Aprendizagem da transformada de Fourier por meio da análise do canto de pássaros locais: um estudo de caso

The Fourier transform is essential for technology and engineering professionals due to its signal processing, image processing, telecommunications, and machine learning applications. However, its teaching is typically covered in signals and systems courses and faces challenges due to the abstract and complex nature of the content, leading to high dropout rates and student demotivation. In this context, this paper analyzes the opinions of Computer Engineering students regarding an innovative approach to teaching the Fourier transform, based on the analysis of birdsong signals from the students' local environment. The methodology involved developing scripts for signal analysis in the MATLAB® environment. The evaluation of this strategy was conducted through a Likert-scale questionnaire, and the results, statistically validated, indicated increased student motivation, as well as significant improvements in practical programming skills, teamwork, and learning outcomes. Students reported that the approach facilitated the understanding of complex concepts and contributed to the development of programming skills focused on solving applied problems, making the learning process more engaging.