ERIC Number: EJ1477302
Record Type: Journal
Publication Date: 2025
Pages: 22
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1548-1093
EISSN: EISSN-1548-1107
Available Date: 0000-00-00
Exploiting Machine Learning Techniques to Discover Physical Fitness Patterns among Diverse Clusters of Female College Students
Yibing Wang; Yunxiang Pang; Siji Wang; Yiqun Pang; Xiaobing Wang
International Journal of Web-Based Learning and Teaching Technologies, v20 n1 2025
To target improving the physical fitness for female college students and to meet the individualized needs of different subgroups. A total of 6987 female college students from a teacher training college were assessed for physical fitness. Their fitness indices were analyzed using K-means clustering and GBDT regression algorithms. Based on physical fitness profiles, students were grouped into four categories: Category I (Normal body shape, average fitness and athletic ability); Category II (Normal body shape, good fitness and athletic ability); Category III (Short, poor fitness and athletic ability); Category IV (Overall excellent fitness). Physical development and factors influencing the 800-meter run vary across groups of female college students. This study provides insights for more targeted interventions to improve specific physical fitness.
Descriptors: Artificial Intelligence, Females, College Students, Physical Fitness, Student Needs, Body Composition, Physical Development, Intervention, Student Characteristics, Training, Foreign Countries
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: China
Grant or Contract Numbers: N/A
Author Affiliations: N/A