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While the use of automated writing evaluation software has received much attention in CALL literature, as Frankenberg-Garcia (2019) notes, empirical research on predictive text and intelligent writing assistants is lacking. Thus, this study addressed this gap in the literature by examining the impact of Grammarly, an intelligent writing assistant that incorporates predictive text technology, on the mobile writing quality of Japanese L2 English students. Specifically, the study explored if Grammarly had a significant effect on the grammatical accuracy, lexical richness, writing fluency, or syntactic complexity of L2 students' writing when compared to unassisted mobile writing. A total of 31 university EFL students participated in the 8-week study which utilized a counterbalanced design. Participants took part in weekly guided freewriting tasks under each writing condition (non-Grammarly and Grammarly) over the duration of the study. The descriptive statistics and results from t-tests showed that when students wrote with the assistance of Grammarly, they produced fewer grammatical errors and wrote with more lexical variation. These findings highlight the potential of predictive text and real-time corrective feedback as a way to support L2 writing, particularly among novice writers who may struggle to write effectively in the L2.

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