Qualitative Research in the Era of AI: A Return to Positivism or a New Paradigm?
The integration of artificial intelligence (AI) into qualitative research is transforming the landscape of social inquiry, raising significant epistemological and methodological, questions. This study explores the dual potential of AI to enhance the scalability in qualitative research while challeng...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-04-01
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| Series: | International Journal of Qualitative Methods |
| Online Access: | https://doi.org/10.1177/16094069251337583 |
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| Summary: | The integration of artificial intelligence (AI) into qualitative research is transforming the landscape of social inquiry, raising significant epistemological and methodological, questions. This study explores the dual potential of AI to enhance the scalability in qualitative research while challenging its interpretive depth. It situates this tension within the historical trajectory of qualitative research -and specifically Grounded Theory- from positivist to constructivist paradigms, highlighting how AI’s automated, data-driven approaches may signal a resurgence of positivist assumptions. Key research questions guide this exploration: To what extent do qualitative researchers harness AI’s efficiencies in data analysis? Can the extended use of AI in qualitative research impact the depth and reflexivity essential to interpretive analysis? To delve into these questions the study employs a Technology Acceptance Model (TAM) survey combined with semi-structured interviews, strategically targeting European researchers to explore AI’s perceived usefulness, ease of use, and implications for qualitative methodologies. Survey and interview findings reveal a generational divide: early-career researchers embrace AI’s capacity for large-scale data analysis and thematic identification, while experienced researchers express scepticism about its impact on qualitative reflexivity and contextual richness. This generational gap implies that the receptiveness of younger researchers could lead to a gradual return to a methodological positivism. While this study brings a generational divide under the spotlight, future directions call for deeper investigations into the structural inequalities shaping AI adoption, such as access to resources, geography and gender. |
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| ISSN: | 1609-4069 |