For the past 24 months I have been developing, implementing, and collecting data for my research exploring how a reflective action learning intervention impacts innovation in higher education. 24 months…I can’t believe it has been that long. Sometimes I feel that not enough is being done to ignite innovation, and that my research will drag on forever with little impact. In 2019, 18 faculty and staff on four teams participated in this intervention and more will join in 2020. The innovative outcomes produced by these teams may take months or years to implement, and the effectiveness of each innovation will take even longer to realize. No wonder I sometimes feel like there is no end in sight. But as I learned while recently conducting a little preliminary qualitative data analysis, there is no need to wait for some contrived end…the meaning is already there, embedded in the work, waiting for you.
One day I will share the preliminary findings of my research with you all, but not right now. Right now, I want to share a short reflection on my research and how it led to a shift in my identity.
The vast majority of data for my current research are qualitative. I don’t consider myself to be a qualitative researcher. My career in institutional research and assessment has been focused almost exclusively on quantitative data. I’m way out of my comfort zone here. To become more comfortable with qualitative data, I recently completed several rounds of coding using different approaches. With The Coding Manual for Qualitative Researchers (Saldaña, 2015) as my guide, I coded a sample of my preliminary data using process coding followed by focused coding. I then turned around and coded the same data using descriptive coding followed by pattern coding.
Being relatively new to qualitative coding, I always feel like I’m doing something wrong. I want everything to fit into a nice formula or table, and well, that just isn’t how qualitative coding works. After completing these coding exercises, a litany of areas for improvement stood out to me. I realized my first cycle of coding was always too high level, and I need to be more granular at first. I need more time to step away between first and second cycles, and frankly, I need at least three or four passes to truly begin to make sense of the codes, categories, and themes. I also learned that some coding styles feel more natural and that one coding method may fit with a purpose of one’s research better than another. Although I felt I had missed so much and made so many mistakes, I forged ahead.
I reexamined the descriptions, applications, and methods of analysis associated with my coding approaches, and then I returned to my data. The iterative nature of qualitative research became my reality. And then it happened. Trends and themes started appearing, almost like they were jumping out of my coding software (HyperResearch) and into the air in front of me. I did it! And wait…I remember this feeling from earlier this year when I first started coding qualitative data. I’ve done this before! Holy cow! Does this mean…I’m a qualitative researcher?
Identity is a powerful thing. Although for most of my career I lived with quantitative data, I never truly felt at home there. Each time I sit down with my qualitative data and work through that iterative process – coding, memo-writing, codeweaving – each time those trends and themes start jumping out at me, I see the potential. I feel the possibilities. And all I want to do is dig in deeper to understand more. While I will always value the complimentary benefits of mixed methods, I want the world to know…qualitative research has my heart.
The biggest lesson I have learned from reflecting on my journey as a researcher is not about the steps I should follow to complete the process. It’s that while it can be daunting to dive into an endless sea of qualitative data, those pearls you find after scavenging the depths and sifting through the sand are worth it. So dig in. You never know what is waiting for you.
