Journal prompt: To Code, or not to Code?

I was surprised to find that I have an affinity for coding.

Maybe this is a wrong use of a tool, but I ended up downloading a free trial of Atlas.ti and using it to help me weed through the literature review for my research proposal. I figured, if I can use this thing to organize my own data, why can’t I use it to code organize others’ data too?

A couple weeks later, I’m at capacity with what I can do with the trial version… and I want more… so I’m seriously considering investing in this thing. Can anyone say educational tax deduction?!?

Anyway, I didn’t expect to be “a coder…” Prof. Webb says there are coders, and there are not-coders, and whether or not you do it depends on your theoretical orientation, the types of data you collect, and the nature of your research question. Sure, but I also think it has to do with how your brain works. My brain likes to collect things in bins, and coding works well for that. As I started to navigate my research proposal I was getting really (really) confused, and taking a few steps backward – going back through the literature with a more deliberate approach while looking for codes really helped me to figure out what the heck was going on.

So I guess I’m a coder. And honestly, my whole research proposal is sort of about looking for “codes,” in trying to find what really matters when it comes to dance performance. As I sifted through the literature for the… fourth?… time, I coded en vivo the qualities that were cited in different models, and then looked for similarities to group those en vivos together under an umbrella term (that is, until the trial version wouldn’t let me create any new codes and still save the project… but that’s fine for now, provided my computer doesn’t crash).

In reading and coding Prof. Webb’s interview transcripts as a class exercise, I found this coding activity slightly more challenging, perhaps (as we discussed in class) because I am not as “intimately connected” with that data. This is an important lesson to learn, because someday when I’m a famous dance researcher I will be in a position to hire individuals to help with data coding and analysis, and they won’t be as “intimately connected” with my data. While I could be tempted to respond to that struggle with, “Huh? How could you not think this is important? You mean, you don’t know anything about dance?” The likelihood of that being a worthwhile approach to the problem is slim to none.