一项基于可解释机器学习的研究,研究了影响中国中学生参与数字体育运动的因素
XiaoTao Cai1, Yi Xian1, TongYi Liu2
1Institute of Physical Education, Sichuan University, Chengdu, 610065, China.
Scientific reports
|May 5, 2025
概括
学术重点和有限的体育教育阻碍了香港学生的数字体育参与. 增加体育课程和资源可以促进数字体育参与.
科学领域:
- 教育技术的教育技术
- 运动科学 运动科学 运动科学
- 体育社会学运动的社会学.
背景情况:
- 数字设备的使用在青少年中越来越普遍.
- 了解影响数字体育参与的因素对于促进体育活动至关重要.
- 香港以学术为中心的文化可能会影响年轻人参与体育活动.
研究的目的:
- 调查影响中学生参与数字体育运动的因素.
- 为了确定这些影响因素的值效应.
- 开发和验证用于预测数字体育参与的机器学习模型.
主要方法:
- 在2018年国际学生评估计划 (PISA) 中利用了4,925名香港学生的数据.
- 采用多级逻辑回归和机器学习模型 (GNB,GBDT,KNN,LR,集体堆叠) 具有5倍交叉验证.
- 使用群群图和特征依赖图进行了可解释性分析.
主要成果:
- 学业成绩,每周的体育课程,家庭和学校的ICT资源,以及ICT的社会认知显著影响了数字体育参与.
- 确定了每周两天体育课程的门.
- 高学业成绩与较低的数字体育参与有关.
结论:
- 文化偏好学术人员而不是体育活动,体育运动频率,ICT资源和社会对ICT的看法造成了数字体育参与差异.
- 学业成绩高的学生需要有针对性的数字体育推广.
- 建议将PE增加至每周至少两天,并加强数字基础设施.
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