基于模糊的AI和ML应用在美国教育部门的教学中提高了教学意识
Naga Simhadri1, T N V R Swamy2
1Apparao Polireddi, IKON Tech Services LLC, Phoenix, AZ USA.
概括
美国的教育工作者在课堂上对人工智能 (AI) 和机器学习 (ML) 的知识有限. 这项研究探讨了美国高等教育当前的AI/ML应用,确定了好处,缺点和未来的研究方向.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 机器学习应用 机器学习应用
背景情况:
- 教育行业从人工智能和机器学习的进步中受益甚微.
- AI/ML系统的开发主要针对医疗保健和交通等部门,而不是高等教育.
- 需要了解美国教育机构采用AI/ML的现状.
研究的目的:
- 评估美国教育工作者在课堂上对AI和ML的知识水平.
- 调查AI/ML在美国大学和学院的当前应用,好处和缺点.
- 确定AI和ML在教育中的潜在未来研究方向.
主要方法:
- 研究方法的三角化.
- 审查国际最先进的报告和有关AI/ML在教育中的相关文献.
- 对美国教育部门有关AI和ML的官方文件的分析.
- 15个基于指导方针的专家采访,以证实调查结果.
主要成果:
- 介绍了在高等教育机构中使用的当前AI/ML系统的选择.
- 分析与实施这些AI/ML系统相关的优缺点.
- 关于人工智能和机器学习在教育领域的未来演变和潜力的猜测.
结论:
- 这项研究揭示了美国高等教育中AI和ML应用的关键领域.
- 识别了教育部门在教育工作者知识和AI/ML采用方面的差距.
- 建议关键的未来研究方向,以推进AI和ML在教育环境中.
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