Wolff, Annika; Kortuem, Gerd and Cavero, Jose
(2015).
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| DOI (Digital Object Identifier) Link: | https://doi.org/10.1109/ICALT.2015.44 |
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| Google Scholar: | Look up in Google Scholar |
Abstract
A bottom-up approach to smart cities places citizens in an active role of contributing, analysing and interpreting data in pursuit of tackling local urban challenges and building a more sustainable future city. This vision can only be realised if citizens have sufficient data literacy skills and experience of large, complex, messy, ever expanding data sets. Schools typically focus on teaching data handling skills using small, personally collected data sets obtained through scientific experimentation, leading to a gap between what is being taught and what will be needed as big data and analytics become more prevalent. This paper proposes an approach to teaching data literacy in the context of urban innovation tasks, using an idea of Urban Data Games. These are supported by a set of training data and resources that will be used in school trials for exploring the problems people have when dealing with large data and trialling novel approaches for teaching data literacy.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2015 IEEE |
| ISBN: | 1-4673-7333-8, 978-1-4673-7333-3 |
| Keywords: | smart city; urban data; urban innovation; sustainability; data literacy |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Related URLs: | |
| Item ID: | 42603 |
| Depositing User: | Annika Wolff |
| Date Deposited: | 28 Apr 2015 08:21 |
| Last Modified: | 12 Sep 2018 01:55 |
| URI: | http://oro.open.ac.uk/id/eprint/42603 |
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