Geographical Python Teaching Resources: geopyter

Jonathan Reades and Sergio J. Rey ()
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Jonathan Reades: University College London
Sergio J. Rey: University of California

Journal of Geographical Systems, 2021, vol. 23, issue 4, No 7, 579-597

Abstract: Abstract geopyter, an acronym of Geographical Python Teaching Resources, provides a hub for the distribution of ‘best practice’ in computational and spatial analytic instruction, enabling instructors to quickly and flexibly remix contributed content to suit their needs and delivery framework and encouraging contributors from around the world to ‘give back’ whether in terms of how to teach individual concepts or deliver whole courses. As such, geopyter is positioned at the confluence of two powerful streams of thought in software and education: the free and open-source software movement in which contributors help to build better software, usually on an unpaid basis, in return for having access to better tools and the recognition of their peers); and the rise of Massive Open Online Courses, which seek to radically expand access to education by moving course content online and providing access to students anywhere in the world at little or no cost. This paper sets out in greater detail the origins and inspiration for geopyter, the design of the system and, through examples, the types of innovative workflows that it enables for teachers. We believe that tools like geopyter, which build on open teaching practices and promote the development of a shared understanding of what it is to be a computational geographer represent an opportunity to expand the impact of this second wave of innovation in instruction while reducing the demands placed on those actively teaching in this area.

Keywords: Open Source; Spatial Analysis; Education (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10109-021-00346-6

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