自反性
定性研究
工作流程
定性性质
计算机科学
认识论
知识管理
参与者观察
社会学
定性分析
数据科学
认知科学
过程(计算)
管理科学
定性推理
心理学
工程伦理学
作者
António Pedro Costa,Grzegorz Bryda,Prokopis Christou,Judita Kasperiūnienė
标识
DOI:10.1177/16094069251383739
摘要
The integration of artificial intelligence (AI) into qualitative research is shifting the boundaries of knowledge production. Instead of mere tools, AI is increasingly conceptualized as a co-researcher or research partner—an epistemic agent that helps in the analysis, interpretation, and reflexivity of data. This article proposes an abductive model, called AbductivAI, for analyzing qualitative data, based on collaboration between humans and AI agents. It explores how AI functions as an analytical partner, reflexive collaborator, and participant in distributed cognition within the framework of the human-AI qualitative research workflow and data analysis approach. To build the model, we used advanced prompting techniques (Chain-of-Prompting) and used the 323 abstracts submitted to the World Conference on Qualitative Research as data. Although this data was not intended for research, its exploration allowed us to test the AbductivAI model, showing that interactions between humans and AI agents can benefit qualitative data analysis if the human recognizes and defines their role as a reflexive agent responsible for the entire process.
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