What Does Automated Feedback Address, and Does It Work? An Investigation of Cambridge Write & Improve in EFL Writing Instruction

Abstract

This study investigates the scope and impact of automated feedback provided by Cambridge Write & Improve (W&I) on English as a Foreign Language (EFL) learners' writing skills. Given the fact that education in the last decades has faced rapid changing landscape due to the growth of    technological innovations and the integration of Artificial Intelligence (AI), there is an urgent need to determine its impact on language learning outcomes. Previous studies focused on examining the overall impact of automated feedback on writing in general, but a few of them explored the functionalities that these tools provide during the revision process and how they successfully contribute to the overall writing process; hence this piece of research attempts to fill this gap. This mixed-methods study(N=28) revealed that the automated feedback provided by W&I is more concerned with accuracy including grammar, usage, and mechanics rather than higher-order concerns. Further analysis confirmed these results and indicated that learners demonstrated significant improvements across all three domains between first and final drafts, with particularly strong gains in mechanical accuracy. Such results serve as a trigger for decision-makers, including curriculum designers, to properly integrate automated feedback in education and combine it with instructor’s feedback to respond to all students’ needs in the writing process.