优化年轻网球运动员的发展:探索新兴技术对培训效率和技术技能获取的影响
Sheng Liu1, Chenxi Wu1, Shurong Xiao1
1Department of Physical Education and Military Education, Jingdezhen Ceramic University, Xianghu Town, Jingdezhen City, Jiangxi Province, China.
PloS one
|August 7, 2024
概括
人工智能教练系统,虚拟现实和可穿戴传感器显著提高了网球技能. 频繁的体育训练也可以提高表现,但传统的计划和个性化的学习对年轻球员的技能发展的影响很小.
科学领域:
- 体育科学与技术 体育科学与技术
- 获得运动技能 获得运动技能
- 在体育运动中的人机交互
背景情况:
- 发展技术网球技巧对于年轻球员的成功至关重要.
- 新兴技术为培训和提高技能提供了潜在的新途径.
- 各种培训方法和技术的有效性需要经验验证.
研究的目的:
- 分析每周训练计划,体育训练频率,AI教练系统,虚拟现实 (VR) 环境和可穿戴传感器对技术网球技能的影响.
- 研究个性化学习在培训干预和技能获取之间的关系中的调解作用.
- 为优化网球训练策略提供基于证据的建议.
主要方法:
- 量化调查方法使用了374名年轻网球运动员的初级数据.
- 确认因素分析 (CFA) 用于评估模型的适应性.
- 结构方程建模 (SEM) 用于测试假设和调解效应.
主要成果:
- 身体训练频率,人工智能辅导系统,虚拟现实训练环境和可穿戴传感器显著影响了技术技能的获得 (p < 0.001).
- 每周的培训计划和个性化学习对技能发展没有显著影响.
- 个性化学习不是培训方法/技术和技术能力之间的重要调解者.
结论:
- 人工智能教练,虚拟现实和可穿戴传感器是提高技术网球技能的有效工具.
- 组织应该投资于这些技术,并对其整合培训教练.
- 进一步的研究可能会探索个性化学习在技能获取中的细微差别.
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