在内部跳舞:与教师-AI合作的在线舞蹈学习的定性研究
Jiwon Kang1, Chaewon Kang1, Jeewoo Yoon1,2
1Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul, Republic of Korea.
概括
DancingInside通过人工智能驱动的反和教师-人工智能合作来增强在线舞蹈学习. 该系统支持学生的实践反思和绩效改进,强调人类教师在人工智能辅助教育中的重要作用.
科学领域:
- 舞蹈教育 舞蹈教育 教育
- 人与计算机的交互
- 教育中的人工智能
背景情况:
- 在线舞蹈学习面临着由于距离和异步格式的学生-教师互动的挑战.
- 传统舞蹈课提供了比远程学习环境更直接的互动.
研究的目的:
- 介绍DancingInside,一个在线舞蹈学习系统,旨在改善学生和教师之间的互动.
- 为了利用教师-AI合作,在舞蹈教育中提供及时和充分的反.
主要方法:
- 使用2D姿势估计方法开发人工智能导师,以比较学习者和教师的表现.
- 一项为期两周的用户研究,涉及11名学生和4名教师,以评估该系统.
- 对反和采访进行定性分析,以了解用户体验.
主要成果:
- 人工智能导师通过多式联络反有效地支持学习者实践反思和绩效提升.
- 学生和教师发现人工智能导师对实践和改进有好处.
- 人类教师对于补充AI反和指导学习过程至关重要.
结论:
- DancingInside展示了AI-AI合作在在线舞蹈教育中的潜力.
- 该系统可以通过提供有价值的反和支持实践来增强远程舞蹈学习.
- 未来的人工智能支持的舞蹈学习系统应该整合人类教师来优化学习体验.
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