AI-POWERED FEEDBACK SYSTEMS FOR WRITING: A REVIEW OF AUTOMATED WRITING EVALUATION (AWE) TOOLS IN ELT

Authors

  • Etna Gres Universitas Tanjungpura
  • Eusabinus Bunau Universitas Tanjungpura

DOI:

https://doi.org/10.26418/jefle.v6i1.93952

Abstract

This systematic literature review examines the role of AI-powered feedback systems in enhancing writing skills within the context of English Language Teaching (ELT). Automated Writing Evaluation (AWE) tools have gained significant attention for their ability to provide instant, personalized feedback, which helps learners improve their writing skills by focusing on grammar, coherence, vocabulary, and overall text structure. This review analyzes 15 empirical studies published between 2019 and 2024, focusing on the effectiveness of AWE tools in ELT classrooms. Key findings indicate that AWE systems, such as Grammarly, Criterion, and WriteToLearn, contribute to significant improvements in learners"™ writing accuracy and fluency. However, challenges such as over-reliance on AI feedback and limited adaptability to higher-order thinking skills (e.g., critical analysis, creativity) remain prevalent. Furthermore, teachers play a crucial role in balancing AI feedback with personalized instruction to meet individual learner needs. This review highlights the potential of AWE tools in ELT but emphasizes the need for further research to refine these systems and address current limitations. The findings provide valuable insights for educators and researchers seeking to integrate AI-driven feedback systems in writing instruction.

Published

2025-07-31

Issue

Vol. 6 No. 1 (2025): July 2025

Section

Articles

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