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Abstract
This study explores the integration of ChatGPT-4 into the qualitative research process, focusing on the methodology of Situational Analysis by Adele Clarke and analysing TED Talks transcripts. Findings show ChatGPT's ability to process data quickly in initial coding, formulating broader categories reflecting Clarke's complexity of “situation,” recognising human and non-human elements, discourses, debates, and issues, temporal and spatial. In analysing data for different map types (situational, social worlds and arenas, positional), ChatGPT-4 “understands” their different analytical purposes, recognising different levels of abstraction and theoretical structuring. The research highlighted the challenges for generative AI in translating complex theoretical frameworks into situational maps and visual representations and underlined the importance of effective prompting strategies. Also, the study identified several roles for generative AI in qualitative research, including co-analyst, consultant and trainer, highlighting the central role of human researchers in decision making and interpretation.
Keywords
AI- enhanced qualitative analysis, ChatGPT-4, computer-assisted qualitative data analysis, GenAI, situational analysis, situational maps, social worlds & arenas maps, TED Talks
Acknowledgements
The publication is a part of the project "Strengthening the R&D activities of the Vytautas Kavolis Transdisciplinary Institute for Social Sciences and Humanities (SOCMTEP).” The project is funded by the Research Council of Lithuania and the Ministry of Education, Science and Sport of the Republic of Lithuania, Contract No S-A-UEI-23-13 (2023-12-27).
Publication Date
10-20-2024
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.
DOI
10.46743/2160-3715/2024.7652
Recommended APA Citation
Mazeikiene, N., & Kasperiuniene, J. (2024). AI-enhanced qualitative research: Insights from Adele Clarke’s situational analysis of TED Talks. The Qualitative Report, 29(9), 2502-2526. https://doi.org/10.46743/2160-3715/2024.7652
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