Technological Reflexivity in Practice: How MAXQDA, NVivo, and ChatGPT Shape Qualitative Survey Analysis

The emergence of Generative Artificial Intelligence (GenAI) into qualitative data analysis software (CAQDAS) intensifies longstanding debates around about how digital tools shape qualitative analysis. This paper foregrounds the concept of technological reflexivity, critically examining how technologies co-produce research practices and claims. Drawing on a reflexive, empirical comparison of MAXQDA, NVivo, and ChatGPT, I examine how different software architectures and GenAI features mediate analytic decisions, researcher-participant relationship and interpretive authority. The analysis uses data from over 1,300 young people (aged 8–25) who responded to a climate-themed qualitative survey imagining the life of a fictional peer in 2050. Findings show how researcher strategies were shaped through distinct software tactics and how GenAI extends existing CAQDAS logics. Its integration raises new challenges for transparency and the relational sensitivity needed to interpret emotionally charged data. Responding to four questions posed by Paulus and Lester (2023) – concerning methods, knowledge production, researcher-participant relationships, and tool design – this paper contributes to calls for methodological transparency and technological reflexivity in qualitative research. It argues for understanding reflexivity as a distributed practice, shared (often unequally) across researchers, tools, and infrastructures. I call for collective responsibility in shaping the ethical and methodological futures of qualitative inquiry.