Solving Bernoulli’s Equations Using Python: Enhancing Student Understanding Through Inquiry-Based Learning

Abstract

This study explores using Python to solve Bernoulli’s equations with the goal of enhancing student understanding. Inquiry-Based Learning (IBL) is integrated into it. The research included second-year students majoring in mathematics from Srinakharinwirot University. The teaching approach began with an introduction to Bernoulli’s equations in theory. These equations were then converted into linear form and solved using Python programming. Among the practical tasks in which students took part were post-test assessments, group problem-solving, and pre-test evaluations. Group members used Bernoulli’s equations to real-world scientific problems including fluid mechanics and population dynamics using Python to generate solutions and present discoveries. Inquiry-based learning (IBL) principles were used in the study, where students posed questions, looked into problems, and assessed the solutions using Python. The results demonstrated a greater understanding of mathematical concepts as well as computational techniques. The decrease in standard deviation between the pre- and post-test data showed how well IBL and Python combine to foster critical thinking and practical problem-solving skills. This method has the potential to assist student teachers acquire computational abilities and a deeper understanding of mathematics, which will better prepare them for careers as teachers.