Data driven pedagogy in physical education a new paradigm in teaching effectiveness

The standard practice of physical education (PE) teaching relies primarily on traditional pedagogical methods that lack systematic data-based techniques for measuring teaching performance. A flexible systematic approach becomes vital because students’ learning styles, performance dynamics, and teaching targets create fluid teaching conditions. A unified teaching-decision-making structure emerges to boost physical education effectiveness through the presented approach. This research introduces a novel T-spherical fuzzy Aczel-Alsina (TSFA) aggregation approach for evaluating instructional methods, student engagement, and performance outcomes, utilizing T-spherical fuzzy sets (TSFS) with Aczel-Alsina aggregation. The system provides live responsiveness to instructional methods by connecting adjustments with immediate feedback and numerical performance information. The model demonstrates its ability to find the best teaching approaches for different learners through experimental testing conducted in college PE settings through scenario-based assessments. The framework benefits teachers, administrators, and curriculum planners who want to enhance physical education programs by making decisions based on research evidence.