Research on the Design of Assistant Basketball Teaching System Based on Big Data

• Published in: Computational intelligence and neuroscience Vol. 2022; pp. 1 - 12
• Main Authors: Wang, Lin, Wei, Xiaoyun, Yuan, Guoliang
• Format: Journal Article
• Language: English
• Published: United States Hindawi 2022; John Wiley & Sons, Inc
• Subjects: Basketball; Big Data; Databases, Factual; Design; Distance learning; Equipment and supplies; Exercise; Humans; HyperText Markup Language; Information technology; Internet; Java; Multimedia; Physical education; Server pages; Software utilities; Students; Systems design; Systems development; Teachers, Rating of; Teaching; Technology; Virtual reality; Websites
• ISSN: 1687-5265; 1687-5273; 1687-5273
• DOI: 10.1155/2022/1499555

Due to the limitations of the current teaching resources searched by the system, it is difficult to achieve good results in basketball teaching. For this reason, an auxiliary basketball teaching system based on big data is designed. On the basis of clarifying the basic principles of teaching system design, JSP (Java Server Pages) dynamic web page back-end technology and Tomcat 7.0 server are used as the system support structure. Take the big data environment as the source of teaching resources and match them to different databases according to the characteristics of the resources. And combined with real-time evaluation to achieve the assessment of teaching effects and the management of teaching resources, the test results show that the average score of the basketball technical action test under the guidance of this system is higher than 7.5 points when the experimental subjects have the same level of basketball skills. In the paired sample t-test and the independent sample t-test of the performance level test scores P=0.001<0.05, there is a significant difference. It shows that the system can effectively improve the teaching effect of basketball and improve students’ basketball test scores.