Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry
The authors of this article introduce two teaching modules that aim to increase climate literacy and active learning in undergraduate economics courses through the incorporation of real-world data and modeling. These modules are based on the concept of computational guided inquiry (CGI), which combi...
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ftrepec:oai:RePEc:taf:jeduce:v:51:y:2020:i:2:p:143-158 2023-05-15T15:01:32+02:00 Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry Lea Fortmann Justin Beaudoin Isha Rajbhandari Aedin Wright Steven Neshyba Penny Rowe http://hdl.handle.net/10.1080/00220485.2020.1731383 unknown http://hdl.handle.net/10.1080/00220485.2020.1731383 article ftrepec 2020-12-04T13:40:40Z The authors of this article introduce two teaching modules that aim to increase climate literacy and active learning in undergraduate economics courses through the incorporation of real-world data and modeling. These modules are based on the concept of computational guided inquiry (CGI), which combines a guided inquiry approach within a computational framework, such as Excel. In one module, students estimate and graph expected marginal damages due to regional sea level rise for various polar ice melt scenarios. In the second module, students partially replicate a journal article estimating the total economic value of ecosystem services in the Arctic. These modules have been used in urban, environmental, and climate change economics courses, and are ready to be implemented with minimal upfront cost to instructors. Article in Journal/Newspaper Arctic Climate change RePEc (Research Papers in Economics) Arctic |
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Open Polar |
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RePEc (Research Papers in Economics) |
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ftrepec |
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unknown |
description |
The authors of this article introduce two teaching modules that aim to increase climate literacy and active learning in undergraduate economics courses through the incorporation of real-world data and modeling. These modules are based on the concept of computational guided inquiry (CGI), which combines a guided inquiry approach within a computational framework, such as Excel. In one module, students estimate and graph expected marginal damages due to regional sea level rise for various polar ice melt scenarios. In the second module, students partially replicate a journal article estimating the total economic value of ecosystem services in the Arctic. These modules have been used in urban, environmental, and climate change economics courses, and are ready to be implemented with minimal upfront cost to instructors. |
format |
Article in Journal/Newspaper |
author |
Lea Fortmann Justin Beaudoin Isha Rajbhandari Aedin Wright Steven Neshyba Penny Rowe |
spellingShingle |
Lea Fortmann Justin Beaudoin Isha Rajbhandari Aedin Wright Steven Neshyba Penny Rowe Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
author_facet |
Lea Fortmann Justin Beaudoin Isha Rajbhandari Aedin Wright Steven Neshyba Penny Rowe |
author_sort |
Lea Fortmann |
title |
Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
title_short |
Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
title_full |
Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
title_fullStr |
Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
title_full_unstemmed |
Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
title_sort |
teaching modules for estimating climate change impacts in economics courses using computational guided inquiry |
url |
http://hdl.handle.net/10.1080/00220485.2020.1731383 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_relation |
http://hdl.handle.net/10.1080/00220485.2020.1731383 |
_version_ |
1766333560920211456 |