This week in Connectivism Stephen Downes and George Siemens differentiate between groups and networks. When I first started to consider connectivism as a learning theory, I had difficulty separating these two ideas. I wondered how connectivism was any different than cooperative learning with technology. A simplistic view, I know. But, playing devil's advocate in my own mind, I couldn't immediately see enough differences to warrant a brand new theory of learning. That changed for me somewhat over the past weeks and more so this week.
A few key concepts associated with groups and networks really clarify the differences.
Groups
Unity
Value
Closed
Limits
Distributive
Unequal
Networks
Connections
Diversity
Autonomy
Open
Distributed
Equal
Connectivism is about networked learning. This doesn't mean that groups won't form within networks. It just means that connective learning in it's most powerful sense has the characteristics on the right side of this concept map. Those characteristics are what differentiates groups from networks and connectivism from other learning theories.
Just one question...
I'm grappling with the notion that networks are like ecosystems. When I think of an ecosystem, I think of critical dependencies whereby the ecosystem fails when one component fails. Yet in a complex network, a node could theoretically disappear without causing major impact to the network. Again, I'm getting caught up in metaphors when I should be thrilled that all of this is starting to make a lot more sense to me.
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4 comments:
I wouldn't say that networks are like ecosystems. Ecosystems are a type of complex network. In a rich ecosystem, there may be several species that disappear but the ecosystem itself survives. There can be instances, however, where a species is so critical by virtue of its many connections to other species in the ecosystem. So it is with any complex network - there are key, highly connected nodes the absence of which can cause the network to fragment.
My understanding is that the greater the diversity of related species in an ecosystem, the greater the likelihood that the ecosystem will survive. Stated differently, more complex ecosystems are more robust because they afford greater flexibility.
I'm not suggesting that you are not suggesting as much--just pointing out that where nodes in a network are less centralized, there is more of a chance that the network will continue to evolve.
Could you elaborate on the technology components for groups vs networks? It seems as if the technologies on the right side are not used on the left side and vice versa in your diagram.
Hi Wendy,
I am a teacher of logistics and I have been working as a lecturer since 1985.
A few years ago, I joined the assessor network, but I seldom participate in any activities. I used it as a resource only. In this case the the network consists of a few hundreds of TAFE teachers and practitioners (private providers) all over the states in Australia. I can raise a point to the network, but wouldn't be expecting any reply. It's difficult to pay full trust as other competitors (assessors) may be checking on you.
We have teaching and learning groups, recognition groups (or committees) and we have observed all rules and regulations in our institutions. Any points raised must be thought through carefully. Otherwise, we may not be exhibiting our professionalism.
In summary, I think group is more formal (especially in an institution) and network could be rather informal.
Relating to your metaphor on ecosystem, take a look at this "network", I am not sure whether you could even identify the individuals contribution. So I agree with your observations.
My question is: Do you find it easy to work in a network? Example: raise a comment or question?
Cheers. http://suifaijohnmak.wordpress.com
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