By building a set of modules to teach data science in STEM courses at Dartmouth, we build a flexible and reusable set of tools and methods for faculty to enrich learning objectives through the hands-on exploration of data collection, analysis, and visualization.
DIFUSE Modules
Our team works with faculty in the sciences and social sciences to build data science learning modules for existing courses. These modules could be for a short assignment or a longer-running exercise with skill-building components. Module teams consist of 2-3 students (graduate and undergrad), one of the DIFUSE grant PI’s. We do the heavy lifting, with input from the faculty member during weekly meetings.
Using Statistics and Supervised Machine Learning to Inform Airline Decision Making
This module reinforces underlying statistical concepts in the process of building a data analysis pipeline. Students practice statistical concepts to gain an understanding of the airline data in Part 1, then the data is used to implement machine learning models in Part 2. The final deliverable is a slide deck, in which students act as consults for the Phoenix Sky Harbor Airport using insights gained from supervised machine learning analysis of the relationship between airline carrier delays and passengers per flight.