Lessons learned from integrating EDDIE modules into a semester-long undergraduate Environmental Data Science course
Wednesday, April 29th, 2020
10am PT | 11am MT| 12pm CT | 1pm ET (Duration - 1 hour)
R. Quinn Thomas
Click to view or download the webinar recording (MP4 Video 351.6MB Apr30 20).Undergraduate environmental science students are actively seeking training in data science. However, many data science courses for undergraduates are focused on non-environmental related applications, thus not allowing students to learn about how data science can be applied in an environmental context. To address this need, I created a semester-long junior-level undergraduate course that teaches data science skills in the R programming language using the inquiry-based learning activities embedded in five EDDIE modules. Webinar participants will be introduced to the structure of the environmental data science course that I teach at Virginia Tech as part of our major in Environmental Informatics. They will learn how I harmonized diverse EDDIE modules and other resources (NEON QUBES modules and Data Carpentry Lessons) into a course plan that builds data science skills using the R language. Finally, I will share lessons learned from teaching the class for two semesters to assist other instructors seeking to add in EDDIE modules into their curriculum.