Assessing L2 Student Writing in the AI Era: A Systematic Review on Challenges and Best Practices
DOI:
https://doi.org/10.54855/ijte.26615Keywords:
AI tools, ESL students, writing assessment, academic integrityAbstract
This paper aims to provide a systematic review of the existing literature on the effects of AI on L2 (ESL/EFL) student writing and assessment. A comprehensive search was conducted through ScienceDirect, ERIC and Taylor & Francis Online, providing qualitative analysis of three major themes: the effects of AI on L2 writing, challenges in identifying AI-generated content, and practices for adapting writing assessment. PRISMA 2020 guidelines and the CASP checklist were used to select appropriate articles and assess validity, relevance and ethical issues. The review included 20 studies published between 2023 and 2025. The results show that AI offers numerous advantages, such as giving individualized feedback and support, improving writing quality and helpfully assisting the grading processes. However, issues related to academic integrity, originality and the difficulties in distinguishing between AI-created writing and student-written work have emerged. The paper proposes best practices for integrating AI into assessment frameworks in which academic integrity is still maintained while AI is utilized to improve learning outcomes.
References
Alexander, K., Savvidou, C., & Alexander, C. (2023). Who wrote this essay? Detecting AI-generated writing in second language education in higher education. Teaching English with Technology, 23(2), 25–43. https://doi.org/10.56297/BUKA4060/XHLD5365
Alharbi, W. (2023). AI in the foreign language classroom: A pedagogical overview of automated writing assistance tools. Education Research International, 2023(1), Article 4253331. https://doi.org/10.1155/2023/4253331
Bordalejo, B., Pafumi, D., Onuh, F., Khalid, A. K. M. I., Pearce, M. S., & O’Donnell, D. P. (2025). Scarlet cloak and the forest adventure: A preliminary study of the impact of AI on commonly used writing tools. International Journal of Educational Technology in Higher Education, 22(6), 1-25. https://doi.org/10.1186/s41239-025-00505-5
Bui, T. T. U., & Tong, T. V. A. (2025). The impact of AI writing tools on academic integrity: Unveiling English-majored students’ perceptions and practical solutions. AsiaCALL Online Journal, 16(1), 83–110. https://doi.org/10.54855/acoj.251615
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, Article 43. https://doi.org/10.1186/s41239-023-00411-8
Cong-Lem, N., Tran, T. N., & Nguyen, T. T. (2024). Academic integrity in the age of generative AI: perceptions and responses of Vietnamese EFL teachers. Teaching English with Technology, 24(1), 28-47. https://doi.org/10.56297/FSYB3031/MXNB7567
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
Crawford, J. A., Cowling, M., & Allen, K.-A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching and Learning Practice, 20(3), Article 02. https://doi.org/10.53761/1.20.3.02
Črček, N., & Patekar, J. (2023). Writing with AI: University students’ use of ChatGPT. Journal of Language and Education, 9(4), 128–138. https://doi.org/10.17323/jle.2023.17379
Dai, Y., Liu, A., & Lim, C. P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. Procedia CIRP, 33rd CIRP Design Conference. Elsevier, 119, 84-90 https://doi.org/10.1016/j.procir.2023.05.002
Fakir, S. A., Marnaoui, S., & Al Anqodi, H. A. (2024). Written assignments and generative artificial intelligence: Challenges and considerations for English education major students at A’Sharqiyah University, Oman. Arab World English Journal, 15(4), 22–38. https://doi.org/10.24093/awej/vol15no4.2
Fitria, T. N. (2022). Avoiding plagiarism of students' scientific writing by using the QuillBot paraphraser. ELSYA: Journal of English Language Studies, 4(3), 252–262. https://doi.org/10.31849/elsya.v4i3.9917
Fleckenstein, J., Meyer, J., Jansen, T., Keller, S. D., Köller, O., & Möller, J. (2024). Do teachers spot AI? Evaluating the detectability of AI-generated texts among student essays. Computers and Education: Artificial Intelligence, 6(5), 100209. https://doi.org/10.1016/j.caeai.2024.100209
Frye, B. L. (2023). Should using an AI text generator to produce academic writing be plagiarism? Fordham Intellectual Property, Media & Entertainment Law Journal, 33(4), 946. https://ir.lawnet.fordham.edu/iplj/vol33/iss4/5
Graham, S. S. (2023). Post-process but not post-writing: Large language models and a future for composition pedagogy. Composition Studies, 51(1), 162–168. https://files.eric.ed.gov/fulltext/EJ1390327.pdf
