This short course is being organized in conjunction with a Geoscience and Society session, and is intended to provide an opportunity to try out educational tools and modules in an interactive small-group setting. If you would like to share an educational tool, platform, or curriculum module, please either submit to the GS poster session with the same name or contact the conveners. This course will also be an opportunity for students and early career researchers looking for learning opportunities, and for educators to try out and discuss new computational approaches to earth and environmental science educators.
The landscape of earth science education is shifting quickly due to emerging technologies and shifting priorities, which present both challenges and opportunities in pedagogy. Satellites, genetic sequencing, long-term in situ sensors, model results and reanalyses, digitized collections and citizen science are producing massive datasets, requiring students in earth and environmental sciences to learn scientific computing skills to utilise them. However, many students in earth and environmental science degree programs report lacking the computational skills needed to work with earth observation data.
At the same time, ubiquitous access to computing can help universities meet goals around educating more scientists by accelerating learning and lowering the barrier to entry with technologies such as virtual labs and cloud-based learning environments. Emerging technologies, including artificial intelligence, further expand these possibilities but also raise questions about ethical use and how best to support meaningful student engagement and scientific understanding.
This short course invites researchers, educators, industry practitioners, and representatives from other organisations working in Earth and environmental science education to share innovative and effective approaches to developing geospatial and computational skills in Earth and environmental science education. We welcome contributions describing successful courses, programmes, learning environments, and other educational tools, as well as experiences evaluating their impact and accessibility. We are particularly interested in highlighting initiatives with a proven track record of targeting and including intersectional identities traditionally under-represented among earth, environmental and/or computer scientists.