Intelligent technologies have great potential for advancing physical education (PE), thus finding an appropriate independent PE plan (IPEP) is a key step in improving undergraduates’ physical fitness (PF) level. In this study, an adaptive fitness enhancement model (AFEM) was designed based on senseless exercise behaviors monitoring (EBM) technology and an intelligent PE platform to explore the changes in PF levels of undergraduates with different fitness levels after receiving different IPEP. A total of 400 undergraduates participated in this study, and they were randomly assigned to four experimental groups and one control group. This study not only considered the historical performance of the undergraduates (fixed effect) but also delved into the individual differences of the undergraduates (random effect). The findings indicated that high-frequency aerobic exercise promoted endurance qualities more than low-frequency anaerobic exercise in an EBM environment, while low-frequency anaerobic exercise promoted strength qualities more than low-frequency anaerobic exercise. In this study, the initial decision-making mechanism of the AFEM model was developed based on the results of linear mixed model data analysis. The results showed that the AFEM model was able to maximize the effect of exercise, which in turn effectively improved the PF of undergraduates. At the same time, the AFEM model also adjusts the control variables according to the actual needs of the users, thus enriching the diversity of IPEP and further exploring the potential of the application of intelligent technology in personalized PE.

智能技术在推进体育教育（PE）方面具有巨大潜力，寻找合适的独立体育计划（IPEP）是提高大学生体质（PF）水平的关键一步。本研究基于无感运动行为监测（EBM）技术和智能体育平台设计了自适应体能增强模型（AFEM），探讨不同体能水平的本科生接受不同IPEP后PF水平的变化。共有 400 名本科生参与了这项研究，他们被随机分配到 4 个实验组和 1 个对照组。本研究不仅考虑了本科生的历史表现（固定效应），还深入研究了本科生的个体差异（随机效应）。研究结果表明，在EBM环境中，高频有氧运动比低频无氧运动更能提高耐力素质，而低频无氧运动比低频无氧运动更能提高力量素质。在本研究中，AFEM模型的初始决策机制是基于线性混合模型数据分析的结果而开发的。结果表明，AFEM模型能够最大限度地发挥运动效果，进而有效提高本科生的PF。同时，AFEM模型还根据用户的实际需求调整控制变量，从而丰富了IPEP的多样性，进一步挖掘了智能技术在个性化PE中的应用潜力。