Making the Invisible Visible: modelling social learning in a knowledge management context

Henry Linger, Leoni Warne

Abstract


The articulation of Knowledge Management as an organisational strategy has occurred in the context of a radical shift towards an information based economy. The most significant aspect for organisations operating in the information economy is their ability to utilise the volumes of information that are now readily available without the constraint of media, geography or time. A critical factor for organisations is the speed at which they are able to productively process such information to enable the organisation to react rapidly to changes in their operating environments.
In this context organisation needs to produce and re-produce knowledge. The shift from information to knowledge is an acknowledgment of the significant role of the human actor in the process of transforming information into effective organisational outcomes. Social learning represents important processes that contribute to actors’ ability to understand information, create knowledge from that information and share what they know. Social learning is therefore intrinsic to knowledge management.
In this paper we present a knowledge management architecture that supports a learning organisation. This architecture accommodates social learning and processes by which knowledge is internalised and externalised by individuals, work groups and the organisation as a whole. The architecture incorporates a model social learning based on the results of ethnographic studies and a model of learning derived from knowledge management case studies. The architecture is not domain specific but can be applied to activity that can be characterised as knowledge work in an organisational context. As such the architecture can play a variety of roles; as a conceptual framework, as a diagnostic tool to identify breakdown and as a design tool for organisational change.

Keywords


Knowledge Management; velocity; volume; social learning; architecture; framework

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DOI: http://dx.doi.org/10.3127/ajis.v9i1.214

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ISSN: Online: 1326-2238 Hard copy: 1449-8618
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