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Scientific Article details

Title Exploring design principles for data literacy activities to support children's inquiries from complex data
ID_Doc 40017
Authors Wolff, A; Wermelinger, M; Petre, M
Title Exploring design principles for data literacy activities to support children's inquiries from complex data
Year 2019
Published
DOI 10.1016/j.ijhcs.2019.03.006
Abstract Data literacy is gaining importance as a genes-al 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 students 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.
Author Keywords Data literacy; Human-data interaction; Smart city; Open data
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
EID WOS:000472687700004
WoS Category Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary
Research Area Computer Science; Engineering; Psychology
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