AI-Assisted Writing: Exploring Academic Writing Strategies of Graduate Students across Disciplines through Activity Theory
- Jin Chen
- Zhuoyan Wang
- Xinyu Zhou
Abstract
With the growing integration of artificial intelligence (AI) tools into academic writing, especially in second language (L2) contexts, there is a pressing need to understand how disciplinary background and AI-mediated environments shape students’ writing strategies. Grounded in Activity Theory, this study investigates the academic writing strategies of Chinese graduate students across disciplines when composing English academic papers with AI assistance. Through semi-structured interviews, the study identifies distinct disciplinary preferences, particularly, arts students emphasize logical coherence and rhetorical organization, while science students prioritize innovation, clarity, and technical accuracy. These differences reflect how disciplinary norms influence strategic behaviors in AI-supported writing contexts. The findings also reveal a blend of shared and discipline-specific strategies shaped by mediational tools, institutional rules, and community expectations. By framing AI as a mediating artifact within writing activity systems, this study highlights the complex interplay between technology, discipline, and strategy use. The results offer valuable insights for designing discipline-sensitive, AI-aware academic writing instruction in higher education.
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- DOI:10.5539/hes.v15n4p243
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