Disruptive online learning in engineering: Enhancing education with mobile sensors and Physics toolbox

The transition to remote education has introduced significant challenges in engineering courses that require deep comprehension of dynamic systems. This study presents an innovative pedagogical approach implemented in the "Modeling in Engineering through Dynamic Systems" course (MA1035) at Tecnologico de Monterrey. By leveraging smartphone sensors and the Physics Toolbox Sensor Suite, students participated in two distinct learning modalities: a control group using traditional theoretical methods and an experimental group engaging in real-time empirical analysis. Experiments involving tuned mass dampers and vehicle suspension systems facilitated a deeper understanding of differential equations. Results indicate that the experimental group achieved higher learning outcomes, increased engagement, and enhanced cognitive processing. Additionally, students developed critical technical competencies, such as real-time data acquisition and analytical problem-solving, reinforcing their employability. The integration of gamification elements and industry-driven challenges further enriched the learning experience, fostering essential transversal skills, including collaborative problem-solving and scientific reasoning.