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Urban Data in the primary classroom: bringing data literacy to the UK curriculum

Wolff, Annika; Cavero Montaner, Jose J. and Kortuem, Gerd (2017). Urban Data in the primary classroom: bringing data literacy to the UK curriculum. Journal of Community Informatics (In Press).

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Abstract

As data becomes established as part of everyday life, the ability for the average citizen to have some level of data literacy is increasingly important. This paper describes an approach to teaching data skills in schools using real life, complex, urban data sets collected as part of a smart city project. The approach is founded on the premise that young learners have the ability to work with complex data sets if they are supported in the right way and if the tasks are grounded in a real life context. Narrative principles are used to frame the task, to assist interpretation and tell stories from data and to structure queries of datasets. An inquiry-based methodology organises the activities. This paper describes the initial trial in a UK primary school in which twelve students aged 9-10 years learnt about home energy consumption and the generation of solar energy from home solar PV, by interpreting existing visualisations of smart meter data and data obtained from aerial survey. Additional trials are scheduled with older learners which will evaluate learners on more challenging data handling tasks. The trials are informing the development of the Urban Data School, a web-based platform designed to support teaching data skills in schools in order to improve data literacy among school leavers.

Item Type: Journal Item
Copyright Holders: 2016 The Authors
ISSN: 1712-4441
Project Funding Details:
Funded Project NameProject IDFunding Body
MK:SMART, an integrated innovation and training programme leveraging large-scale city data to drive economic growth (Q-13-037-EM)H04HEFCE
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 47778
Depositing User: Annika Wolff
Date Deposited: 04 Nov 2016 16:48
Last Modified: 05 Nov 2016 04:08
URI: http://oro.open.ac.uk/id/eprint/47778
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