Ha, Y. N., & Ho, N. P. (2025). EFL postgraduate students’ perceptions on the use of Grammarly and peer feedback to improve their academic writing skills. International Journal of TESOL & Education, 5(1), 25-49. https://doi.org/10.54855/ijte.25512
Herbold, S., Hautli-Janisz, A., Heuer, U., Kikteva, Z., & Trautsch, A. (2023). A large-scale comparison of human-written versus ChatGPT-generated essays. Scientific Reports, 13, Article 18617. https://doi.org/10.1038/s41598-023-45644-9
Hong, W. C. H. (2023). The impact of ChatGPT on foreign language teaching and learning: Opportunities in education and research. Journal of Educational Technology and Innovation, 5(1), 37-45. https://doi.org/10.61414/jeti.v5i1.103
Hossain, Z., Çelik, Ö., & Hiniz, G. (2025). Exploring EFL students’ AI literacy in academic writing: Insights into familiarity, knowledge, and ethical perceptions. Journal of Theoretical Educational Science (Kuramsal Eğitimbilim Dergisi), 18(1), 157–181. https://hdl.handle.net/11630/12556
Ibrahim, K. (2023). Using AI-based detectors to control AI-assisted plagiarism in ESL writing: “The Terminator versus the machines.” Language Testing in Asia, 13(1), Article 46. https://doi.org/10.1186/s40468-023-00260-2
Johinke, R., Cummings, R., & Di Lauro, F. (2023). Reclaiming the technology of higher education for teaching digital writing in a post-pandemic world. Journal of University Teaching & Learning Practice, 20(2), Article 01. https://doi.org/10.53761/1.20.02.01
Kim, J., Yu, S., Detrick, R., & Li, N. (2024). Exploring students’ perspectives on generative AI-assisted academic writing. Education and Information Technologies, 30(1), 1265-1300. https://doi.org/10.1007/s10639-024-12878-7
Khalil, M., & Er, E. (2023). Will ChatGPT get you caught? Rethinking plagiarism detection. In P. Zaphiris & A. Ioannou (Eds.), Learning and collaboration technologies: HCII 2023 (Lecture Notes in Computer Science, 14040, 442–457). Springer. https://doi.org/10.1007/978-3-031-34411-4_32
Khampusaen, D. (2025). The impact of ChatGPT on academic writing skills and knowledge: An investigation of its use in argumentative essays. LEARN Journal: Language Education and Acquisition Research Network, 18(1), 963-988. https://doi.org/10.70730/PGCQ9242
Krashen, S. D. (1982). Principles and Practice in Second Language Acquisition. Pergamon Press.
Kurniati, E. Y., & Fithriani, R. (2022). Post-graduate students’ perceptions of Quillbot utilization in English academic writing class. Journal of English Language Teaching and Linguistics, 7(3), 437-451. https://doi.org/10.21462/jeltl.v7i3.852
Latifah, S., Muth'im, A., & Nasrullah, N. (2024). The use of QuillBot in academic writing. Journey: Journal of English Language and Pedagogy, 7(1), 110–121. https://doi.org/10.33503/journey.v7i1.872
Long, H. A., French, D. P., & Brooks, J. M. (2020). Optimising the value of the Critical Appraisal Skills Programme (CASP) tool for quality appraisal in qualitative evidence synthesis. Research Methods in Medicine & Health Science, 1(1), 31-42. https://research.manchester.ac.uk/en/publications/optimising-the-value-of-the-critical-appraisal-skills-programme-c/
Luo, J. (2024). A critical review of GenAI policies in higher education assessment: A call to reconsider the “originality” of students’ work. Assessment & Evaluation in Higher Education, 49(5), 651–664. https://doi.org/10.1080/02602938.2024.2309963
Mahapatra, S. (2024). Impact of ChatGPT on ESL students’ academic writing skills: A mixed methods intervention study. Smart Learning Environments, 11, Article 09. https://doi.org/10.1186/s40561-024-00295-9
Maphoto, K. B., Sevnarayan, K., Mohale, N. E., Suliman, Z., Ntsopi, T. J., & Mokoena, D. (2024). Advancing students’ academic excellence in distance education: Exploring the potential of generative AI integration to improve academic writing skills. Open Praxis, 16(2), 142–159. https://doi.org/10.55982/openpraxis.16.2.649
Marghany, M. M. (2023). Using artificial intelligence-based instruction to develop EFL higher education students’ essay writing skills. CDELT Occasional Papers in the Development of English Education, 82(1), 219-240. https://www.researchgate.net/publication/373432641_Using_artificial_intelligence-based_instruction_to_develop_EFL_higher_education_students'_essay_writing_skills
Marzuki, U., Widiati, U., Rusdin, D., Darwin, & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students' writing: EFL teachers' perspective. Cogent Education, 10(2), 2236469. https://doi.org/10.1080/2331186X.2023.2236469
Mizumoto, A., & Eguchi, M. (2023). Exploring the potential of using an AI language model for automated essay scoring. Research Methods in Applied Linguistics, 2, Article 100050. https://doi.org/10.1016/j.rmal.2023.100050
