Employing computation to overcome epistemic obstacles in physics education

Abstract

While the mathematization of physics has been essential to its development, the dominant focus on continuous mathematics can act as an epistemological obstacle in certain educational contexts. This limitation arises when the conceptual frameworks used in teaching physics restrict students’ access to problems that require advanced mathematical tools, particularly differential calculus. In this work, we explore how integrating computation and discrete mathematics can help overcome such barriers, enabling alternative approaches to phenomena that are otherwise analytically inaccessible. As case studies, we examine projectile motion with air resistance, a classical problem whose analytical resolution is too complex for high school students, and the motion of planets around the Sun, whose dynamics are governed by central gravitational forces and are naturally suited to numerical simulation. By implementing the Euler method in a Python program, we are able to accurately simulate the motion using basic programming skills and simple algorithms. This computational approach not only yields reliable results, but also enhances conceptual understanding through dynamic modeling, simulations, and graphical representations. We argue that computation should be regarded not as supplementary content but as a central component of physics education, serving as a bridge between current scientific practices and classroom instruction. This shift also requires updating mathematics curricula to include discrete structures and logic, which would support students’ understanding of computational approaches in physics and other sciences.