Reades, J;
(2020)
Teaching on Jupyter: Using notebooks to accelerate learning and curriculum development.
Region
, 7
(1)
pp. 21-34.
10.18335/region.v7i1.282.
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Abstract
The proliferation of large, complex data spatial data sets presents challenges to the way that regional science --- and geography more widely -- is researched and taught. Increasingly, it is not 'just' quantitative skills that are needed, but computational ones. However, the majority of undergraduate programmes have yet to offer much more than a one-off ‘GIS programming’ class since such courses are seen as challenging not only for students to take, but for staff to deliver. Using evaluation criterion of minimal complexity, maximal flexibility, interactivity, utility, and maintainability, we show how the technical features of Jupyter notebooks -- particularly when combined with the popularity of Anaconda Python and Docker -- enabled us to develop and deliver a suite of three 'geocomputation' modules to Geography undergraduates, with some progressing to data science and analytics roles.
| Type: | Article |
|---|---|
| Title: | Teaching on Jupyter: Using notebooks to accelerate learning and curriculum development |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.18335/region.v7i1.282 |
| Publisher version: | https://doi.org/10.18335/region.v7i1.282 |
| Language: | English |
| Additional information: | Copyright © 2020 Jonathan Reades. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10109080 |
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