Tag Archives: Data analysis

Finding the story in data

Over the last few days I’ve been working on analyzing some data generated using a survey as part of a study looking at the work of teacher educators. When I first looked at the data and began reading through it, nothing was speaking to me. I was reading through the words and categories and the problem was that I couldn’t find THE story. There was nothing that was calling to me, nothing that I wanted to read, or write, or learn more about. The ‘so what?’ question was reverberating in my brain and I wondered ‘what is the story here?’

I thought back to my PhD and advice that I’d had written on a post-it on my pinboard –  ‘Let the data tell the story’. 

Working on this project with a colleague we’d created a survey in Google drive and had used the automatic summary function that calculates the quant data into percentages and pie charts and which collates all of the qualitative responses together as well.  When I printed this data off and read through it there didn’t seem to be much of a story to the data – sure we could generate some themes and get some understandings about concepts but there was nothing that was ‘sexy’, nothing that appeared at first glance to have an edge. It’s an odd concept to think about our data as being ‘sexy’, as being something that captures both our imagination and the rational, logical parts of our brains, but it’s something that I was looking for and I was thinking of Robyn’s question ‘What do we want to read about?’ When I first looked at the data using this automatic summary, it seemed flat, boring, all dull edges and no shine and I wondered why this was.

Spurred on by Robyn’s question about what the silences in our data might be, I began to look at the possibilities of ‘reading between the lines’, of finding these silences, the concepts that are hidden, of finding only what is expected in the answers and of not discovering the unusual or the interesting. I was torn by this notion though, as in reading the silences am I only reading the silences of what I think should be there? Am I only projecting my own assumptions about what is hidden? I also wondered about highlighting the silences, as maybe the silences would just convey errors in our survey design, becoming a projection of our dysfunction as survey creators.

I walked away, crunching numbers and data and thinking about the story and the angle- what was the data trying to tell me? Like an investigative journalist I was thinking of what more there was to discover, determined that there had to be more that I was missing, that there was a shortcoming to the way I was looking at things. Later that night I dragged out the survey and began manually coding the data, organizing it into questions, looking at each participant and finding the similarities and differences between them. Suddenly, a light of story began to flicker in the data darkness.

When I began to look at each survey response, I began to see each person as a whole, not as a fragment of data, a figure, a percentage, a wedge of pie in a chart or a statement in isolation. Looking at each response in its totality I began to see the story emerge. In each response people were telling me more about themselves, what matters to them in their work, what helps and what hinders progress and development. Looking at their responses as a whole I began to see who they were. Here were their stories, writ large. Looking at each person’s story I began to find the connections, synergies and disconnections between their experiences. It was here that things started to get interesting. Suddenly I was enthused and excited and couldn’t wait to unpack what these differences meant and what we could learn from them.

In going back to the whole picture, I began to get a better understanding of the parts. When I listened properly and didn’t take shortcuts, I began to hear the data and the story it is telling me.

 

 

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