Analysis of the mixed teaching of college physical education based on the health big data and blockchain technology

Abstract

In the era of health big data, with the continuous development of information technology, students’ physical health management also relies more on various information technologies. Blockchain, as an emerging technology in recent years, has the characteristics of high efficiency and intelligence. College physical education is an important part of college students’ health big data. Unlike cultural classes, physical education with its rich movements and activities, leaves teachers no time to monitor students’ real classroom performance. Therefore, we propose a human pose estimation method based on cross-attention-based Transformer multi-scale representation learning to monitor students’ class concentration. Firstly, the feature maps with different resolution are obtained by deep convolutional network and these feature maps are transformed into multi-scale visual markers. Secondly, we propose a cross-attention module with the multi-scales. The module reduces the redundancy of key point markers and the number of cross fusion operations through multiple interactions between feature markers with different resolutions and the strategy of moving key points for key point markers. Finally, the cross-attention fusion module extracts feature information of different scales from feature tags to form key tags. We can confirm the performance of the cross-attention module and the fusion module by the experimental results conducting on MSCOCO datasets, which can effectively promote the Transformer encoder to learn the association relationship between key points. Compared with the completive TokenPose method, our method can reduce the computational cost by 11.8% without reducing the performance.

Research on the construction of intelligent sports teaching ecosystem in universities based on multi-data chain technology

“…Smart teaching in colleges and universities has become one of the trends of modern education and has played an important role in promoting informationization and intelligence in education [1][2]. Smart physical education teaching is one of the important areas, which is not only an extension of traditional education methods, but also an in-depth reform and innovation of education philosophy, curriculum system, teaching methods, practical links, and other aspects [3][4]. However, in reality, there are still certain problems and challenges in the teaching of intelligent physical education in colleges and universities [5].…”

Web-Semantic-Driven Machine Learning and Blockchain for Transformative Change in the Future of Physical Education

“…To maximize the promise of machine learning in physical education, blockchain technology can be leveraged to offer secure and immutable storage of student data while ensuring data integrity and privacy. Physical education can adopt innovative and dependable platforms by leveraging the transparency and decentralized nature of blockchain, empowering students to take charge of their educational journey and promoting a more inclusive and collaborative educational ecosystem, as shown in Figure 1 (Liu & Li, 2023;Dziatkovskii, 2023). The potential of machine learning has resulted in a dramatic shift in the field of physical education, and teachers can now develop individualized learning experiences that meet the specific needs of each student by using machine learning algorithms to evaluate data on behavior and performance.…”