Wearable technology and goal setting for sustainable learning outcomes in physical education through integrated PLS SEM and gradient boosting machine analysis

Improving educational quality and fostering lifelong learning competencies are central priorities of Sustainable Development Goal (SDG) 4, yet empirical evidence on how technology-supported learning influences motivation, self-regulation, and achievement in physical education remains limited. This study examines the associations between wearable technology use, goal-setting strategies, motivation, self-regulation, and achievement in physical education. A cross-sectional design was employed, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Gradient Boosting Machine (GBM) to assess explanatory relationships and predictive importance. The results indicate that wearable technology use and goal-setting strategies are positively associated with students’ motivation and self-regulation. Motivation and self-regulation are also positively associated with achievement in physical education, suggesting that these psychological factors function as mechanisms linking instructional supports to learning outcomes. The GBM analysis further identifies motivation and self-regulation as the most influential predictors of achievement, followed by wearable technology use and goal-setting strategies. These findings suggest that wearable technology may serve as a supportive instructional resource rather than a direct determinant of achievement. The study contributes to SDG 4–oriented research by providing cross-sectional evidence that technology-supported learning and goal-setting strategies are associated with motivational and self-regulatory processes that support educational outcomes in physical education.