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Practitioners and researchers in geoscience education embrace collaboration applying ICON (Integrated, Coordinated, Open science, and Networked) principles and approaches ICON principles and approaches have been used to create and share large collections of educational resources, to move forward collective priorities, and to foster peer-learning among educators. These strategies can also support the advancement of coproduction between geoscientists and diverse communities. For this reason, many authors from the geoscience education community have co-created three commentaries on the use and future of ICON in geoscience education. We envision that sharing our expertise with ICON practice will be useful to other geoscience communities seeking to strengthen collaboration. Geoscience education brings substantial expertise in social science research and its application to building individual and collective capacity to address earth sustainability and equity issues at local to global scales The geoscience education community has expanded its own ICON capacity through access to and use of shared resources and research findings, enhancing data sharing and publication, and leadership development. We prioritize continued use of ICON principles to develop effective and inclusive communities that increase equity in geoscience education and beyond, support leadership and full participation of systemically non-dominant groups and enable global discussions and collaborations.

Data-intensive skills are becoming increasingly critical in earth and environmental science. As data sets become larger, more numerous, and harder to analyze, there is a need for scientists who can develop earth and environmental data science (EDS) workflows that are open, reproducible, and use modern programming languages. To leverage the full potential of EDS, attention should also be focused on broadening participation by members of groups who have been historically underrepresented in data science and STEM. The Earth Data Science Corps (EDSC) program, hosted at Earth Lab (CIRES/CU Boulder) with partners from tribal colleges and minority-serving institutions throughout the Front Range and Northern Great Plains, offers one approach to introducing EDS to underserved communities. EDSC engages participants with fundamental Python programming tools and packages (pandas, numpy, matplotlib), along with resources to work with time- series, and vector and raster spatial data (earthpy, geopandas, rioxarray) in the context of EDS. Beginning in 2020, EDSC has built capacity for our partners to teach EDS at their home institutions and helped students develop confidence and comfort in a variety of different science and data science areas. Through a paid internship experience that includes a series of technical workshops and group projects, EDSC participants are assessed in the following five areas: (i) science identity, (ii) science practices, and (iii) Python, (iv) data science, and (v) science communication skills. Using a retrospective pre-then-post design, Likert-type survey items were analyzed using Rasch modeling to measure growth in EDSC participants’ self-reported comfort and confidence in the five areas outlined above. Analysis of variance (ANOVA) of person ability measures from Rasch modeling of survey responses collected during Year 1 of EDSC revealed significant differences from pre- to post- program, and between the five assessment areas. Post-hoc analysis pointed to significant growth in each of the five assessment areas with the exception of Science Identity. Collection and analysis of Year 2 EDSC survey responses is ongoing and results are forthcoming. Implications for teaching earth and environmental data science to members of historically underrepresented communities will be discussed.

Poster from Earth Lab and ESIIL Education teams for AGU 2022 (Chicago, IL).

There is a mismatch between demand for a data-cable workforce with skills at the intersection of earth and data science (earth data science) and the capacity to teach those skills, particularly at schools serving historically underrepresented communities. The Earth Data Science Corps (EDSC) is a fully-online model that builds capacity for faculty and undergraduate students at institutions serving underrepresented communities to teach and learn earth data science. The EDSC builds sustainable teaching capacity while training students in critical data and career development skills in a virtual space. Access to these skills is further democratized by publishing curricular materials online as open education resources for anyone to use.Here we will present best practices for teaching and learning EDS skills online, derived from a program-wide evaluation that considers underrepresented groups, supports mentorship and community building, and scales to broaden reach. We will discuss tools comprising our learning environment including a cloud-based JupyterHub and autograding platform. We will also review best practices for online content delivery including 1. pairing synchronous video training with open education resources to facilitate active, student-directed learning; 2. using discussion forums and chat to encourage engagement, and 3. managing student mentoring challenges in a virtual space to support project-based learning.Initial findings indicate that online learning can effectively build confidence in using EDS skills but requires careful consideration of teaching delivery. Further, the use of small breakout rooms paired with chat supports class level engagement. Finally, open education resources can support a flipped classroom approach. Mentoring students in a virtual space further requires additional training of mentors to ensure communication lines with students remain open. Collecting real-time student feedback and modifying our delivery will also be discussed.