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Article published In: Generative Artificial Intelligence (GenAI) and Writing for Scholarly Publication
Edited by A. Mehdi Riazi
[Journal of English for Research Publication Purposes 6:2] 2025
► pp. 340–369

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Dialogic triad

Balancing human-AI collaboration in academic writing for scholarly publication

 | Education University of Hong Kong
 | Education University of Hong Kong
Published online: 12 March 2026
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https://doi.org/10.1075/jerpp.00038.cao
Abstract
This article introduces the “dialogic triad,” a model that redefines human-AI collaboration in scholarly writing by integrating relational agency and Bakhtinian dialogism. Through a case study involving two scholars and multiple GenAI systems, we demonstrate how AI serves as an active co-creator, provoking critical reflection and epistemic innovation. The study highlights moments of tension, where AI outputs conflict with human expertise, and synergy, where AI’s generative potential catalyzes theoretical breakthroughs. Crucially, our findings emphasize that human oversight remains central to ensuring accuracy, ethical accountability, and epistemic depth in AI-assisted scholarship. The model advocates for iterative, transparent collaboration that leverages AI’s potential while preserving scholarly rigor. Practical strategies, including iterative prompting, staged engagement and dialogic trace documentation, emphasize the need for human authority in framing arguments and validating AI outputs. Ultimately, this work positions human expertise as the essential anchor for meaningful, ethical, and innovative academic co-creation.
Article outline
  • Introduction: Transformations, challenges, and research gap in GenAI‑assisted scholarly writing
  • Theoretical framework
    • Relational agency in human-AI interaction
    • Dialogism
  • Case study: Co-creating a theoretical framework with AI
    • Research context
    • Writing as a collaborative, genre-based process
    • The dialogic triad
    • Research questions
    • Methodological approach and data source
    • Research process and data analysis
    • Analytical approach
    • Analysis
    • Tension in human-AI collaboration
      • Event description
        • Generative exploration (Right Axis: Scholar 2 ↔ AI)
        • Critical interrogation (Left axis: Scholar 1 ↔ AI)
        • Negotiation and consensus (Bottom axis: Scholar 1 ↔ Scholar 2)
      • Analysis
        • Heteroglossia
        • Answerability
        • Relational agency
        • Synergy in human-AI collaboration
      • Event description
        • Theoretical integration (Bottom axis: Scholar 1 ↔ Scholar 2)
        • Conceptual refinement (Left axis: Scholar 1 ↔ AI)
        • Theoretical expansion (Bottom axis: Scholar 1 ↔ Scholar 2)
        • Exemplification and contextualization (Left axis: Scholar 2 ↔ AI)
      • Analysis
        • Heteroglossia
        • Answerability
        • Relational agency
  • Discussion
    • Theoretical implications
    • Practical recommendations
    • Pedagogical implications for ERPP
    • Institutional and ethical considerations
    • Limitations and future research
  • Conclusion
  • References
References (47)
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