Dartmouth Data Science Education Featured on ASEE TV

DIFUSE aims to address the growing need for data science skills—the ability to combine theoretical knowledge with meaningful data in order to implement solutions computationally, interpret the results, and communicate them clearly and broadly. The project has involved both faculty and students working in teams with professors across Dartmouth to develop data science modules that can be integrated into course curricula.

"We noticed this gap between students needing knowledge in data science, but students not majoring in data science," says Bonfert-Taylor. "We're integrating data science into already existing courses ... trying to whet [students'] appetite early on in their studies so that then they might pivot and choose a few extra classes."

The DIFUSE team—led by Bonfert-Taylor and co-PIs Laura Ray, professor of engineering; Lorie Loeb, professor of computer science and faculty director of the DALI Lab; and Scott Pauls, professor of mathematics—has helped develop modules for a range of courses in earth science, geography, mathematics, biology, psychological and brain sciences, astronomy, and engineering.

For each course, members of DIFUSE form a team consisting of a graduate student, an undergraduate student, a PI, and the class instructor in order to first develop the learning objectives of the module and then the module itself.

In an environmental engineering class, "we were given many different tool sets and different types of plots and ways to look at [air quality] data," says engineering sciences major Christian Hudanich '25. "That really helped to establish in my mind that you use this large data set and these tools to arrive at a new conclusion and to develop your own answer to it."

"This project really enhances how students enter the job market," continues Bonfert-Taylor. "The world is full of data, more and more each day, and students need to be able to make sense and meaning of all that data regardless of their chosen field of study."