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Social learning analytics

Published 1 December 2012Open access
Simon Buckingham Shum, Rebecca Ferguson
Citations353
SJR quartileQ1
SJR score1.92
SNIP2.59
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TL;DR

It is proposed that the design and implementation of effective Social Learning Analytics (SLA) present significant challenges and opportunities for both research and enterprise, in three important respects.

Abstract

We propose that the design and implementation of effective Social Learning Analytics (SLA) present significant challenges and opportunities for both research and enterprise, in three important respects. The first is that the learning landscape is extraordinarily turbulent at present, in no small part due to technological drivers. Online social learning is emergin g as a significant phenomenon for a variety of reasons, which we review, in order to motivate the concept of social learning. The second challenge is to identify different types of SLA and their associated technologies and uses. We discuss five categories of analytic in relation to online social learning; these analytics are either inherently social or can be socialised. This sets the scene for a third challenge, that of implementing analytics that have pedagogical and ethical integrity in a context where power and control over data are now of primary importance. We consider some of the concerns that learning analytics provoke, and suggest that Social Learning Analytics may provide ways forward. We conclude by revisiting the drivers andtrends, and consider future scenarios that we may see unfold as SLA tools and services mature. © International Forum of Educational Technology & Society (IFETS).

Keywords

Computer ScienceSocial Sciences