If you’ve been following along on this blog lately, you already know that right now I am in the inception stage of plotting my research practicum: a study that I will conduct during this second year of my program. This is seen as sort of a “mini-dissertation” complete with a round of convincing a committee that your proposal is a good one, all the way to defending the results when you are done.
I am a social networking gal, and I’ve been obsessed with Penuel et.al’s examination of teachers’ interactions in a school wherein they took a social capital approach. I keep coming back to this idea, and every time I read this study I think: I WANT. Now, that being said, this IS NOT EASY TO DO AT ALL. It is even harder considering I am a baby researcher and there is one of me, and this study had four really amazing researchers working on it. The whole section of analysis done by Ken Frank is all greek to me (haha! stats joke!), for I am not anywhere close to able to imagine how they go from point A to point B in this analysis. Fingers crossed I get to take his class before I’m done: Survey Design was offered at the same time and I really needed to take that one, too. Plus, I’ve been told that the other research methods course I’ll be taking (advanced multivariate) will assist me in better understanding the social network analysis.
At any rate, in my attempt to bite off a chunk of this type of work, I found some amazing databases on our state of Michigan Department of Education website, including a database of tech proficient teachers. I was thrilled. I am interested mainly in tech adoption by teachers, and here was one measure of tech proficiency for the entire state! With all the other data collected on teachers in the state, I thought I could really do some fun analysis, checking for correlations with all sorts of other factors. It was gold!
Then I sat down with my advisor and we worked on my crazy spreadsheets, got them aligned in SPSS, and I realized: oh crap, there are ALL sorts of problems with this data. These are not tiny limitations, these are they types of flaws wherein a lot of work will go into me knowing basically nothing about the rates of tech proficiency in the state of Michigan. D’oh! Once I had climbed the hill and started digging, I realized those shiny objects were of little value.
Good thing I had a backup plan.
The lesson I am learning is that sometimes in research, my plans are not as good as I think they are. In my lit review, I stumble across the perfect article based on title and abstract, only to be let down in the reading of it. In my research proposal, I am on method SEVEN now as I shed each one for this or that fatal flaw. (I admit it stung a little when my advisor said, “I can’t even remember what you are studying anymore.” Ouch. But true, oh so painfully true.). I can only hope that through this method of thinking, proposing, poking holes, finding flaws, and starting over again I will end up with something I can get approved, carry out, and defend. I would really like to discover the magic formula so that the process could become more efficient for me, so if anyone has any suggestions, let me know. I suspect that this is how it goes for everyone. Maybe it’s like learning any process: at first you have the slow, jagged movements of a beginner, and after a while those movements become practiced and fluid. I hope so any way.