| Abstract Scope |
In today’s academic and professional environment, students are increasingly drawn to fields like computer science, data science, artificial intelligence, and machine learning. By incorporating coding as a core competency in our courses, we can position Materials Science and Engineering as a forward‑thinking major that provides students with both the theoretical foundation and the practical skills that are highly sought after in the workforce. Here, we highlight our efforts in transforming the required undergraduate course “Kinetics, Phase Transformations, and Transport” to emphasize learning through code. Central to this redesign is the use of generative AI tools, which students employ to translate theoretical derivations into functioning code and then apply their code to solve complex, open-ended materials problems; often, these are tasks that lie at the highest levels of Bloom’s taxonomy. Such an approach has the potential to foster creativity while providing a stronger conceptual understanding of core topics. |