Search

Constructing Autonomous Exercise Programs for College Students Guided by Physical Fitness Monitoring Data

Author(s)

Weihong Wang

Affiliation(s)

Huanghe Science and Technology University, Zhengzhou, China

Abstract

Physical fitness data collected from college students are often reported but seldom used to guide exercise outside class. Drawing on a review of related research, this study identifies five obstacles to building data-guided autonomous exercise programs: broken feedback loops, homogeneous program supply, weak motivation transfer, imprecise support for underconditioned students, and the absence of ongoing adjustment. Five corresponding strategies are proposed: an integrated data service covering monitoring, feedback, and interpretation; a stratified program library matched to individual profiles; quantified goals with progressive tasks; digitally delivered targeted support; and dynamic adjustment driven by movement-quality monitoring and periodic retesting. Together these strategies form a closed loop of monitoring, feedback, programming, and retesting, and offer a practical reference for universities that intend to turn fitness data into guidance for students' independent exercise.

Keywords

Physical Fitness Monitoring; College Students; Autonomous Exercise; Exercise Program; Digital Health Intervention

References

[1] Zeng Diqin, Fan Lianxiang. Effects of self-monitoring of physical fitness on college students' exercise motivation[C]//China Sport Science Society. Abstract Collection of the 5th National Fitness Science Conference: Poster Communication (II). 2024: 2052-2053. [2] Zhang Liping, Luo Lin, Zhou Ling, et al. The mediating role of self-efficacy between physical literacy and autonomous exercise behavior of college students[C]//China Sport Science Society. Abstract Compilation of the 12th National Sports Science Conference: Thematic Reports (Section on Physical Fitness and Health). 2022: 5858-5859. [3] Cui Bateer, Hu Xiaoyan, Cui Lei. Research on the development of an evaluation system and exercise prescriptions for college students' physical fitness[J]. Journal of Beijing Sport University, 2004(7): 927-929. [4] Huang Rong, Yu Huimin, Du Changshan. A practical study of AI-supported personalized exercise prescriptions for guiding college students' extracurricular exercise[J]. Shaanxi Education (Higher Education), 2024(5): 41-43. [5] Qiu Xiaohui, Li Chungang, Qiu Zhicai, et al. Health promotion through digital health intervention among physically underconditioned college students[J]. Journal of Jiaying University, 2026, 44(3): 91-99. [6] Cui Jianhua, Zhang Junjie, Guo Wenchao, et al. Effects of functional fitness training on movement quality and physical fitness test performance of college students[J]. Journal of Lanzhou University of Arts and Science (Natural Sciences Edition), 2025, 39(5): 91-97, 109. [7] Liu Yuting. A study of college students' physical fitness and its management[J]. Chinese Journal of School Health, 2024, 45(5): 764-765. [8] Yuan Haonan, Zhang Yan, Qi Yugang. Establishing an isotemporal substitution model of college students' physical behaviors and its cumulative utility for physical fitness[J]. Sport Science Research, 2025, 46(3): 88-95.