Enhancing disciplinary voice through feedback-seeking in AI-assisted doctoral writing for publication

Abstract Artificial Intelligence (AI) tools are reshaping academic writing, yet their impact on disciplinary voice in writing for publication remains underexplored. This study examines the integration of AI in a writing-for-publication course, using a pedagogical framework that emphasizes human-human interaction to develop feedback-seeking strategies. Fifty-five linguistically and disciplinarily diverse doctoral students engaged in structured activities to explore how AI can support and challenge their disciplinary voices. Through textual analysis of students’ reflections and interactions with AI, findings reveal that while these tools can enhance certain aspects of writing, their effective use requires critical engagement. Feedback-seeking emerged as a key skill, shaping how writers negotiate AI’s role in their writing process—determining when input from AI tools, which operate outside the students’ disciplinary boundaries, strengthens their writing and when disciplinary expertise remains essential. The study highlights the interplay between AI tools, feedback-seeking, and disciplinary voice, offering insights into their pedagogical potential in academic writing and writing for publication.

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Institutions

Publication Details

Journal
Applied Linguistics
Published
2025-05-03
DOI
https://doi.org/10.1093/applin/amaf022
Citations
9
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
5.89
Controls
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article

Enhancing disciplinary voice through feedback-seeking in AI-assisted doctoral writing for publication

Baraa Khuder
9 citations
Applied Linguistics
Artificial Intelligence in Healthcare and Education
5.89
article

Enhancing disciplinary voice through feedback-seeking in AI-assisted doctoral writing for publication

Baraa Khuder
article en
9 citations

Abstract

Abstract Artificial Intelligence (AI) tools are reshaping academic writing, yet their impact on disciplinary voice in writing for publication remains underexplored. This study examines the integration of AI in a writing-for-publication course, using a pedagogical framework that emphasizes human-human interaction to develop feedback-seeking strategies. Fifty-five linguistically and disciplinarily diverse doctoral students engaged in structured activities to explore how AI can support and challenge their disciplinary voices. Through textual analysis of students’ reflections and interactions with AI, findings reveal that while these tools can enhance certain aspects of writing, their effective use requires critical engagement. Feedback-seeking emerged as a key skill, shaping how writers negotiate AI’s role in their writing process—determining when input from AI tools, which operate outside the students’ disciplinary boundaries, strengthens their writing and when disciplinary expertise remains essential. The study highlights the interplay between AI tools, feedback-seeking, and disciplinary voice, offering insights into their pedagogical potential in academic writing and writing for publication.

Applied Linguistics
Chalmers University of Technology (SE)
Openalex Percentile: Top 4%
Artificial Intelligence in Healthcare and Education
5.89
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