Mohammad, T., Alzubi, A. A. F., Nazim, M., & Khan, S. I. (2024). Evaluating the effectiveness of QuillBot in improving students' paraphrasing skills: Teachers’ voices. Journal of Theoretical and Applied Information Technology, 102(6), 2556–2565. https://jatit.org/volumes/Vol102No6/25Vol102No6.pdf
Moorhouse, B. L., Yeo, M., & Wan, Y. (2023). Generative AI tools and assessment: Guidelines of the world's top-ranking universities. Computers and Education Open, 5(2), 100151. https://doi.org/10.1016/j.caeo.2023.100151
Naz, I., & Robertson, R. (2024). Exploring the feasibility and efficacy of ChatGPT-3 for personalized feedback in teaching. European Journal of e-Learning, 22(2), 98-111. https://doi.org/10.34190/ejel.22.2.3345
Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. EURASIA Journal of Mathematics, Science and Technology Education, 19(8), Article em2307. https://doi.org/10.29333/ejmste/13428
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
Perkins, M., Hickerson, D., Roe, J., Postma, D., & McGaughran, J. (2023). Detection of GPT-4 generated text in higher education: Combining academic judgment and software to identify generative AI tool misuse. Journal of Academic Ethics, 22, 89-113. https://doi.org/10.1007/s10805-023-09492-6
Pham, M. T., & Cao, T. X. T. (2025). The Practice of ChatGPT in English Teaching and Learning in Vietnam: A Systematic Review. International Journal of TESOL & Education, 5(1), 50-70. https://doi.org/10.54855/ijte.25513
Pham, V. P. H., & Le, A. Q. (2024). ChatGPT in Language Learning: Perspectives from Vietnamese Students in Vietnam and the USA. International Journal of Language Instruction, 3(2), 59–72. https://doi.org/10.54855/ijli.24325
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1), 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
Smerdon, D. (2024). AI in essay-based assessment: Student adoption, usage, and performance. Computers and Education: Artificial Intelligence, 7, Article 100288. https://doi.org/10.1016/j.caeai.2024.100288
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 31-40. https://doi.org/10.37074/jalt.2023.6.1.17
Tate, T. P., Steiss, J., Bailey, D., Graham, S., Moon, Y., Ritchie, D., Tseng, W., & Warschauer, M. (2024). Can AI provide useful holistic essay scoring? Computers and Education: Artificial Intelligence, 7, Article 100255. https://doi.org/10.1016/j.caeai.2024.100255
Thanh, B. N., Vo, D. T. H., Nhat, M. N., Pham, T. T. T., Trung, H. T., & Xuan, S. H. (2023). Race with the machines: Assessing the capability of generative AI in solving authentic assessments. Australasian Journal of Educational Technology, 39(5), 59–81. https://doi.org/10.14742/ajet.8902
Thangthong, P., Phiromsombut, J., & Imsa-ard, P. (2024). Navigating AI writing assistance tools: Unveiling the insights of Thai EFL learners. THAITESOL Journal, 37(1), 111–131. https://so05.tci-thaijo.org/index.php/thaitesoljournal/article/view/270168
Waltzer, T., Pilegard, C., & Heyman, G. D. (2024). Can you spot the bot? Identifying AI-generated writing in college essays. International Journal for Educational Integrity, 20(2024), Article 11. https://doi.org/10.1007/s40979-024-00158-3
Westfall, C. (2023, January 28). Educators battle plagiarism as 89% of students admit to using OpenAI’s ChatGPT for homework. Forbes. https://www.forbes.com/sites/chriswestfall/2023/01/28/educators-battle-plagiarism-as-89-of-students-admit-to-using-open-ais-chatgpt-for-homework/
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Dau Thi Thanh Luy, Lam Thuy Trang

This work is licensed under a Creative Commons Attribution 4.0 International License.
The copyright of all articles published in the International Journal of TESOL & Education (ijte) remains with the Authors, i.e. Authors retain full ownership of their article. Permitted third-party reuse of the open access articles is defined by the applicable Creative Commons (CC) end-user license which is accepted by the Authors upon submission of their paper. All articles in the ijte are published under the CC BY-NC 4.0 license, meaning that end users can freely share an article (i.e. copy and redistribute the material in any medium or format) and adapt it (i.e. remix, transform and build upon the material) on the condition that proper attribution is given (i.e. appropriate credit, a link to the applicable license and an indication if any changes were made; all in such a way that does not suggest that the licensor endorses the user or the use) and the material is only used for non-commercial purposes.
Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository, in a journal or publish it in a book), with an acknowledgment of its initial publication in this journal.









