Role Play: Conversational Roles as a Framework for Reflexive Practice in AI-Assisted Qualitative Research
Previous literature has shown that generative artificial intelligence (GAI) software, including large language model (LLM) chatbots, might contribute to qualitative research studies. However, there is still a need to examine the relationships between researchers, GAI technologies, data, and findings...
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Published in | Journal of technical writing and communication Vol. 54; no. 4; pp. 396 - 418 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Los Angeles, CA
SAGE Publications
01.10.2024
Sage Publications Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | Previous literature has shown that generative artificial intelligence (GAI) software, including large language model (LLM) chatbots, might contribute to qualitative research studies. However, there is still a need to examine the relationships between researchers, GAI technologies, data, and findings. To address this need, our team conducted a thematic analysis of our reflexive journals from an LLM chatbot-assisted research project. We identified four roles that researchers adopted: managers closely monitored the LLM's work, teachers instructed the LLM on theories and methods, colleagues openly discussed the data with the LLM, and advocates worked with the LLM to improve user experiences. Planning for and playing with multiple roles also helped to enrich the research process. This study underscores the potential for using conversational roles as a framework to support reflexivity when working with GAI technologies on qualitative research. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0047-2816 1541-3780 |
DOI: | 10.1177/00472816241260044 |