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.
Exploring Eddy Covariance Method
The purpose of this lab is to introduce students to the basics of Eddy Covariance, explore raw measurement data to observe visible patterns across seasons and time of day, as well as being able to discover meaningful relationships between variables important to the ecosystem.
Environmental Change
Through this project, the students will have the opportunity to measure environmental change. Students will also be exposed to temperature and insolation related public datasets. The project is appropriate for courses in introductory environmental sciences, earth sciences, and any other courses related to the climate.
Climate Extremes in a Warming Planet
The problem sets were designed to introduce students to important concepts/applications in Python and to connect the lecture content. In order to keep the problem sets simple and not overwhelm the students, the problem sets were broken up into five separate, shorter assignments. The contents of the problem sets are outlined below to indicate after which lectures the problem sets should be introduced.
Data Science in Psychology
The course module is designed to show students what Data Science in Psychology is like, at a high level. We want them to see how real-world data can be collected, and how that gets translated into something we can hypothesize and experiment with.
Differential Equations
Ensure that students appreciate the need for understanding domain context (Math 23 concepts) in deriving ODE solutions.