qi Zhu1
1Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Beijing, 100730, People's Republic of China.
医学学生对学习大语言模型 (LLM) 的接受度很高. 态度是它们使用的关键,感知到的风险和社会影响也会影响医学教育中的采用.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 技术的接受技术的接受
背景情况:
- 大型语言模型 (LLM) 在医学教育中表现有前途.
- 了解医学学生对LLMs的接受度至关重要.
- 影响LLM采用的因素需要调查.
研究的目的:
- 探索医学学生对学习中的法学士的接受.
- 使用技术接受模型 (TAM) 检查影响LLM接受的因素.
- 评估态度的作用,感知到的有用性,易用性,感知到的风险和社会影响.
主要方法:
- 对中国的医学学生进行了问卷调查.
- 应用了技术接受模型 (TAM) 框架.
- 使用统计分析来确定影响因素.
主要成果:
- 医学学生表现出很高的意愿使用LLMs.
- 态度显著预测了使用LLM的行为意图,调解了其他因素.
- 感知风险和社会影响直接影响了行为意图.
结论:
- 该TAM适用于医学教育的LLM接受.
- 态度是医学学生采用LLMs的核心.
- 医学学位是医学学生学习的有价值的辅助工具.
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