Earth Data Science Education for Groups Historically Underrepresented in STEM
The Earth Lab Education Team is committed to leading, promoting and facilitating earth data science education for groups historically underrepresented in STEM. Promoting diversity, equity, inclusion, and accessibility (DEIA) is not only fair, it improves the quality of science. We do this through a combination of workshops, training, capacity building with faculty and developing open curriculum and tools that anyone can use in their courses. We also collect data and conduct research to assess the effectiveness of our approaches. We currently have two projects that explicitly focus on equitable access to earth data science skills:
- The Earth Data Science Corps, which is funded through the NSF Harnessing the Data Revolution Data Science Corps Initiative to build capacity to teach and learn earth data science and
- pyOpenSci, a project funded by the SLOAN foundation which targets diversity issues in open source Python scientific software
Building Earth Data Science Teaching Capacity at Tribal Institutions, Community Colleges, and Hispanic Serving Institutions
While the demand for earth data science skills in the workforce is exploding, the availability of programs that teach these in demand skills is not equally distributed. Smaller schools that support communities that have been historically underrepresented in STEM often lack the capacity to teach technical earth data science skills. This is often due to limited resources to create and support new curriculum and limited faculty expertise to teach these skills. This lack of capacity in turn yields a lack of diversity in the technology sector and data science specifically. Recent studies report that less than 12% of students in data science courses identify as Black or Hispanic.
The Earth Data Science Corps, funded by the National Science Foundation Harnessing the Data Revolution program, is a $1.2 million three-year project that builds capacity to teach and learn earth data science at schools serving communities that are historically underrepresented in STEM. The project includes a combination of online data skills training for students and faculty, career focused webinars and project based learning. Faculty training builds capacity to teach earth data science at each school. Learn more about our earth data science teaching efforts here.
Empowering Women and BIPOC to Contribute to Open Source Software
pyOpenSci will build an inclusive and diverse community around the development and maintenance and peer review of scientific Python packages, through mentorship and training in open source scientific software (OSS) contributions for underrepresented groups. The lack of diversity seen in STEM is amplified in the OSS community. The lack of diversity seen in STEM is amplified in the open source scientific software (OSS) community. Women, non binary and BIPOC communities are even less represented in the OSS community than they are in STEM. For example, in 2017 women comprised only 5% of OSS project contributions on GitHub with up to 20% of all programmers being women, despite the fact that diversity enhances scientific efforts. PyOpenSci was developed and is led by education lead Leah Wasser.
Nathan A. Quarderer
Nate is an educational researcher currently focused on the topics of data science education, and on how people come to know about climate change and why they hold a particular set of beliefs. At Earth Lab, Nate helped organize and implement the Earth Data Science Corps program, leading assessment and evaluation efforts.