I have always refused to be constrained by the conventions of a genre, discipline, or society. Fitting neatly into such a compartment cramps my style, harshes my zen, and squashes my favorite lampshade hat.
As a result, my journey from quantitative researcher to qualitative researcher has not been without frustration. In general, both communities seem to scorn the contributions of the other. Qualitative researchers can be heard to say, “But when there are numbers, people think that it is concrete and objective! And nothing is ever objective!” Quantitative researchers, on the other hand, scoff, “But how can you possibly know that, with such a small sample size?” Neither side of the razor-wire fence separating the two forms of data seemed particularly keen to bridge the gap.
I have been waiting, dreading the moment when both communities turn to me and say, “Well? Decide already! Which will it be, quantitative or qualitative?”
I wouldn’t have an answer. I didn’t think I could choose.
Imagine my delight, then, when I was greeted by this poster on my first day of Design Ethnography this semester.
Catriona explained that in the early days of design ethnography, the ’80s and ’90s, practitioners of the discipline thought that the real challenge in design ethnography was doing the fieldwork. Through the early part of the 21st century, however, it became apparent that the real challenge was communicating the findings of a study.
Now, on the cusp of a new decade (depending on how you count it), it has emerged that while communicating the findings is important, and good field work is vital, the difficulty facing us now is interacting with other kinds of people and other kinds of data.
I heard this and a little light went on in my head. This challenge left room for me to build a career that combines design ethnography (my qualitative research of choice) and machine learning and data mining (my quantitative research of choice). There was hope!
It was not until the following Wednesday that I realized exactly how much hope there was. We had a guest speaker, Tye Rattenbury from the People and Practices Research group from Intel. He gave us a presentation on how his team does user research, and it blew my mind.
Essentially, what Tye’s team does is collect a bunch of quantitative data on a set of participants in a study. They mine the data for trends and create innovative ways to visualize the data to make it easier for the participants to understand. They take the data visualizations to ethnographic interviews and let the participants use the data as a prompt to launch a story. They let the participants give the numbers a voice. They let the participants make the numbers talk.
Not only is it a brilliant approach, I think it might be precisely what I want to do.