Individualized New Teaching Mode for Sports Biomechanics based on Big Data

Abstract

Sports biomechanics is an applied discipline with relatively strong theoretical knowledge. At present, it is used as an analysis means in exercise training in various countries and plays a huge promotion role for the development of competitive sports and sports science. However, phenomena, such as single-teaching methods, fixed-teaching thinking, backward-teaching environment, and hardware, still exist in the current education for sports biomechanics. For such phenomena, we perform individualized IRDC (Internet + retrieval literature + big data + cloud) teaching by using the Internet big data analysis and considering different characteristics of every student and apply it in online teaching of sports biomechanics course. We base our proposed individualized IRDC teaching mode on postmodern curriculum theory. According to four features, namely, rich, recursive, relational, and rigorous, we propose an individualized IRDC online teaching mode in this study. Moreover, we apply a new wireless telemetry surface EMG tester as a learning tool of practical teaching in the teaching mode, which we use to acquire Internet information data of online course and induce a real time communication between teachers and students. Finally, we adopt the principal component analysis to develop evaluation indices, including expert evaluation in and out of school and peer teacher evaluation, for the teaching mode. We find through teaching practice that the proposed individualized IRDC teaching mode can make the best of advantages of big data teaching, help teachers implement targeted individualized teaching, and contribute to the improvement of students' academic performance and comprehensive qualities.

AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets

“…These predictions can inform the design of training sessions to avoid premature fatigue and can be used to optimize in-game strategies, such as player substitutions in team sports. Optimization of recovery protocols [ 31 , 32 ]: AI can also monitor recovery, assessing whether an athlete’s biomechanical signals have returned to their baseline post-exertion. This information can guide the type and duration of recovery methods applied, such as active recovery, massage, or specialized nutrition intake.…”

“…This involves analyzing how long an athlete can maintain a certain intensity level before fatigue sets in, and how this capacity changes with different training regimens, environmental conditions, or stages of the competitive season.4.Predictive fatigue onset detection[30]: by leveraging historical data, AI can predict when an athlete is likely to become fatigued in future training sessions or competitions. These predictions can inform the design of training sessions to avoid premature fatigue and can be used to optimize in-game strategies, such as player substitutions in team sports.5.Optimization of recovery protocols[31,32]: AI can also monitor recovery, assessing whether an athlete's biomechanical signals have returned to their baseline postexertion. This information can guide the type and duration of recovery methods applied, such as active recovery, massage, or specialized nutrition intake.…”

Strategies for Improving Data Literacy of University Teachers in The Era of Big Data

“…Recent online teaching platforms, such as the flipped classroom [4], rely heavily on online activities and big data technologies. To this phenomenon of fixed teaching ideas, single teaching methods, and backward teaching hardware in current course teaching, Ying Liu et al [5] used big data for Internet analysis and explored a personalized IRDC (Internet + retrieval of literature + big data + cloud) course teaching model by combining different characteristics of students. In order to improve the pedagogical efficiency of the course teaching, and to address the drawback that the huge scale of the data itself in the traditional teaching model is prone to errors and data loss, Süleyman Eken [6] developed an exploratory teaching program for big data analysis, which aims to familiarize students with the key techniques for storing, using, and analyzing big data.…”

The Application of Human–Computer Interaction Technology Fused With Artificial Intelligence in Sports Moving Target Detection Education for College Athlete

“…Athletic abilities include professional skills, professional intelligence, physical fitness, and psychological quality. Especially, for excellent athletes whose intelligence and professional skills have reached a fairly high level, the impact of physical fitness on their sports career may be crucial (Liu and Zhu, 2020). According to the situation of athletes, scientific and effective physical exercises are made, which can not only help athletes approach the limit of sports ability, improve the effect of sports training, but also effectively prevent sports injury.…”