#CCK11: Juggling with Connectivism: Week 1
Connectivism has much to offer as a new perspective on learning and I’m pleased and excited to be one small node in the CCK11 MOOC. However, I find some of the phraseology a little jarring and I’m unsure whether this is because some of the concepts are perhaps overstated in odd ways but are in fact straightforward and commonsensical or whether new and profoundly different meanings are intended. “Learning may reside in non-human appliances” is a good example and from tweets and Leitha Delves’ blog I know I’m not the only one having problems with this. I come to CCK11 with very little background in learning theory and was not born yesterday so I’m probably more resistant than some when it comes to accepting new ideas. Anyway, here’s where I’m coming from (and I’m no biologist either!).
Firstly, since the capability to know or understand has evolved and adapted over many millions of years as a means of survival, I’d say that knowledge, know-how, meaning, understanding etc are primarily to do with the memory, modeling and ‘programming’ functions necessary for a living organism’s success (be it hunting, fighting, socializing or complex cultural activities). Learning is then the process by which organisms acquire these skills over and above the ones they are born with. In the case of the modern human, ‘success’ depends on an extraordinarily large number of cultural skills: reading, writing, etc and education in the widest sense. This places heavy demands on the individual in time and effort as well as economic and other burdens on society. Ways and means of meeting these demands in the most effective way is the concern of educators in particular and society in general.
Secondly, I’m quite happy to apply at least some some of the attributes of learning to non-human appliances such as books or databases. It seems natural to talk about the knowledge or meaning conveyed by a book or the know-how stored in a database (containing, for example, the procedural details of a complex constructional project). A robot programmed to construct something ‘knows’ how to do it and if the robot were to adapt and improve its performance through some sort of feedback mechanism then I might reasonably call this learning and ascribe an artificial intelligence to the robot.
If this type of thing is what Connectivism means by “Learning may reside in non-human appliances” then I’m quite happy with that but for me it seems to hang together perfectly well without bringing in connections at all. Clearly, connections are at work in the human brain and the robot might be programmed by an artificial neural network but outside that an individual can learn from a book, come up with a new idea, or learn how to juggle, without obvious engagement in social or any other sort of networks. No doubt the juggler would become a better and more knowledgeable or even expert juggler by exploiting connections within a network of jugglers, reading juggling books, accessing databases on juggling know-how or even interacting with juggling practice robots. Although juggling knowledge can then reasonably be said to be distributed across the network I’m not sure what is achieved by stating that it literally identifies with the connections between the nodes; another example of connectivist phraseology that jars with me, but maybe I’m missing something deeper. (Then again, maybe it’s all just semantics as I’ve certainly no problem with this little video by soto_mayra!)
Although I think that connectivism has the greatest relevance to social networks the connectivist focus on the similarities between neural networks and social networks jars a little less now after reading Stephen Downes, ‘An Introduction to Connective Knowledge’. It’s fascinating, scary even, to think how a futuristic social network or society could ‘know’ in a similar way to the human brain so I’m looking forward to next week’s topic on ‘patterns of connectivity’. (I wrote a facetious piece last year about education in 2022).
And now, back to next week’s readings ……..