The Use of Artificial Intelligence Tools in English Academic Writing among University Students: A Scoping Review

Abstract

As artificial intelligence (AI) use in English academic writing instruction has increased, this scoping review reviews empirical studies in higher education. However, the studies differ in theory use and teaching practice. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) protocol and the Population-Concept-Context (PCC) framework, a systematic Web of Science (WoS) Core Collection search yielded 20 eligible peer-reviewed studies published post-2020. Most studies were carried out in English as a Foreign Language (EFL) contexts, aiming to improve writing performance and learner motivation via AI-assisted tools. Common platforms encompass automated writing assessment systems. Theoretical frameworks were frequently limited to self-efficacy and scaffolding, with scant consideration for cognitive load, sociocultural adaptation, or ethical governance. Methodologically, most studies relied on short-term experimental designs, lacking longitudinal or classroom-based rigor. Future research should employ mixed-methods and longitudinal designs, include diverse learner demographics, and prioritize teacher preparation and ethical AI literacy to guarantee sustainable and equitable implementation.

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