Lorena Barba
Lorena A. Barba is professor of mechanical and aerospace engineering at the George Washington University in Washington, DC. Her research interests include computational fluid dynamics, high-performance computing, and computational biophysics. An international leader in computational science and engineering, she is also a long-standing advocate of open source software for science and education, and is well known for her courses and open educational resources. Barba served (2014–2021) in the Board of Directors for NumFOCUS, a US public charity that supports and promotes world-class open-source scientific software. She is an expert in research reproducibility, and was a member of the National Academies study committee on Reproducibility and Replicability in Science. She served as Reproducibility Chair for the SC19 (Supercomputing) Conference, is Editor-in-Chief of IEEE Computing in Science & Engineering, was founding editor and Associate EiC (2016–2021) for the Journal of Open Source Software, and is EiC of The Journal of Open Source Education. She was General Chair of the global JupyterCon 2020 and was named Jupyter Distinguished Contributor in 2020.
Sessions
This talk presents a candid reflection on integrating generative AI into an Engineering Computations course, revealing unexpected challenges despite best intentions. Students quickly developed patterns of using AI as a shortcut rather than a learning companion, leading to decreased attendance and an "illusion of competence." I'll discuss the disconnect between instructor expectations and student behavior, analyze how traditional assessment structures reinforced counterproductive AI usage, and share strategies for guiding students toward using AI as a co-pilot rather than a substitute for critical thinking while maintaining academic integrity.