Football College, Wuhan Sports University, Wuhan Hubei 430077, China.
Comput Math Methods Med. 2022 Jun 28;2022:7174246. doi: 10.1155/2022/7174246. eCollection 2022.
The arrival of the big data era has opened up new avenues for assessing the quality of physical education instruction. Using big data to explore these systems may help improve the quality of physical education itself, in addition to assisting schools in developing quality assessment systems for physical education. More and more schools are making football a compulsory part of their physical education and wellness curriculum. Therefore, this study used the methods of literature materials, expert interviews, questionnaires, and Delphi method to determine the evaluation indicators and index weight coefficients of football teaching and borrowed the application background of big data to initially explore the construction of a football teaching quality evaluation system. To this end, this paper completes the following tasks: (1) The current state of football teaching quality evaluation studies in the United States and internationally is summarized. (2) A football teaching quality evaluation system based on the background of big data is constructed. (3) Our experiments show that the assessment approach described in this study is scientifically and rationally distributed and can accurately represent all components of physical education. As a result, evaluating football instruction using big data is a possibility.
大数据时代的到来为评估体育教学质量开辟了新的途径。利用大数据探索这些系统，除了帮助学校制定体育教育质量评估体系外，还有助于提高体育教育本身的质量。越来越多的学校将足球作为体育和健康课程的必修部分。因此，本研究采用文献资料、专家访谈、问卷调查和德尔菲法确定了足球教学的评价指标和指标权重系数，并借鉴大数据的应用背景，初步探讨了足球教学质量评价体系的构建。为此，本文完成了以下任务：（1）总结了美国和国际上足球教学质量评价研究的现状。（2）构建了基于大数据背景的足球教学质量评价体系。（3）实验表明，本研究中描述的评估方法在科学和理性上分布均匀，能够准确地代表体育教育的所有组成部分。因此，利用大数据评估足球教学是可行的。
