DOI: 10.11648/j.ijll.20261405.12 ISSN: 2330-0221

Generative AI-Mediated Feedback and L2 Grammatical-Lexical Development: A Scoping Review of Longitudinal Research Gaps

Le An, Nguyen Hong
Show PDF Cite
The rapid adoption of generative artificial intelligence (AI) tools such as ChatGPT in second language (L2) writing instruction has produced a fast-growing body of research on AI-generated written corrective feedback. Two recent scoping reviews have mapped this literature broadly, focusing on feedback quality, learner uptake and pedagogical integration. However, neither review specifically examined how this literature treats grammatical and lexical development as distinct, measurable constructs, nor how it addresses the moderating role of learner proficiency over time. This scoping review synthesizes 30 empirical and methodological sources, identified through a targeted, PRISMA-ScR-informed search of Google Scholar, Scopus-indexed journal content and ERIC, together with citation networks, to map the state of longitudinal research on generative-AI-mediated feedback and grammatical-lexical development in L2/EFL writing. The review finds that most intervention studies remain limited to a single semester or shorter, that grammatical accuracy and lexical development are rarely measured as separate, co-tracked outcomes and that only a small number of very recent studies (2025-2026) have applied longitudinal growth-modelling techniques, none of which disentangle grammar from vocabulary or systematically test proficiency level as a moderator of developmental trajectories. No such study appears to have been conducted in the Vietnamese EFL context, based on the sources identified in this review. The review proposes a research agenda for longitudinal, multi-proficiency-level, construct-differentiated research on generative-AI-mediated feedback and outlines implications for instructional design and future primary research.

More from our Archive