The Impact of Next-Generation AI Chatbots on Academic Writing Skills and Academic Integrity Among English-Majored Students at HUIT: An Experimental Study
DOI:
https://doi.org/10.60087/ijls.v3.n2.004Keywords:
AI chatbots, Academic writing performance, ANCOVA, Academic integrity, English as a foreign language, Higher educationAbstract
This study examines the impact of next-generation AI chatbots on the academic writing performance of English-majored students at Ho Chi Minh City University of Industry and Trade (HUIT), situating the findings within broader questions of academic integrity raised by AI-assisted writing. Using a quasi-experimental pretest-posttest design, 287 students completed academic writing tasks before and after an AI-assisted writing intervention; 150 students received AI assistance during the intervention while 137 completed the task without AI support. Writing performance was scored using a five-dimension analytic rubric (organization, language accuracy, syntactic complexity, coherence and cohesion, and critical thinking). Results showed a statistically significant improvement from pretest (M = 6.64) to posttest (M = 8.07), t(286) = -51.16, p < .001. Students who received AI assistance achieved significantly higher posttest scores (M = 8.33) than those who did not (M = 7.79), t(285) = -5.46, p < .001. After controlling for pretest scores, ANCOVA confirmed a large effect of AI assistance on posttest performance, F(1, 284) = 218.70, p < .001, partial η² = .435. These findings indicate that AI-assisted writing produced substantial, statistically robust gains in students' writing performance beyond what pre-existing ability could explain. The discussion situates these performance gains within ongoing debates about authorship, originality, and academic integrity in AI-assisted academic work, arguing that improvements in measurable writing quality do not by themselves resolve, and may in fact sharpen, questions about what should count as a student's own intellectual contribution. Implications for students, lecturers, and institutional assessment policy are discussed.
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Copyright (c) 2026 Nguyen Minh Nhat, Nguyen Thao My, Tran Thi Thuan, Le Thi Quynh Nhu (Author)
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Copyright: © The Author(s), 2026. Published by IJLS. This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.
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