In the past year or so, I’ve been intensely focused on analyzing my online discourse data. At first, to be honest, I could barely stand to look at it. Once I did get some detachment from the data, I really immersed myself in it. I conducted in-depth content analyses, trained an alternate coder, and calculated inter-rater reliability on segmentation of units of analysis and coding. I proceeded to discourse analysis, using a group unit of analysis to characterize sequences of notes written by multiple students to advance group understanding.
In so doing, I examined minute details of each note in particular threads of discourse in the context of its production. I really did find lots to look at. I wanted to capture the richness of the data and not miss anything, however localized, that might be happening.
I saw how the notes were complexly interwoven with each other. I tried really hard to describe how the collaborative reasoning was distributed over a group of notes written by multiple students. I tried representing it graphically. Still, I just couldn’t articulate the highlights of my thesis findings. The story seemed so complex, and I couldn’t tell a simple narrative of what I found. I couldn’t see the forest for the trees, so to speak.
So I went to see Clare for help, and she told me to stop writing for now and make a table. She suggested I ask myself what I did in my intervention study that made a difference and what did not make a difference to the students’ discourse for each of my iterations. I’m still working on this table, but the good news is, I am finally starting to see clear patterns emerging on one intervention. I also have some interesting leads on the other intervention. Further, the explanations look like they might fit into all that literature I have been reading in and around my thesis topic. So I am finally beginning to see the forest and the trees.
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