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Leveraging generative AI for enhancing university-level English writing: comparative insights on automated feedback and student engagement

Research output: Contribution to journalReview articlepeer-review

22 Citations (Scopus)
228 Downloads (Pure)

Abstract

This study explores the impact of generative AI-based feedback, specifically utilizing ChatGPT, on the essay-writing proficiency and revision outcomes of university students in Hong Kong. A randomized controlled trial was conducted, where one group received AI-generated feedback while the control group received traditional feedback. The study investigates both the quantitative improvements in essay revisions and the qualitative aspects of student engagement, motivation, and emotional response to AI feedback. Results indicate that students who received AI feedback demonstrated statistically significant improvements in their writing quality and reported higher levels of motivation and engagement during the revision process. Additionally, thematic analysis from student interviews revealed mixed emotional responses, though many participants highlighted the usefulness of the AI in providing targeted, actionable feedback. This research contributes to the growing body of evidence supporting the integration of AI tools in higher education for enhancing student learning outcomes and reducing instructor workload.
Original languageEnglish
Article number2440182
Number of pages22
JournalCogent Education
Volume12
Issue number1
Publication statusPublished - 20 Dec 2024
EventAECT International Convention - Kansas City, Missouri, United States
Duration: 19 Oct 202423 Oct 2024
https://convention.aect.org/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education

Keywords

  • Generative AI
  • Automated feedback
  • Language learning outcomes
  • Student engagement
  • Writing proficiency
  • Higher Education
  • Language Teaching & Learning
  • automated feedback
  • writing proficiency
  • student engagement
  • language learning outcomes
  • Information Technology

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