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

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Title: Enhancing disciplinary voice through feedback-seeking in AI-assisted doctoral writing for publication
Authors: Khuder, Baraa, 1987
Source: Utformning och förbättring av en mikroläroplan om kritisk generativ AI för doktorander Applied Linguistics. In Press
Subject Terms: Artificial Intelligence (AI), feedback-seeking, writing for publication, disciplinary voice, academic writing
Description: 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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https://research.chalmers.se/publication/546436
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  Data: Enhancing disciplinary voice through feedback-seeking in AI-assisted doctoral writing for publication
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  Data: <searchLink fieldCode="AR" term="%22Khuder%2C+Baraa%22">Khuder, Baraa</searchLink>, 1987
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  Data: <i>Utformning och förbättring av en mikroläroplan om kritisk generativ AI för doktorander Applied Linguistics</i>. In Press
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence+%28AI%29%22">Artificial Intelligence (AI)</searchLink><br /><searchLink fieldCode="DE" term="%22feedback-seeking%22">feedback-seeking</searchLink><br /><searchLink fieldCode="DE" term="%22writing+for+publication%22">writing for publication</searchLink><br /><searchLink fieldCode="DE" term="%22disciplinary+voice%22">disciplinary voice</searchLink><br /><searchLink fieldCode="DE" term="%22academic+writing%22">academic writing</searchLink>
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  Data: 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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      – SubjectFull: feedback-seeking
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              M: 01
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              Y: 2025
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            – TitleFull: Utformning och förbättring av en mikroläroplan om kritisk generativ AI för doktorander Applied Linguistics
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