Visualizing my understanding of connectivism

Matthias Melcher, Concepts, May 01, 2014
Commentary by Stephen Downes
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Connectivism, as I describe it, suggests that there are different types of knowing networks. A human neural network is one. A society (or social network) is another. A neural net computer program is another. So far so good. But Geoff Cain asks the question: "how are these related? The recent criticisms show that it is difficult to reconcile these two." I would point out that there is no particular requirement that they be reconciled. It would be nice for us if they did, but it's not a priori necessary.


I think there are two answers, which I'll call 'the Downes answer' and 'the Siemens answer' because I've talked mostly about one and George has talked mostly about the other. These two are not mutually exclusive, they might both be true, and (probably) elements of both of them are, as they vary mostly from the perspective of point of view as opposed to postulation of a different causal mechanism.


The Siemens answer is multimodal extension. The networks reach out and integrate with each other. Thus, for example, a concept might be contained partially in a human brain but the full extension of the concept might extend beyond the network of neurons to include, and interact with (as part of the same network) extra-neural entities (like computers, other people, and the like).


The Downes answer is pattern recognition (yes yes I know William Gibson wrote a book of that name, and that the concept is widely discussed by others). One network perceives patterns in another network and interprets or recognizes these patterns as something. So, for example, a social network might recognize 'genius' in a person via the presentation of patterns of behaviour by that person that cause responses typical of recognition of genius in society.

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