App clusters: Exploring patterns of multiple app use in primary learning contexts

Howard, S, Yang, J, Ma, J, Maton, K and Rennie, E 2018, 'App clusters: Exploring patterns of multiple app use in primary learning contexts', Computers and Education, pp. 1-30.

Document type: Journal Article
Collection: Journal Articles

Title App clusters: Exploring patterns of multiple app use in primary learning contexts
Author(s) Howard, S
Yang, J
Ma, J
Maton, K
Rennie, E
Year 2018
Journal name Computers and Education
Start page 1
End page 30
Total pages 30
Publisher Elsevier
Abstract There has been a continuous and rapid increase in the volume of apps in recent years since tablets became widely available in schools. Tablets contain a wide variety of apps, which are used for a large range of activities and tasks, and they are used in different combinations over time. Yet, there is limited research on young children's real and varied use of apps. The variety and volume of apps accessed by young children contributes to difficulty understanding there use and the consequences of that use. This has limited understanding of how apps contribute to students' learning. Given the importance of high quality early learning experiences, it is essential that the use of apps in schools is better understood. This paper explores young children's real varied app use through a large aggregated Australian dataset of app usage in primary schools, which has been collected automatically from approximately 15,000 Android devices over three years. The data mining methods of clustering and association rules analysis have been used to identify patterns of app use. Results show five distinct patterns of app use. Findings provide important insights into the complexity of multiple app use in the classroom. Implications of different use patterns in relation to learning and teaching are discussed.
Subject Educational Technology and Computing
Communication Technology and Digital Media Studies
Keyword(s) technology integration
multimedia/hypermedia systems
elementary education
data mining
DOI - identifier 10.1016/j.compedu.2018.08.021
Copyright notice © 2018 Elsevier Ltd. All rights reserved.
ISSN 0360-1315
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