The Application of Smart Wristbands Driven by Data in a Personalized Physical Training Program within Vocational Education Curriculum

Abstract

Against the background of vocational education curriculum reform and the popularization of intelligent wearable devices, traditional unified physical training modes fail to match vocational students’ differentiated physical conditions and career fitness demands. This study constructs a data-driven personalized physical training program with smart wristbands as the core carrier, and adopts a mixed research method combining experimental and control groups to explore its effects on three core indicators: students’ physical health knowledge (Y1), training performance (Y2), and learning satisfaction (Y3). The research subjects were 200 architecture majors from Quanzhou Light Industry College, divided into an experimental group receiving 16 weeks of smart wristband-assisted personalized training and a control group adopting conventional unified physical training. Research instruments included physical health knowledge questionnaires, national student physical fitness test indicators, student satisfaction scales, and teacher-student semi-structured interview outlines. SPSS was used for quantitative analysis such as paired t-test and ANCOVA, while NVivo was adopted for thematic coding of interview qualitative data. The research results predict that the experimental group will achieve significantly higher scores in health knowledge, physical fitness indicators and training satisfaction than the control group. The implementation effect of the program is mainly restricted by four key factors: data accuracy of smart wristbands, teachers’ data analysis and curriculum design ability, students’ training participation, and school hardware and curriculum support. This study enriches the theoretical system of personalized physical education under vocational education, and provides operable curriculum reform schemes for vocational colleges and physical education teachers. The research has limitations such as single-school sample and short intervention cycle, and multi-school longitudinal tracking research can be carried out in the future.