Speaker
Description
Scientific computing constitutes the third pillar of modern physics, yet effectively integrating it into the undergraduate curriculum remains a pedagogical challenge, especially in Brazil. Historically, Brazilian students view programming as a challenge to overcome rather than a skill to develop. Moreover, the recent emergence of AI programmers allows students to lean on these tools, purposely avoiding competence development. This report details the implementation of a Project-Based Flipped Learning (PBFL) methodology in a scientific computing course at the University of Campinas. By shifting theoretical instruction to asynchronous study, classroom time was dedicated to collaborative, open-ended projects covering hardware architecture, code optimization, and simulation. An examination of student feedback (N=24) reveals a substantial enhancement in self-reported conceptual comprehension and programming confidence. While the flipped component ensured the acquisition of technical foundations, the project-based element fostered high student engagement through autonomy. Although time management emerged as a logistical constraint, we conclude that the PBFL model effectively bridges the gap between abstract programming syntax and practical physical application while allocating AI to its proper use without compromising the students' development.
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