Convergence Curriculum for Geospatial Data Science.
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Keywords: geospatial data science, teaching, learning, geoAI
Abstract Type: Paper Abstract
Authors:
Eric Shook, University of Minnesota
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Abstract
The Convergent Curriculum for Geospatial Data Science is an integrative framework to prepare next-generation and current-generation students, scholars, and professionals to build the necessary knowledge, skills, and competencies to tackle convergent problems without requiring a series of 15-week courses. The multi-tiered curriculum starts with foundational knowledge threads to establish a common basis for individuals coming from diverse backgrounds. It then connects and frames that foundational knowledge culminating in convergent knowledge to tackle convergent problems.
The paper will detail our current status with the convergence curriculum and explain how to get access to the materials. We will also discuss how the curriculum is being integrated into classes at leading institutions as well as other activities in the NSF-support Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE).
Convergence Curriculum for Geospatial Data Science.
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Paper Abstract
