评估在医学教育中使用大型语言模型的使用:来自本科医学学生的见解
Sairavi Kiran Biri1, Subir Kumar2, Muralidhar Panigrahi3
1Biochemistry, Phulo Jhano Medical College, Dumka, IND.
Cureus
|November 29, 2023
概括
医学本科生对在教育中使用大型语言模型 (LLM) 持积极态度,但他们的知识和实践有限. 需要进一步规划,以便有效地将LLM纳入医学培训.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 教育技术的教育技术
背景情况:
- 人工智能 (AI) 具有将其整合到医学教育中的巨大潜力.
- 大型语言模型 (LLM),包括ChatGPT,谷歌Bard和微软Bing,是先进的自然语言处理工具.
- 本研究探讨了医学教育中LLM利用的现状.
研究的目的:
- 调查医学本科生关于LLM使用的知识,态度和实践.
- 评估目前在印度哈邦医学教育中的LLM整合水平.
- 确定在医学培训中采用LLM的潜在障碍和促进者.
主要方法:
- 对370名医学本科生进行了横截面在线调查.
- 问卷评估了使用验证领域的知识,态度和实践 (克朗巴赫的α>0.7).
- 使用ANOVA分析数据,以比较跨领域的得分,统计显著性设置为p < 0.0001.1.
主要成果:
- 共有172名学生参与 (46.49%的响应率).
- 大多数 (45.93%) 报告说,在教学和学习中很少使用LLMs.
- 态度得分 (3.47±0.54) 显著高于知识 (3.21±0.55) 和实践 (3.26±0.61) 的得分 (p < 0.0001).
结论:
- 医学学生通常对将LLMs纳入他们的教育表现出积极的态度.
- 学生们仍然担心LLMs的过度依赖和潜在的不准确性.
- 战略规划对于有效整合LLMs来增强医学学习资源和可访问性至关重要.
关键词:
人工智能的人工智能是人工智能.我们的态度 态度 态度 态度 态度聊天 聊天 聊天情报 情报 情报 的情报 情报 的情报.知识的知识知识的知识.医学院的学生 医学院的学生在实践中,实践实践.搜索引擎搜索引擎搜索引擎是什么调查和问卷调查和问卷调查.更多相关视频
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