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关于人工智能在高等教育中的整合,以提高教学,学习和评估的范围的文献综述
Pradeep K Sahu1, Arvind Kumar2, Arlene Williams-Persad3
1Center for Medical Sciences Education, Faculty of Medical Sciences, The University of the West Indies, St. Augustine Campus, St. Augustine, Trinidad and Tobago, West Indies - pradeep.sahu@uwi.edu.
Panminerva medica
|January 20, 2026
概括
人工智能 (AI) 正通过改进教学和评估来改变高等教育. 负责任的采用需要解决道德问题,确保公平的访问,并制定强有力的政策,以实现有效的整合.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 高等教育 高等教育
背景情况:
- 人工智能 (AI) 在高等教育中的全球整合.
- 对教学,学习和评估的影响.
- 可持续和公平收养的挑战和机会.
研究的目的:
- 审查人工智能在高等教育中的全球整合.
- 检查人工智能对教学和评估的影响.
- 为负责任的人工智能采用确定挑战和机会.
主要方法:
- 根据PRISMA指南进行范围审查.
- 搜索科学网络和SciFinder进行研究 (2020-2024年).
- 使用Tranfield,Denyer和Smart (2003) 框架进行主题综合.
主要成果:
- 六个主题出现了:人工智能用于教学,学习,评估,道德,挑战和机会.
- 人工智能增强了个性化的学习和教学设计,但也引发了对学术完整性的担忧.
- 伦理问题 (数据隐私,偏见) 和挑战 (基础设施,人工智能素养) 是普遍存在的,特别是在资源不足的环境中.
结论:
- 人工智能正在重塑高等教育的教学和评估.
- 均衡的采用需要道德保障,教育工作者培训和政策框架.
- 优先考虑公平,基础设施和以人为中心的方法对于负责任的AI使用至关重要.
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