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Exploring design principles for data literacy activities to support children’s inquiries from complex data

Wolff, Annika; Wermelinger, Michel and Petre, Marian (2019). Exploring design principles for data literacy activities to support children’s inquiries from complex data. International Journal of Human-Computer Studies, 129 pp. 41–54.

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Data literacy is gaining importance as a general skill that all citizens should possess in an increasingly data-driven society. As such there is interest in how it can be taught in schools. However, the majority of teaching focuses on small, personally collected data which is easier for students to relate to. This does not give the students the breadth of experience they need for dealing with the larger, complex data that is collected at scale and used to drive the intelligent systems that people engage with during work and leisure time. Neither does it prepare them for future jobs, which increasingly require skills for critically querying and deriving insights from data.

This paper addresses this gap by trialling a method for teaching from complex data, collected through a smart city project. The main contribution is to show that existing data principles from the literature can be adapted to design data literacy activities that help pupils understand complex data collected by others and form interesting questions and hypotheses about it. It also demonstrates how smart city ideas and concepts can be brought to life in the classroom.

The Urban Data School study was carried out over two years in three primary and secondary schools in England, using smart city datasets. Three teachers took part, providing access to different age groups, subject areas, and class types. This resulted in four distinctive field studies, with 67 stu- dents aged between 10-14 years, each lasting a few weeks within the two year period. The studies provide evidence that when engaging with data that has not been personally collected, activities designed to give the experience of collecting the data can help in critiquing it.

Item Type: Journal Item
ISSN: 1071-5819
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 Higher Education Funding Council for England
Keywords: Data literacy; Human-data interaction; Smart city; Open data
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 59762
Depositing User: Michel Wermelinger
Date Deposited: 15 Mar 2019 16:23
Last Modified: 01 Apr 2019 17:19
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