Exploring design principles for data literacy activities to support children's inquiries from complex data. Issue 129 (September 2019)

• Record Type: Journal Article
• Authors: Wolff, Annika; Wermelinger, Michel; Petre, Marian
• Is Part Of: International journal of human-computer studies. Issue 129(2019)
• Page Start: 41
• Page End: 54
• Publication Date: 2019-09
• Subjects: Data literacy -- Human-data interaction -- Smart city -- Open data; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2019.03.006
• Languages: English
• ISSNs: 1071-5819

Abstract

Highlights: Interactive data visualisations can support school children between the ages of 10–18 in asking valid questions from data. Curated snapshots of part of a small part of dataset can help school children understand how to frame questions around the extended dataset, along dimensions such as space and time to explore more and more of. A guided data inquiry can help lead to a more open data inquiry. The learning of data skills lends itself to cross-curricular learning and can begin with primary school students. There are a number of design principles that may help in developing new applications to engage children with complex data whilst developing new data literacies. Abstract: 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 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.