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

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 un-dergraduate 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 con-cepts to STEM and non-STEM students and to bolster the confidence of underrepresented minorities and females in STEM.

计算能力在指导学生借助卫星遥感（satellite remote sensing）技术开展环境变化调查研究的教学中具备显著优势。鉴于少数群体与女性在科学、技术、工程、数学（Science, Technology, Engineering, Mathematics, STEM）领域的代表性严重不足，这一教学重点的现实意义尤为凸显。本研究针对开设于谷歌地球引擎（Google Earth Engine）平台的地球科学遥感教学模块，量化分析其在STEM与非STEM两类课堂中对学生编程自我效能感、遥感认知水平以及对科学研究与环境领域职业的兴趣所产生的影响；此外，参与课程的STEM学生还完成了一项针对水质问题的课程式本科研究体验（course-based undergraduate research experience, CURE），借助卫星影像可视化呈现了全球沿海地区因COVID-19疫情停摆而发生的水质变化。前后测问卷结果显示，多数学生在运用编程技能开展环境变化研究以及理解遥感技术相关知识的自信心方面出现了具有统计学意义的显著提升，但本次教学干预并未显著提升学生对科学研究或环境领域职业的兴趣。综上，将遥感实验课程融入教学，可为STEM与非STEM学生传授环境科学概念，同时还能增强少数弱势群体与女性群体在STEM领域的自信心，具备显著的应用价值。