This link has been bookmarked by 8 people . It was first bookmarked on 12 Aug 2008, by Christy Tucker.
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16 Sep 11
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Downes’ and Siemens’ discussions shed new light on fundamental concepts, such as rules versus patterns, complicated vs. complex, equivalence vs. similarity, and coping with ambiguity and uncertainty. And these consideration render many entrenched practices of the entire knowledge industry questionable.
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E-discovers complexity (much like the Renaissance re-discovered antiquity rather than discovering it) and encourages to apply complexity perspectives to areas where previously a rules-based approach was not questioned.
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notably emergent order, non-linearity, and the concept of independent agents. I think the biggest difference, as Matthias says, is that Connectivism applies complexity to areas where previously deterministic (i.e. rules based) approaches prevailed.
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Connectivism, I think, attempts to take the observations of complexity science and begin to build social structures that embody the same theories.
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I could see more opportunities, but equally interesting challenges, if informal connections are to “confront” the formal institutional settings. It is not just evolution, it is revolution, and it is happening, it is ubiquitous, and it is in constant flux. What do you think?
John
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12 Sep 11
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08 Sep 11
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03 Sep 08
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23 Aug 08
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13 Aug 08
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12 Aug 08
Christy TuckerAn answer to the question "What is Connectivism?" Rather than going for a fixed definition within the framework of a learning theory, the author argues that connectivism is an emerging concept best understood by looking at how it connects to other ideas and theories. The central metaphor of the network is the unifying element of connectivism.
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Downes’ and Siemens’ discussions shed new light on fundamental concepts, such as rules versus patterns, complicated vs. complex, equivalence vs. similarity, and coping with ambiguity and uncertainty. And these consideration render many entrenched practices of the entire knowledge industry questionable.
All these aspects have one thing in common: that they can be illustrated by the neuronal metaphor, the metaphor of a network with nodes and connections, where
“Not all connections are of equal strength in this metaphor” (Wikipedia)
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So, connectivism and its neuronal connections metaphor, allow to distinguish more clearly between two types of knowledge, one of which is the more adequate one for coping with complexity and uncertainty: connective knowledge.
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