Research methods and generative artificial intelligence in applied linguistics

Benjamin Luke Moorhouse, Sal Consoli, Samantha M. Curle

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Abstract

Since the release of ChatGPT, there has been an explosion of interest in Generative Artificial Intelligence (GenAI) and a desire to understand how these tools can be utilised in almost every domain of human activity. Never before in human history have we had a tool that could simulate so many human capabilities. Yet, just as with humans, these tools have been found to have substantial limitations. These limitations have led us to question the roles they can play in high-stakes tasks, such as research. At the same time, they have challenged our current conventions and norms of authorship, transparency, and accountability, thus forcing us to consider:
•What tasks should be left to humans exclusively?
•What tasks can AI do alone?
•What tasks can/should AI and humans do together?
For some scholars, clear red lines have been drawn. For example, 416 experienced qualitative researchers from 38 countries wrote a commentary rejecting the use of GenAI for reflexive qualitative research (Jowsey, Braun, Clark et al., 2025). They provided three legitimate reasons for their rejection: (1) GenAI as simulated intelligence is incapable of meaning-making; (2) Qualitative research should remain a distinctly human practice; (3) the established harms of GenAI, especially to the environment and workers in the Global South. Nguyen and Welch (2025) have similar concerns and arguments against the use of GenAI in qualitative research. For other scholars, GenAI offers significant potential to reshape “the academic research lifecycle—from ideation and literature discovery to hypothesis formation, methodological planning, and data acquisition” (Haber et al., 2025, p. 27). Meanwhile, other scholars, including us, take a pragmatic stance, trying to balance the potential of these tools with the explicit threats they pose to our epistemologies, methodological rigor, integrity, and ethics (Roe, 2025; Moorhouse, Nejadghanbar & Yeo, 2025; Moorhouse, Consoli & Curle, 2025).
Original languageEnglish
Article number100295
JournalResearch Methods in Applied Linguistics
Volume5
Issue number1
Early online date9 Jan 2026
DOIs
Publication statusE-pub ahead of print - 9 Jan 2026

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