Role Play: Conversational Roles as a Framework for Reflexive Practice in AI-Assisted Qualitative Research

Luke Thominet Florida International University ; Jacqueline Amorim Florida International University ; Kristine Acosta Florida International University ; Vanessa K. Sohan

Abstract

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.

Journal
Journal of Technical Writing and Communication
Published
2024-10-01
DOI
10.1177/00472816241260044
Open Access
Closed
Topics

Citation Context

Cited by in this index (1)

  1. Journal of Technical Writing and Communication

Cites in this index (6)

  1. Journal of Technical Writing and Communication
  2. Technical Communication Quarterly
  3. Technical Communication Quarterly
  4. Journal of Technical Writing and Communication
  5. Journal of Technical Writing and Communication
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  1. College Composition and Communication
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