药学教育中的生成人工智能 (Gen-AI):对学术诚信的利用和影响:一个范围审查
R Mortlock1, C Lucas1,2,3
1Graduate School of Health, Faculty of Health, University of Technology, Sydney, Australia.
Exploratory research in clinical and social pharmacy
|August 26, 2024
概括
生成型人工智能 (Gen-AI) 在药学教育中提供了好处,但对学术诚信的风险未得到充分探索. 灰色文献提供了降低风险的策略,强调道德培训和评估重新设计.
科学领域:
- 药房 教育 教育 药房 教育
- 教育中的人工智能
- 学术诚信 学术诚信
背景情况:
- 生成型人工智能 (Gen-AI),包括像ChatGPT这样的工具,在健康教育中越来越多地被采用.
- 药房教育面临着Gen-AI整合的潜在好处和重大风险.
- 需要评估和减轻与药房课程中的Gen-AI相关的风险.
研究的目的:
- 对Gen-AI在药学教育中的影响进行范围审查.
- 确定目前在这个领域使用的Gen-AI的现有用途和新兴证据.
- 专注于减轻学术诚信潜在风险的战略.
主要方法:
- 采用了遵循PRISMA-ScR指南的范围审查方法.
- 搜索的数据库包括PubMed,ERIC,Scopus和ProQuest (2000年1月至2024年2月).这些数据库的搜索范围包括:
- 灰色文献的搜索涵盖了机构政策和指导方针,补充了传统的学术来源.
主要成果:
- 包括来自科学数据库的12篇文章和来自灰色文学的9条记录.
- 虽然在药学教育中注意到Gen-AI的好处,但发表的关于学术诚信风险的研究很少.
- 灰色文献主要提供风险减轻策略,包括加强伦理培训和评估重新设计.
结论:
- 基于证据的方法对于管理药学教育中的Gen-AI挑战至关重要.
- 缓解策略存在,主要在灰色文献中,但发表的关于实际道德实施的科学文献有限.
- 需要进一步研究在药学课程中负责任地使用Gen-AI以及有效地减轻学术诚信风险.
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