- Undergraduate
Bachelor's Degrees
Bachelor of ArtsBachelor of EngineeringDual-Degree ProgramUndergraduate AdmissionsUndergraduate Experience
- Graduate
Graduate Experience
- Research
- Entrepreneurship
- Community
- About
-
Search
All Thayer News
Dartmouth and NSF Work to Expand the Data Scientist Pipeline
Mar 03, 2021 | by Julie Bonette
Demand for data scientists — analysts who combine theoretical knowledge with tools to gather meaningful data in order to implement solutions computationally, interpret results, and communicate them broadly — is rising around the globe. Domestically, a 2019 LinkedIn study found that "data scientist" is the most promising job in the country, and in 2021, Glassdoor ranked the job second on their list of best positions.
Dartmouth has stepped up to help satisfy this demand, thanks in large part to a National Science Foundation (NSF) four-year grant totaling nearly $2.8 million. Since receiving the funding in Fall of 2019, the project, called "Data Science Infused into the Undergraduate STEM Curriculum" (DIFUSE), has involved both faculty and students working individually with professors across Dartmouth to develop data science modules that can be integrated into current course curricula.
"We work with instructors of introductory STEM classes who are interested in having a module developed for their class that introduces students to basic data science techniques and practices," explained Petra Bonfert-Taylor, Principal Investigator (PI) and a professor of engineering. "Each module we have developed so far is completely unique — no two are even close to similar."
In addition to Bonfert-Taylor, the DIFUSE team is led by co-PIs Laura Ray, professor of engineering; Lorie Loeb, Faculty Director at the DALI Lab; and Scott Pauls, professor of mathematics. The team, which also meets regularly with a learning design specialist, has so far developed modules for five courses in the earth science, geography, mathematics, biology, and psychological and brain sciences departments. Two more modules, for astronomy and engineering courses, are currently in the works.
For each course, members of DIFUSE form a special 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. The bulk of the work is done by DIFUSE without burdening the instructor, but constant communication with the instructor ensures that the module fits well into the course and has the desired learning outcomes.
"I really enjoyed working with the DIFUSE team to get more data science into my course," said Robert Hawley, chair and associate professor of earth sciences, who worked with DIFUSE to develop a module for EARS 6: Environmental Change. "As a result, nearly every student group connected the ideas that I'd hoped for in the project, where previously many groups still missed important components of the concept."
Caitlin Hicks Pries, assistant professor of biological sciences, similarly felt her BIO 16: Ecology students benefitted from the newly incorporated DIFUSE data science module. "This data-exploration type lab is one that I have been wanting to design, but I did not have the time or technical know-how to do it on my own. It was so much fun to work with two students who were so dedicated to the success of this project. From them, I learned about translating my code to an interactive webpage, and hopefully, they learned a bit about carbon balance and eddy covariance from me."
The approximately dozen students on the DIFUSE team have also been gaining skills and knowledge from the experience.
James Busch, a Dartmouth PhD student studying earth science, has been working on a series of activities that would allow students in ASTR 15: Stars and the Milky Way, to use specially-built Python libraries as tools to learn about celestial objects in our galaxy. "I have really been enjoying learning about the basics of astronomy and how we view objects in our very own galaxy while designing the exercises!" he said.
And, while working on a module that would allow students in ENGS 93: Statistical Methods in Engineering, to use the programming software R for statistical analysis, Sarah Korb '22 learned, "about the challenges that come with building an effective and engaging course. As a student who is normally on the receiving end, it is interesting and impressive to see how much thought and consideration goes into building a Dartmouth course," she said.
Next summer, the DIFUSE team will share their results with faculty from other institutions at a workshop designed to spread the techniques developed for module creation, as well as the modules themselves.
For contacts and other media information visit our Media Resources page.