Where We’re At, What We Must Know, and Where We Can Go: A Systematic Review of Research about Writing and Artificial Intelligence

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Authors: Christopher Eaton, Isabella Belmonte, Talla Enaya, Sarah Flood, Zainab Khalil, Anthony Makwanda, Mian Muhammad Ahmed Shah, Alexia Toma, Tiffany Wang, Connor Yu
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Abstract

This paper uses a systematic analysis to develop a thematic map of scholarship on AI, writing, and writing pedagogies. The project, developed between a university instructor and nine undergraduate students, had two central aims. The first was to synthesize the early research conversations on AI in writing contexts. The second was to identify gaps that will point to important next steps as the scholarly record on AI and writing develops. The paper presents five prominent themes: AI literacy, evaluating AI outputs, rhetoric in Human-AI interactions, AI and bias, and academic integrity. Conversations on AI literacy and academic integrity represent conceptual level discussions around AI and writing. The conversations around evaluation, rhetoric, and bias align more with AI writing practices and how these practices affect teaching and learning. Together, they provide a useful snapshot of scholarship and inform future work in a rapidly developing research conversation.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Computational and Text Analysis Methods Teaching and Learning Programming

Publication details

Journal / source
Discourse and Writing/Rédactologie
Volume
35
Pages
89–113
Publication date
6 January 2026
Language
EN