TY - JOUR

T1 - Leveraging generative AI for enhancing university-level English writing

T2 - comparative insights on automated feedback and student engagement

AU - Chan, Sumie

AU - Lo, Noble

AU - Wong, Alan

PY - 2024/12/20

Y1 - 2024/12/20

N2 - 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.

AB - 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.

U2 - 10.1080/2331186x.2024.2440182

DO - 10.1080/2331186x.2024.2440182

M3 - Review article

VL - 12

JO - Cogent Education

JF - Cogent Education

SN - 2331-186X

IS - 1

M1 - 2440182

ER -