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Evaluating action learning: a critical realist complex network theory approach

Evaluating action learning: a critical realist complex network theory approach

This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around complex systems and networks. Network theory is the general proposition that the world can be understood as a system of nodes or links at recursive levels (individuals, groups/departments, organisations, clusters and industries etc.) and includes, but is by no means limited to, social networking. The paper will argue that action learning can help organisations and groups, understood as networks, balance the destabilising tendencies to explosion and implosion, and, rightly used, can help prevent network distortion (over-dominance of one group of stakeholders).

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