I have been quite impressed by the breadth and depth of the conversations in CCK08, and have already started thinking about what I can take back to my more ordinary teaching and training. Here I run into a challenge, and it’s got me thinking about our network diagrams.

All the ones I’ve seen are two dimensional, but I think there’s a third dimension, prior learning, which plays an important role. While few of us know anywhere near what George and Stephen do about the topics of the course, neither are most of us novices. Many of us are familiar with social networks, concept maps, and learning theory, for example. Therefore we have some prior understanding in which to ground our thinking, leading to some intelligent comments and questions.

I am considering two possibilities.

a. The level of discourse correlates directly to the mean level of prior learning. If you put knowledgeable people together, the conversation will be good.

b. Discourse level correlates inversely to the standard deviation of the level of prior learning. I think of this in terms of knowledge/learning gaps. My imagined typical case is the standard freshman survey of X where the instructor knows quite a bit and the students often know very little.

When we think about networks for learning, we have to ask , “From where in the network is the knowledge/information/etc. going to propagate?” I know this goes against the idea that the knowledge is in the network links, but, for example, I just saw a classmate Tweet a request for information on how to perform a technology task. In that instance there was a specific piece of information (instructions on how to do Y). The questioner was trying to find a node (person) on the network that had that information.

This isn’t to say there is no gestalt. In interacting with your network, you can come up with an idea that you and others on your network hadn’t thought of before. Perhaps those two processes work side by side.

I now notice that I’m rambling, so I’ll quiet down and see what everyone else thinks.

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