Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/22185
Appears in Collections:Faculty of Social Sciences Journal Articles
Peer Review Status: Refereed
Title: Digital analytics in professional work and learning
Authors: Edwards, Richard
Fenwick, Tara
Contact Email: r.g.edwards@stir.ac.uk
Keywords: Digital analytics
professional practice
learning
algorithms
big data
software
Issue Date: 2016
Publisher: Taylor and Francis
Citation: Edwards R & Fenwick T (2016) Digital analytics in professional work and learning, Studies in Continuing Education, 38 (2), pp. 213-227.
Abstract: In a wide range of fields, professional practice is being transformed by the increasing influence of digital analytics: the massive volumes of big data, and software algorithms that are collecting, comparing, and calculating that data to make predictions and even decisions. Researchers in a number of social sciences have been calling attention to the far-reaching and accelerating consequences of these forces, claiming that many professionals, researchers, policy makers and the public are just beginning to realise the enormous potentials and challenges these analytics are producing. Yet, outside of particular areas of research and practice, such as learning analytics, there has been little discussion of this to date in the broader education literature. This article aims to set out some key issues particularly relevant to the understandings of professional practice, knowledge and learning posed by the linkages of big data and software code. It begins by outlining definitions, forms and examples of these analytics, their potentialities and some of the hidden impact, and then presents issues for researchers and educators. It seeks to contribute to and extend debates taking place in certain quarters to a broader professional education and work audience.
Type: Journal Article
URI: http://hdl.handle.net/1893/22185
DOI Link: http://dx.doi.org/10.1080/0158037X.2015.1074894
Rights: © 2015 The Author(s). Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/Licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Affiliation: English Language Teaching
Education

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