Application of Deep Learning in College Physical Education Design under Flipped Classroom

Abstract

With the development of information technology, teaching reform has also undergone major changes. e traditional college physical education teaching method cannot meet the needs of the majority of students, and the physical education teaching mode continues to be reformed. Microcourse is the most intuitive form of deep integration of information technology and physical education. From the perspective of the ipped classroom (FC), the physical education model has gradually changed from teacher centered to student centered. Deep learning (DL) emphasizes that learners have the ability to actively construct knowledge, e ectively transfer knowledge, and solve real problems. is design applies DL and convolutional neural network to the teaching design of physical gymnastics in colleges and universities.e application of the DL teaching model based on FC in the microcourse teaching of gymnastics in colleges and universities is studied and evaluated. e results show that the current utilization of microcourse teaching resources is too low. Interest-oriented teaching microcourses cannot improve students' interests. e proportion of students who are interested is relatively small, and more than 50% of students are not interested. Teachers generally believe that the current gymnastics microcourse needs further optimization and improvement. e poor quality of microvideos and the lack of supervision and reward mechanism in the course are the main reasons for the insu cient students' interest. e complexity of the videos and the liveliness of the discussions are the main problems of low resource utilization. e student's interest in learning is greatly improved after the application of the designed model, and the proportion increases to 82.4%. e e ect on ordinary college students is the most obvious, and the e ect of microvideo learning has been signi cantly promoted. Design mode has the most obvious improvement in improving learning e ciency and autonomous learning ability. e improvement of learning ability has increased from 18% to 72%, and the improvement of learning e ciency has increased from 39% to 82%. Meanwhile, students' interest in learning is stimulated, and the utilization of resources is improved.

An Investigation of the Flipped Learning Method to Physical Education Classes in the University: Systematic Review

“…Likewise, in Taijiquan teaching the use of virtual reality technology, it has been found that the majority of students view virtual reality technology-assisted martial arts education as good, and their enthusiasm for learning martial arts has greatly increased (Zhang et al, 2021). Furthermore, in learning gymnastics, it was revealed in another study which reported that students' interest in learning greatly increased after implementing the designed model, namely DL theory combined with micro course theory in college sports gymnastics (Huang & Yu, 2022). In Investigation of Dance Sports, several studies reported that the use of the FL model produced positive results (Dimarucot, 2022).…”

“…technology-assisted martial arts education favorably, and their passion for studying martial arts has greatly increased. (Huang & Yu, 2022) Deep Learning based on FC in Microcourse Teaching of Gymnastics This study investigates focuses on various teaching methods and design teaching modes with the continuous advancement of the reform of university physical education. This design introduces the FC and studies the DL model.…”

Integrating deep learning techniques for personalized learning pathways in higher education

“…Authors [ 14 ] complement this discussion with their empirical research, presenting compelling case studies that highlight the improvements in student learning outcomes attributable to the use of AI-driven tools in educational contexts. Their findings advocate for the necessity of integrating DL algorithms in educational environments, not just as an enhancement but as a fundamental component in creating effective and personalized learning experiences [ [15] , [16] , [17] , [18] ]. They argue for the critical role of such AI-driven tools in shaping the future of education, envisioning an environment where learning is not only more engaging but also more attuned to individual student needs and preferences.…”

Factors Affecting the Physical Fitness of College Students and Improvement Strategies

“…In order to effectively enhance the physical health of college students, the nation has implemented relevant regulations and standards to promote their fitness levels [7] . This paper assesses the physical fitness of college students in accordance with the "National Student Physical Fitness Standards" and compiles statistical data regarding their test results [8] . Through various methodologies, it investigates and comprehends the physical health status of college students, identifying any existing health concerns [9] .…”