Google Gemini-assisted writing and lexical appropriateness in EFL Paragraph Writing: Evidence of stability across tasks - Pandu Prasodjo; Siusana Kweldju; Nur Mukminatien; Francisca Maria Ivone; Hilarius Raditya Priambada Purba (English Language Teaching Educational Journal, 2026)
This study examined the influence of Google Gemini, a generative artificial-intelligence (AI) tool, on the lexical appropriateness of Indonesian EFL students’ paragraph writing. Drawing on theories of lexical richness and appropriateness, the study employed an exploratory quasi-experimental design involving three writing conditions: a baseline task, an AI-assisted revision task, and a delayed post-test without AI support. Fourteen second-year English Language Teaching students (A2–B1 CEFR) participated in the study. Lexical appropriateness was measured using Type-Token Ratio (TTR) and Measure of Textual Lexical Diversity (MTLD), and the data were analyzed using repeated-measures ANOVA to examine differences across tasks. The results revealed no statistically significant differences in lexical diversity across the three conditions, suggesting that short-term interaction with Google Gemini did not lead to measurable improvement in lexical appropriateness. Qualitative observations further indicated that limited vocabulary depth and low metalinguistic awareness constrained students’ ability to evaluate and apply AI-generated lexical suggestions. These findings suggest that lexical appropriateness is reflective, and instruction-dependent process, and that AI tools such as Google Gemini function more as a potential scaffolding partner rather than autonomous enhancers of lexical development.