Enrichment Of Student Learning And Homework Management With Use Of GitHub In An Introductory Cross-Disciplinary Engineering Course Series On Software Engineering And Data Science


GitHub is increasingly finding a role in academia to both encourage reproducible computational research and to foster a collaborative environment. We show that employing GitHub as an implementation of version control in engineering-related fields reinforces the 'design-build-evaluate' way of thinking and prepares students with skills they can use well beyond the classroom. Additionally, course features such as homework submission and feedback via GitHub enhanced student learning. Finally, we demonstrate that GitHub can be used to actively measure homework progress and teamwork.

Author Biographies

Chad Daniel Curtis, University of Washington

Chad D. Curtis is a lecturer in the Department of Chemical Engineering at the University of Washington. He teaches primarily computational-based courses and design courses. His teaching interests include the incorporation of computational tools in engineering education and an emphasis on statistics and scientific writing. His graduate research focused on the use of data science tools to improve the analysis of nanoparticle trajectory datasets for nanotherapeutic applications.

David Beck, University of Washington

David A. C. Beck is a Research Associate Professor in the Department of Chemical Engineering at the University of Washington and Director of Research in the eScience Institute which is the University of Washington’s data science institute. He is also Associate Director of the NSF funded NRT-DESE: Data Intensive Research Enabling Clean Technologies (DIRECT, award # 1633216). His work is at the intersections of molecular data science and energy, environment and health.

Caitlyn Wolf, University of Washington

Caitlyn M. Wolf is a PhD Candidate in the Department of Chemical Engineering at the University of Washington. As a member of the campus data science community, she has completed the Advanced Graduate Data Science Option and is currently working on her second quarter as a teaching assistant for the DIRECT data science courses. Her graduate research utilizes neutron and x-ray scattering, molecular simulations, and data science tools to explore the molecular conformation and dynamics and to improve molecular modeling methods of semiconducting polymers.