My Experience, My Data: Using Autoethnography for Research

So, here’s something I didn’t see coming in grad school: apparently, my own experiences could count as research. I know, it sounds a little strange. I was trained to trust data, reports, and policy frameworks, not my day‑to‑day experience with how I do research. But then I learned about autoethnography, and it completely changed how I think about public policy and how it actually works in real life.

I first heard about autoethnography from my thesis adviser during my master’s program, when we were still trying to figure out how to deal with my research topic for my thesis.  Autoethnography, introduced and promoted by scholars like Carolyn Ellis, Arthur Bochner, and Tony Adams, encourages researchers to use their own experiences as part of the analysis, as long as those experiences are connected to bigger social and institutional realities. At the time, the idea felt a little unusual, but also exciting. It made me wonder whether my own encounters with policies and institutions might actually matter as research material.

Like many researchers, I was trained to value data, reports, and evidence-based frameworks. Numbers, models, and official documents were the tools I trusted most. But when I started working on my master’s thesis, I realized that these tools don’t always provide the depth of a particular issue. Using autoethnography pushed me to pay attention to everyday moments, meetings, group discussions, and even decision-making processes that often get lost in research amd analysis but say a lot about how I incorporate knowledge into my outputs.

Indeed, autoethnography allows a researcher to not only write down their experience but also to take a step backward and look at the data before them, analyzing how their experiences relate to societal norms, values, and issues.

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As I wrote my thesis, reflection became part of my research process. I began asking simple but important questions about my own experiences with research: Why did I use this information rather than that? Why use data from other regions instead of our neighboring countries? What I initially thought were just personal reactions often turned out to reflect institutional issues, like official preferences and other constraints.

The process wasn’t always easy. Writing about my own experiences meant being honest about uncertainty and discomfort. Still, it helped me see policy from another perspective. Abstract concepts suddenly felt real, and my research felt more grounded in lived reality than mere theory.

Using autoethnography allowed me to uncover the different ways I incorporate my knowledge in my area of expertise in my research. Only through careful reflection did I realize these practices existed. This process changed how I approach my job and deepened my understanding of my field.

Looking back, the biggest lesson I took from using autoethnography is this: good public policy research isn’t only about getting the analysis right, it’s also about paying attention to how we do our research, on the things we consider when we make our recommendations. Autoethnography taught me that reflection can be a strength, not a weakness, and that sometimes the most useful insights come from the everyday moments we often overlook.