Visualizar'11 (subtitled "understanding the infrastructures") is a workshop lasting 3 weeks (from 14/6 to 30/6) intended to develop several projects related somehow to data visualization with the underlying leitmotiv of the infrastructures. The first two days were devoted to keynotes and "communications" from experts in the field, and since then you can participate in one of the 10 selected projects (in my case, in order to learn a bit more about the topic). Right now I am more or less implicated in a project related to visualize the Google technological infrastructures in order to show implications to the "don't be evil" stuff: open source and closed components, effort devoted to them, etc. Let's see where it takes...
But why (the hell) do I want to learn more about data visualization? Because visualization is one of the tools for analysis of collected learning statistics (events). If well used, it can be very powerful since it permits to find relations among data not directly related to other data. As Enrico Bertini said in Visualizing Europe last week, we have to find the concrete field or context where visualization was not useful but indispensable. And I think that for learning analytics in class (in the enactment phase) it is indispensable for facilitating teacher monitoring of the activity of the students (in the context of a lab session).
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| W. Ross Ashby, from wikipedia |
Another concept I want to highlight is Intelligence Amplification (W. Ross Ashby, 1956) as opposed to Artificial Intelligence. As Inês Salpico so well introduced during her communication at Visualizar11, the visualization is not supposed to be an AI product but a IA tool, that is, a tool that helps the user to amplify his/her potential (let's say intelligence) in order to accomplish a concrete task. And this is actually what I want to do in my PhD!!
Will I enable the visualization of the learning infrastructures? Hopefully!
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