Discrepancies Between ChatGPT and Vietnamese EFL Teachers in Writing Assessment

Authors

DOI:

https://doi.org/10.54855/ijaile.26311

Keywords:

ChatGPT, Vietnamese EFL teacher, writing, discrepancy, rubric

Abstract

Artificial intelligence, particularly ChatGPT, strongly influences education, especially in modern EFL classrooms. However, a significant gap still exists in Vietnam regarding how ChatGPT’s writing assessments differ from those of EFL teachers. To address this gap, this study directly compares ChatGPT’s writing assessments with those of Vietnamese EFL teachers to identify key discrepancies. Twenty experienced teachers working at English centers and universities in Ho Chi Minh City participated in this quantitative research. ChatGPT and human raters used an analytic rubric adapted from a standardized rubric to assess the written works of twenty students. A paired-sample t-test was then employed to compare the scores of human raters and ChatGPT in assessing twenty students’ essays across the rubric criteria. The findings revealed a statistically significant difference between ChatGPT and Vietnamese EFL teachers in writing evaluations (p = .034), with ChatGPT (M = 16.08, SD = 3.29)  assigning a higher total score than human raters (M = 14.75, SD = 2.96). Particularly, ChatGPT tended to give higher scores than human raters across all criteria, including content, organization, vocabulary, and grammar, with the content criterion showing the greatest discrepancy.

Author Biographies

  • Ho Nhut Nam, Industrial University of Ho Chi Minh City

    Ho Nhut Nam completed a Bachelor's program in English Language at the Industrial University of Ho Chi Minh City, Vietnam, and is pursuing a master's degree at the same institution. He has many years of teaching young learners and adults. His research interests include the integration of AI into language education, second-language acquisition, and interdisciplinary studies of language and culture.

  • Tra Thi Cam Thu, Industrial University of Ho Chi Minh City

    Tra Thi Cam Thu is currently pursuing a master’s degree in English Language at the Industrial University of Ho Chi Minh City. She is an experienced English teacher who has worked with a wide range of students at a public school and at VUS. Her practical classroom experience has shaped her academic focus on developing effective strategies that enhance both student engagement and the language-learning process for EFL learners.

  • Pham Thi Quyen, Industrial University of Ho Chi Minh City

    Pham Thi Quyen is currently pursuing her master’s degree in English language at the Industrial University of Ho Chi Minh City, Vietnam. She is an officer at the Department of International Cooperation at a university in Ho Chi Minh City and has three years of experience in teaching English to young learners. Her interest in doing research is in English teaching and learning methodology.

  • Tran Phuong Thanh, Industrial University of Ho Chi Minh City

    Tran Phuong Thanh is currently pursuing an MA in English Language at the Industrial University of Ho Chi Minh City, Vietnam, building on her Bachelor of Arts in the same field. She has over three years of experience in teaching English communication courses to young learners and adults at private English centers. Her current academic and professional focus is on advancing teaching methodology and exploring the effective integration of AI into educational contexts.

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Published

04/29/2026

Issue

Vol. 3 No. 1 (2026): AI in Language Education

Section

Research Articles

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Copyright (c) 2026 Ho Nhut Nam, Tra Thi Cam Thu, Pham Thi Quyen, Tran Phuong Thanh (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Ho, N. N., Tra, T. C. T., Pham, T. Q., & Tran, P. T. (2026). Discrepancies Between ChatGPT and Vietnamese EFL Teachers in Writing Assessment. International Journal of AI in Language Education, 3(1), 1-16. https://doi.org/10.54855/ijaile.26311

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