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Sociality and learning in social software

Authors: Tim Hoogenboom; Martin Kloos; Wim Bouman; René Jansen;

Sociality and learning in social software

Abstract

Lately, Web2.0 or social software receives a lot of attention, both by practitioners and academics, because of its ability to support social learning processes. We explore two criticisms that assess the learning impediments within current manifestations of social software. Firstly, we hold that social software is biased towards market-organising and secondly, it lacks a social theory of learning. By using both the social learning cycle of Boisot and the learning architecture of Wenger we theorise about structures that could guide the design of learning within social software. The objective of this paper is to support the design for object-centred sociality in social software to enable a more social approach to learning.

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    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Top 10%
Top 10%
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