Learning networks are a complex interaction between structures and activities. Each of the key features has a role to play and, like any complex system, the ways in which they combine and interact are innumerable and cannot be predicted in any particular context. Complex systems theory is useful for understanding the workings of networks. A central characteristic of complex adaptive systems is the interdependence of the features, with each one being connected to all of the others. A change in any one invites changes in the rest. For example, the nature of collaborative enquiry will depend also on the quality of relationships; capacity building and support will depend on the kinds of leadership that exist; the role of accountability will depend on the focus and purpose, and so on.
Research Professor on society, culture, art, cognition, critical thinking, intelligence, creativity, neuroscience, autopoiesis, self-organization, complexity, systems, networks, rhizomes, leadership, sustainability, thinkers, futures ++
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