This study aims to design, implement, and validate a wireless sensor network (WSN)-based system for the objective biomechanical assessment and real-time feedback of yoga postures in a university setting, addressing the limitations of subjective visual correction in traditional instruction. A system integrating multiple Inertial Measurement Unit (IMU) nodes was developed, utilizing a sensor fusion algorithm to calculate accurate 3D joint angles. A controlled 8-week experiment with 40 novice students compared an experimental group (Training with sensor feedback) against a control group (traditional training). Performance in five fundamental asanas was evaluated using alignment, stability, and temporal metrics. The system achieved high measurement accuracy (RMSE < 2°). The experimental group demonstrated a significantly faster (43%) and greater improvement in postural alignment (p < 0.01) and successfully corrected critical errors like knee valgus in 90% of participants. A 30% greater enhancement in postural stability was also observed. The wireless sensing system is a technically viable and pedagogically effective tool for enhancing yoga training through quantitative assessment and personalized feedback. Integrating this technology into physical education curricula can augment instructor capabilities, enable data-driven class management, and provide students with an intuitive biofeedback tool for safer and more efficient skill acquisition.