This project aims to develop an open, scalable, and adaptable model for data science education to address the growing demand for a 21st-century data-capable workforce in Earth and Environmental Sciences. The model will be structured around an online educational framework for Earth Data Science (DS). The Earth Data Science Corps (EDSC) framework includes modular courses, an interactive open textbook, internships, and workshops for faculty and instructors from partner colleges. University of Colorado at Boulder as the coordinating organization will work closely with United Tribes Technical College, Oglala Lakota College, Front Range Community College, Metropolitan State University of Denver as implementing institutions. This project serves underrepresented students in the sciences including Hispanic, Tribal, community college, and non-traditional students. The EDSC plans to provide the community with two open tools. The first will make grading student coding assignments easier. The second will make analyzing evaluation survey data more efficient. A public, online discussion forum will provide students across implementing institutions with community support. Further, it will facilitate discussions between faculty on challenges and opportunities associated with teaching data science to diverse groups. This effort will encourage diversity and equitable opportunity in the national 21st-century data-literate workforce, contributing to bridging the data-to-knowledge gap in environmental science. If successful, it has the potential to reveal answers to some of society's most pressing environmental challenges.
The objectives of this project are two-fold. Students will gain knowledge in data science, problem-solving skills, hands-on experience, and rigorous research training. Instructors to have access to the training that will enable them to build data science capacity in the context of their own institutions. EDSC will be structured around five activities: 1) a modular Earth Data Science course supported by online computer processing power (cloud computing), a companion interactive, free online textbook, and an autograding platform; 2) data skills and career workshops for teachers and students; 3) paid hands-on undergraduate student internships; 4) faculty instructor training; and 5) program-wide evaluation. If successful, these activities will allow five diverse higher education institutions to adopt different elements depending on their current capacity. The project builds on existing efforts of the University of Colorado Earth Lab Education Initiative. Curricular materials will be designed for portability, sustainability, and easy dissemination to ensure their expanded impact. They will be evaluated for measurable outcomes and tailored to support non-traditional students, who form a large portion of the potential data science workforce in the regions surrounding the participating institutions. Course curriculum, including career development webinars, Introduction to Earth Data Science course modules, and instructor training, will be published on the EDS Learning Portal, leveraging the existing and rapidly growing user base. The EDSC plans to directly support 75 undergraduate students, train 15 faculty in data-intensive teaching, and provide data skill and career-development training to 400 or more participants across the five institutions. NSF's Harnessing the Data Revolution Data Science Corps program focuses on building capacity for harnessing the data revolution at the local, state, national, and international levels to help unleash the power of data in the service of science and society. Projects in this program are being jointly funded by the NSF's Harnessing the Data Revolution Big Idea; the Directorate for Computer and Information Science and Engineering, Division of Information and Intelligent Systems; the Directorate for Education and Human Resources, Division of Undergraduate Education; the Directorate for Mathematical and Physical Sciences, Division of Mathematical Sciences; and the Directorate for Social, Behavioral and Economic Sciences, Office of Multidisciplinary Activities and Division of Behavioral and Cognitive Sciences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
