Qualitative researchers can benefit from using generative artificial intelligence (GenAI), such as different versions of ChatGPT—GPT-3.5 or GPT-4, Google Bard—now renamed as a Gemini, and Bing Chat—now renamed as a Copilot, in their studies. The scientific community has used artificial intelligence (AI) tools in various ways. However, using GenAI has generated concerns regarding potential research unreliability, bias, and unethical outcomes in GenAI-generated research results. Considering these concerns, the purpose of this commentary is to review the current use of GenAI in qualitative research, including its strengths, limitations, and ethical dilemmas from the perspective of critical appraisal from South Asia, Nepal. I explore the controversy surrounding the proper acknowledgment of GenAI or AI use in qualitative studies and how GenAI can support or challenge qualitative studies. First, I discuss what qualitative researchers need to know about GenAI in their research. Second, I examine how GenAI can be a valuable tool in qualitative research as a co-author, a conversational platform, and a research assistant for enhancing and hindering qualitative studies. Third, I address the ethical issues of using GenAI in qualitative studies. Fourth, I share my perspectives on the future of GenAI in qualitative research. I would like to recognize and record the utilization of GenAI and/or AI alongside my cognitive and evaluative abilities in constructing this critical appraisal. I offer ethical guidance on when and how to appropriately recognize the use of GenAI in qualitative studies. Finally, I offer some remarks on the implications of using GenAI in qualitative studies


qualitative data analysis, GenAI, research methods, ethical issues, critical appraisal

Author Bio(s)

Niroj Dahal (https://orcid.org/0000-0001-7646-1186), works at Kathmandu University School of Education under the Department of STEAM Education. He also serves as an editorial member of TQR. His research interests include ICT in education, artificial intelligence (AI), generative artificial intelligence (GenAI), qualitative research—action research, participatory action research, appreciative inquiry, arts-based inquiry, autoethnography, narrative inquiry, case study, content analysis, critical ethnography, critical social theories inquiry, decolonizing methodologies, decolonizing autoethnography, thematic analysis, narrative analysis, and collaborative inquiry (among others), mathematics education, open, distance & e-learning, STEAM education, research and development, and ICT & e-Research. Mr. Dahal has been teaching graduate and undergraduate students for over the past two decades. He has also been continuously taking part and presenting his research and practices in more than four dozen national and international conferences, workshops, and seminars. He has published articles, research notes, commentary, editorials, book reviews, books, and book chapters in various national and international journals and publication presses in ICT, qualitative research, education in general and mathematics education, and STEAM education. He may be contacted by e-mail at niroj@kusoed.edu.np.


I express my sincere gratitude to the reviewer, editor, and senior editor—Alicia King, Martha Snyder, and Chip Turner—of TQR for their valuable feedback, insightful suggestions, and meticulous corrections throughout this commentary. Equally, I wish to acknowledge the use of ChatGPT—GPT-3.5 or GPT-4, Google Bard—now renamed as a Gemini, and Bing Chat—now renamed as a Copilot in this commentary. ChatGPT was used to brainstorm and structure the content. Google Bard was employed to distill the key themes from academic papers, while Bing Chat was used to refine the language and ensure a consistent flow and cohesion throughout the sentences and paragraphs. Thus, I wish to recognize and record the application of both GenAI and AI and my cognitive and evaluative abilities in the formulation of this commentary.

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