Use of Google Earth Engine for Teaching Coding and Monitoring of Environmental Change: A Case Study among STEM and Non-STEM Students

Abstract

Computational skills are advantageous for teaching students to investigate environmental change using satellite remote sensing. This focus is especially relevant given the disproportionate underrepresentation of minorities and women in STEM fields. This study quantified the effects in both a STEM and a non-STEM class of Earth science remote sensing modules in Google Earth Engine on students’ self-efficacy in coding, understanding remote sensing, and interest in science and a career in environmental research. Additionally, the STEM students engaged in a course-based undergraduate research experience (CURE) on water quality. Satellite imagery was used to visualize water quality changes in coastal areas around the world due to the COVID-19 pandemic shutdown. Pre- and post-surveys reveal statistically significant changes in most students’ confidence to apply coding skills to investigate environmental change and understand remote sensing. The intervention was not sufficient to lead to significant changes in interest in science or a career in environmental research. There is great benefit in incorporating remote sensing labs to teach environmental concepts to STEM and non-STEM students and to bolster the confidence of underrepresented minorities and females in STEM.