Personalized college physical education curriculum generation via hierarchical recommendation algorithm with biomechanics-driven optimization

With the rapid development of modern communication technology and multimedia technology, learners can obtain various learning resources in various ways. But the problem that comes with it is to obtain the knowledge needed by learners from many resources efficiently, quickly and effectively, so as to complete the systematic study of college physical education personalized courses. Since 1980s, personalized learning and personalized service in the network learning environment have been studied accordingly. The related research involves many information science fields such as information retrieval, data mining, artificial intelligence, computer communication and network, but the research on the generation of personalized curriculum of college physical education is relatively few. This paper mainly focuses on the research and realization of personalized curriculum generation technology of college physical education, and explores the solution to realize the individualization of college physical education learning content in the process of large-scale online education. A hierarchical recommendation algorithm based on multi-dimensional feature vector is proposed, with a unique emphasis on integrating biomechanics. By analyzing biomechanical indicators like joint mobility, muscle strength, and body coordination of students, the algorithm can accurately assess their physical conditions. This integration can not only help physical education teachers make the overall teaching plan, but also meet the needs of college students’ individual knowledge and ability characteristics for curriculum learning. In addition, the hierarchical implementation of the recommendation algorithm distributes the recommendation of large-scale knowledge base and resource base at different levels, which effectively reduces the dimension, reduces the amount of calculation and improves the efficiency of the implementation of the personalized curriculum generation algorithm of college physical education. Biomechanics-driven optimization ensures that the recommended courses are not only knowledge - based but also safe and effective for students from a biomechanical perspective, enhancing the overall quality of personalized PE curricula.

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Publication Details

Journal
Molecular & cellular biomechanics
Published
2025-02-07
DOI
https://doi.org/10.62617/mcb836
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

Personalized college physical education curriculum generation via hierarchical recommendation algorithm with biomechanics-driven optimization

X. Liu, Zidi Wang, Su Gao, Jinting Yao
Molecular & cellular biomechanics
Educational Technology and Pedagogy
article

Personalized college physical education curriculum generation via hierarchical recommendation algorithm with biomechanics-driven optimization

X. Liu, Zidi Wang, Su Gao, Jinting Yao
article en

Abstract

With the rapid development of modern communication technology and multimedia technology, learners can obtain various learning resources in various ways. But the problem that comes with it is to obtain the knowledge needed by learners from many resources efficiently, quickly and effectively, so as to complete the systematic study of college physical education personalized courses. Since 1980s, personalized learning and personalized service in the network learning environment have been studied accordingly. The related research involves many information science fields such as information retrieval, data mining, artificial intelligence, computer communication and network, but the research on the generation of personalized curriculum of college physical education is relatively few. This paper mainly focuses on the research and realization of personalized curriculum generation technology of college physical education, and explores the solution to realize the individualization of college physical education learning content in the process of large-scale online education. A hierarchical recommendation algorithm based on multi-dimensional feature vector is proposed, with a unique emphasis on integrating biomechanics. By analyzing biomechanical indicators like joint mobility, muscle strength, and body coordination of students, the algorithm can accurately assess their physical conditions. This integration can not only help physical education teachers make the overall teaching plan, but also meet the needs of college students’ individual knowledge and ability characteristics for curriculum learning. In addition, the hierarchical implementation of the recommendation algorithm distributes the recommendation of large-scale knowledge base and resource base at different levels, which effectively reduces the dimension, reduces the amount of calculation and improves the efficiency of the implementation of the personalized curriculum generation algorithm of college physical education. Biomechanics-driven optimization ensures that the recommended courses are not only knowledge - based but also safe and effective for students from a biomechanical perspective, enhancing the overall quality of personalized PE curricula.

Molecular & cellular biomechanicsVol. 22(2)
North Minzu University (CN), Hebei University of Chinese Medicine (CN), Hebei Normal University (CN), Hebei Institute of Physical Education (CN)
Quality Education
Openalex Percentile: Top 99%
Educational Technology and Pedagogy
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