ED023
Earth Data Science Education: Training Earth Scientists for Interdisciplinary Work on New and Emerging Approaches
Earth Data Science Education: Training Earth Scientists for Interdisciplinary Work on New and Emerging Approaches
Session ID#: 80339
Session Description:
Data science methods in the Earth Sciences have been complementing, enhancing and in some cases replacing traditional approaches that have been taught for decades. Educating the next generation of Earth scientists requires incorporating data science methods and their applications to problems pertaining to the subsystems of our planet. This session invites presentations on pedagogy and teaching that incorporate data science methods in Earth Science curricula. Potential topics include, but are not limited to, data wrangling, data integration and assimilation, machine learning, Semantic Web, augmented reality, visual analytics, or any other data-driven problem-solving method. Presentations that elaborate on curriculum and resource design, including ways to teach strategies for interdisciplinary collaboration, or that showcase roadblocks, opportunities and future vision are welcome. Session co-organized by IS-GEO.
Co-Organized:
- IN - Earth and Space Science Informatics
- IN - Earth and Space Science Informatics
- T - Tectonophysics
- T - Tectonophysics
Index Terms:
0825 Teaching methods [EDUCATION]
0850 Geoscience education research [EDUCATION]
1920 Emerging informatics technologies [INFORMATICS]
1942 Machine learning [INFORMATICS]
Primary Convener: Orhun Aydin, ESRI, Redlands, CA, United States
Conveners: Deana D Pennington, University of Texas at El Paso, El Paso, TX, United States, Sudhir R Shrestha, Esri, Vienna, VA, United States and Yolanda Gil, University of Southern California, Information Sciences Institute, Los Angeles, CA, United States
Primary Liaison: Imme Ebert-Uphoff, Colorado State University, Fort Collins, CO, United States
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