What question did this study set out to answer?

The framework aims to innovate qualitative research by integrating traditional methods with AI-driven data analysis.

March 12, 2026Open Access

A Mixed-Method Qualitative Design Framework for the Age of Artificial Intelligence

Key Points

The framework aims to innovate qualitative research by integrating traditional methods with AI-driven data analysis.
Developed a mixed-method framework called QDA/DS.
Combined inductive reasoning with algorithmic inference.
Focused on maintaining human interpretation within qualitative research.
Utilized AI tools to enhance research scalability and transparency.
Demonstrated improved precision and methodological rigor in qualitative research.
Indicated that AI can complement rather than replace human insights.
Showed potential for broader application of qualitative methods through AI support.

Abstract

Abstract This paper introduces an innovative mixed method design framework called Qualitative Data Analysis/Data Science (QDA/DS) for conducting qualitative research in the age of Artificial Intelligence (AI). The framework integrates the inductive reasoning epistemology of traditional qualitative research with the algorithmic inference of computational data science. Its objective is to enhance the precision and methodological rigor of qualitative inquiry while preserving the essential role of human interpretation. Enabled by AI and complementary computational tools, this integration empowers researchers to extend the depth, scalability, and transparency of qualitative research without replacing the interpretive function of the human researcher. Keywords QDA/DS, Triangulation, AI-assisted qualitative analysis, Grounded theory, Mixed-method research

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