创新创业理论研究与实践 ›› 2025, Vol. 8 ›› Issue (20): 1-4.

• 理论研究 •    下一篇

“人工智能 +”背景下高校体育“学练赛评”一体化的应用研究

何宜川1, 刘军2, 陈东方1   

  1. 1.北京邮电大学 体育部,北京 100876;
    2.北京邮电大学 人工智能学院,北京 100876
  • 出版日期:2025-10-25 发布日期:2025-11-18
  • 作者简介:何宜川(1994—),女,河北保定人,硕士研究生,讲师,研究方向:体育人文社会学、学生健康促进。
  • 基金资助:
    中国校园健康行动·教育教学研究项目“基于学生发展的高校教师教学能力提升研究”(EDU0517)

Application Research on the Integration of “Learning, Training, Competition and Evaluation” in University Sports under the Background of “Artificial Intelligence +”

HE Yichuan1, LIU Jun2, CHEN Dongfang1   

  1. 1. Department of Physical Education, Beijing University of Posts and Telecommunications, Beijing, 100876, China;
    2. School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  • Online:2025-10-25 Published:2025-11-18

摘要: 该文运用人体姿态估计算法、Wed技术研发智能体育动作识别系统,归纳其在高校体育课程、课余体育锻炼、训练、竞赛中的应用,创新高校体育“学练赛评”体系;运用实验研究法,验证该体系对学生评教和学生体质健康具有干预效果,以新理念、新方法提升学生体质健康水平,促进高校体育“学练赛评”一体化,深化高校体育育人与体教融合。结果显示:高校的智能体育“学练赛评”体系对大学生的评教情况和体测成绩产生了积极的干预效应,显著提高了大学生的评教分数,纵向分析实验组测试成绩,显示学生体测合格率呈逐年上升趋势;今后可进一步探讨拓宽该体系的干预维度与应用范围,优化人工智能技术在高校体育领域的应用环境,并将研究成果拓展至社会体育与竞技体育层面。

关键词: “人工智能 +”, 智能体育动作识别系统, 高校体育, “学练赛评”一体化, 学生评教, 体质健康

Abstract: This article uses human pose estimation algorithms and Wed technology to develop an intelligent sports action recognition system, summarizes its application in university physical education courses, extracurricular physical exercise, training, and competitions, and innovates the“learning practice competition evaluation”system in university physical education; Using experimental research methods, verify the intervention effects of this system on student evaluation and physical health, improve students'physical health level with new concepts and methods, promote the integration of learning, practice, competition, and evaluation in university sports, and deepen the integration of university sports education and physical education. The results showed that the intelligent sports learning and training competition evaluation system of the university had a positive intervention effect on the evaluation and physical test scores of college students, significantly improving their evaluation scores. Longitudinal analysis of the experimental group test scores showed that the pass rate of students'physical tests was increasing year by year. In the future, further exploration can be conducted to broaden the intervention dimensions and application scope of this system, optimize the application environment of artificial intelligence technology in the field of school sports, and expand the research results to the level of social sports and competitive sports.

Key words: “Artificial intelligence +”, Intelligent sports action recognition system, College sports, Integration of “learning,training,competition,and evaluation”, Student evaluation of teaching, Physical health

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