Following Clare’s suggestion, I’ve been analyzing data in a less linear, and
perhaps more unconventional way. I printed out a week’s worth of whole-group
discussion notes in small font, cut them up by note, and grouped them into clusters.
Each cluster focuses on a problem or sub-problem that the students identified.
My goal was to find the relations between the notes in each cluster, and across
clusters. This process looked thus:
For practical reasons (my dog eats paper), I switched to Cmap, which you can download for free. It works on my MAC OSX, and for whatever reason, I couldn’t get the newest version of Inspiration to work on it. Wendy pointed me to Cmap in November 2005 and helped me find references on that site for one of my CSSE proposals. Also,
George Siemens has blogged about it (I know he blogged about this more recently, but can’t find the entry I want).
Getting back to my analysis, concept mapping worked well for exploring connections between notes and between clusters, and I felt less constrained by the linearity of a wordprocessor or spreadsheet. I can see that a qualitative data analysis software like NVivo would facilitate coded notes better, perhaps, but for now, this helped me work with ideas in a more flexible way. For instance, I could draw relationships between notes in different clusters with dotted lines and see recursion in students returning to certain ideas in other clusters. I also liked being able to see which students were interacting more visually (I gave each student a different colour). I could also jot down thought I had. Here’s just a close-up on the first couple of clusters:
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