The temperature did not get above 28 degrees for the full 7 days we were in Alaska.  It snowed every day.  Not just little snow—big snow.  For a few days, the wind blew so hard that the snow drifts shifted from one end of our hotel parking lot to the other. I grew up in Utah, so I should be used to snow—but as mentioned in a previous entry, I am a bit of a wimp when it comes to cold weather.

The moment I landed in Alaska, though, something magical happened.  I was somehow transformed.  I loved the snow.  I got up early every morning to peek out my hotel room window and hoped desperately to see more snow.  I relished in putting on layer after layer to go outside.  I wore boots all the time and did not miss any of my other shoes (and that is pretty unbelievable for me).  I never felt cold.  Not once.  I cannot tell you exactly how it happened. I attribute it to finding my “inner Alaskan” (and during the trip I even helped my daughter write a poem called “My Inner Alaskan”).   The transformation was unbelievable.

Next week I begin the three-week module on data analysis.  It is the most intense part of the semester because students are still in the midst of collecting data but given the timeline, they have to learn how to transform that data from words on pages or computer screens to something that 1) answers their research question (which many are still tinkering with) and 2) is faithful to the site and people they are working with (when they are probably not entirely entrenched in the site yet). In terms of a teaching challenge—it is significant.  Students are worried they will not finish.  Students are concerned they will not do analysis right.  Students feel unqualified to be at the helm of the transformation.  It feels mysterious to them.  It feels like they have to do something that is almost magical.

When I took my daughter to Cinderella, she was about 3 ½ years old.  After the infamous Bibbidi-Bobbidi-Boo song/scene, she asked me:

“How did the fairy godmother do that?”
I answered what any mom probably would—“she’s magic.”
My ever curious and grounded daughter would not stand for that.
“How does the magic work?”
Good question, peanut.  Good question.
“Well, I don’t quite know.  It just does for fairy godmothers.”

How does the magic of qualitative data analysis work?  On the first day of teaching analysis, I provide students with a step-by-step process.  I show them how to identify units of analysis, reduce the data, place units on index cards, go through the constant comparison technique, name and refine category names, test for internal homogeneity and external heterogeneity, and run intercoder reliability tests.  Students find relief in what they see as a fairly black and white process. And then they try it and realize they were living an illusion.  Data analysis is messy.  They often ask me:

“How do you deal with a unit that—based on your interpretation—can fit in two categories?”

“How do I know if this is a full unit–it is a complete thought but rambles for a paragraph before getting to the point.”

“How do you deal with that quotation that has important underlying meanings (you know, because you were there) that do not come through the words?”

“How do you know if you have too many categories?”

I teach students to do thematic analysis with index cards.  They type out units and glue them to cards and use cards to create categories (through constant comparison technique).  I tell them to spread out on a floor of a room and to use the space to visually explore which unit fits with which category.  Or I tell them to use push pins and wall space to place cards in groupings along the walls of their research space.  I’ve resisted teaching qualitative analysis software mostly because I’ve resisted using the software.  But, I decided I needed to venture into my first software program this past summer—to test out my assumptions so I could speak competently about the process and make an informed decision about whether I wanted to teach it.  What I learned, experientially, is that the software programs help manage the data.  They do not do anything miraculous with it.  I still had to make the decision about which code was assigned to which unit.  I still had to decide when my categories were too broad or too narrow.  I still had to read into the quotations to find the meaning.  But I couldn’t see the cards all spread out in front of me or on the wall.  I couldn’t touch them or move them.  So, I’m back to index cards.  I like teaching analysis as a tactile and visual process (as well as a cognitive one).

The index cards only get us so far, though.  Once we’ve generated several categories that meet all measures of quality, then what?  This is where the transformation takes place.  This is the dreaded interpretive move.  And this is the concept I find hardest to teach in qualitative research methods. There is no process or template for making this move.  There are not 5 steps students can take to get to a good interpretive move. It requires a leap from the data while being tethered to the data.  It requires taking cards and categories and figuring out what they mean. It necessitates insight beyond the data. It requires thought.  And more thought.  And it requires instinct about human interaction and activity.

I tell students I have no magical process.  I wish I did.  The best I can tell them is to set aside thinking time to focus solely on the data.  I suggest they sit quietly amidst the data and to think about what it means—big picture.  I tell them to walk around the data, literally (remember, in my world the data are on index cards spread all over the floors or walls of the research space) to see if anything stands out.  I tell them their brain should hurt.  And when it does, I tell them to do something that requires very little academic thought—something physical (e.g., walk, run, bike, swing, etc.) to allow their body to move and their mind to rest.  Those are usually the “ah ha” moments for me—when I am allowing my brain to rest and open up to the fresh air. I tell them it will take time and patience and that it requires difficult brain work.

That does not comfort them.  They much prefer the step-by-step process, despite its grey hues.

Every year I try to figure out a good way to teach the interpretive move.  As I ponder it this year I’m thinking of having students do some of the brain work in class—in the space of the learning context, sitting amidst their data, with music playing in the background.  And I’m thinking of taking them out to the courtyard for a silent walk.  I’m not sure if that will do it.  But that is all I can think of right now—after sitting here in the midst of my teacher materials trying very hard to figure it out.

My brain is starting to hurt.
I think I will go out for a run.
Perhaps I can channel my inner fairy godmother.

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