Home » learning

Visualisation as a means of coping with, and making sense of, data overload

In “Patterns and sense-making: information visualisation”, George Siemens proposes a variety of strategies to create visual representations of data to help us, essentially, get our heads around the big picture by spotting relationships, trends and connections before getting into the finer and statistical details.

It isn’t about oversimplifying complex issues, it is about giving the issues some colour and shape before delving.

He also went on the show a list of potential benefits from thinking about and applying appropriate filters to how we approach data. Here he reintroduced the vital concepts of networks, distributed knowledge and connectivism citing benefits (I’ve put my comments in parenthesis):
– Network models of learning are adaptive (because networks are inherently dynamic)
– Ecologies must be diverse and enabling (or we’re heading back to a model where we teach as we were taught not how different people might learn)
– Today’s information is tomorrow’s sense-making (I love this one. It brings to mind that when we ask for information there’s a moment when we realise that we’ve got an awful lot of stuff to make sense of before we can make use of it).
– Sane, digital life (in other words, not trying to take a drink of water from the fire hose)
– Complex, integrated understanding (again reinforcing the point that complexity is an integral part of understanding)
– Multi-faceted
– Multi-ontology

You can see a recording of the whole <i>Patterns and sense-making: Information visualisation</i> session at: http://sas.elluminate.com/site/external/event/playback

Leave your comment

Add your comment below, or trackback from your own site. You can also subscribe to these comments via RSS.

Be nice. Keep it clean. Stay on topic. No spam.

Proud to support

Archive