The Role of Generative AI in Qualitative Research: GPT-4's Contributions to a Grounded Theory Analysis
Ravi Sinha, Idris Solola, Ha Nguyen, Hillary Swanson, LuEttaMae Lawrence
Abstract
We present reflections on our experience using a generative AI model in qualitative research, to illuminate the AI's contributions to our analytic process. Our analytic focus was a segment of classroom transcript, which captured a teacher introducing scientific theory-building practices to middle school students. We used a grounded theory approach to produce a fine-grained characterization of the teacher's talk moves during the lesson implementation. Our eventual goal is to build a more nuanced conceptualization of responsive teaching in the context of theory-building activities. We involved GPT-4 during the initial exploratory and later focused coding stages. For our analysis of GPT-4’s contributions to the analytic process, we analyzed our notes and analytic memos, along with video recordings of meetings where we discussed insights in response to GPT-4’s input. We present vignettes to illustrate pivotal moments where AI contributed to the coding process, including code generation, comparison, and refinement. The paper presents our experiences of conducting qualitative research in partnership with generative AI, underscoring the role that emerging technologies can play in the analysis of data and the development of grounded theory.