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June 24, 2024

Students in �������� pilot course use sustainability research questions and data sets as context for learning data science principles.

A pilot course at �������� is helping students master the principles of data science by positioning it in a framework that innately interests them—sustainability.

“’Data Science with an Eye Towards Sustainability’” builds off other data science and statistics classes that I’ve taught here at �������� and elsewhere,” says David Shuman, professor of data science and applied mathematics. “The goal is to keep the same technical learnings—carrying out a full, iterative data science pipeline from research question formulation to visualization and presentation— but all of the data sets and projects have some connection to sustainability.”

To begin the class, students read through , which outlines dozens of future-focused learning outcomes for engineering undergraduates; they selected several to work on for the first half of semester as individuals. Students also read up on , , and the (SDGs).

“The early weeks of the class were spent scaffolding in very specific learning goals, from visualizing a single variable to statistical modeling of different trends and how to make inferences from a small population to a big population,” says Phillip Post ’25, an electrical and computer engineering major, who served as a course assistant in Shuman’s class due to his existing knowledge in data science.

Students worked with third-party data on a range of sustainability projects, such as all the electric vehicle charging stations in the United States and how they have evolved over time; which waterways wastewater plants around the world flow into and what kinds of vegetation grow there; and who is using Washington, D.C.’s shared bike systems, as well as where and when.

Another critical part of “Data Science with an Eye Towards Sustainability” is the opportunity to integrate campus operations into the curriculum at ��������. Along with outside data, students were able to use real-world data from ��������, such as electrical and natural gas usage and patterns over the last 10 years, to hone their visualization and data exploration skills.

“Allowing students to think about and ask specific questions about what’s happening at �������� from a sustainability perspective—such as what the campus does over summer break to save energy—reaches them personally and shows them how data science is used in the real world,” says Shuman.

For their final project, students crowdsourced potential sustainability research questions and then narrowed them down through a diplomatic process. They organized into teams based on interest and worked together to examine available data, present a clear visualization of their findings, and write a blog post for the public about their work. 

“A big focus for the class was wanting to remove the mental blocks around statistics by making it fun and interesting, but also highlighting to students their role as storytellers,” says Post. “How do you tell something in a compelling way that makes someone want to care?”

Final project topic areas included plastic waste in the ocean, comparing the sustainability of dairy milk and milk alternatives, and the spread and effect of gentrification in Brooklyn. 

“To see students’ progress from not knowing much about data science to creating these beautiful, informative final projects was really stunning,” says Post. “It was really gratifying to see how good people got at taking nebulous data and making people care about what it means. That’s how we can turn data into action.”