Exploring AI-Powered Writing Assistants’ Impact on the Academic Performance: A Case of a South African University
Keywords:
academic performance; AI-PWA; higher education; postgraduate students; technology adoptionAbstract
Artificial Intelligence (AI) technologies are progressively changing teaching and learning methods in higher education, especially regarding academic writing. Postgraduate students now commonly utilise AI-powered writing assistants (AI-PWA) to aid with tasks such as editing, paraphrasing, correcting grammar, and enhancing clarity in their written assignments. This study aimed to investigate the impacts of AI-PWA writing tools on the academic achievement of postgraduate students at a South African higher education institute. A sequential explanatory mixed-methods approach was utilised, integrating quantitative surveys with a sample size of 100 respondents and qualitative interviews with the size of 25 participants and focus group discussion to offer both statistical data and a richer understanding of students' experiences. Quantitative data were examined using descriptive statistics such as frequency distributions and percentages, whereas qualitative data were assessed thematically to uncover significant patterns in student perceptions. The results indicated that regular use of AI-PWA is positively associated with enhanced academic writing performance, particularly clarity, coherence, and the overall quality of written assignments. Students who speak multiple languages also reported that these resources helped them overcome language barriers and boosted their confidence in academic writing. Nonetheless, obstacles such as ethical issues, restricted access to high-quality tools, and a lack of adequate institutional support were also noted. The study suggests that higher education institutions should create explicit policies, training initiatives, and support systems to guarantee the responsible and effective implementation of AI-based writing aids in postgraduate education.
https://doi.org/10.26803/ijlter.25.6.50
References
Alharbi, W. (2023). AI in the foreign language classroom: A pedagogical overview of automated writing assistance tools. Education Research International, 1–15. https://doi.org/10.1155/2023/4253331
Arakpogun, E. O., Elsahn, Z., Olan, F., & Elsahn, F. (2021). Artificial intelligence in Africa: Challenges and opportunities. The fourth industrial revolution: Implementation of artificial intelligence for growing business success, 375-388. https://doi.org/10.1007/978-3-030-62796-6_22
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21) (pp. 610–623). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445922
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Brown, C., & Czerniewicz, L. (2010). Debunking the ‘digital native’: Beyond digital apartheid, towards digital democracy. Journal of Computer Assisted Learning, 26(5), 357–369. https://doi.org/10.1111/j.1365-2729.2010.00369.x
Chanpradit, T. (2025). Generative artificial intelligence in academic writing in higher education: A systematic review. Edelweiss Applied Science and Technology, 9(4), 889-906. https://doi.org/10.55214/25768484.v9i4.6128
Council on Higher Education (CHE). (2016). VitalStats: Public higher education 2016. Council on Higher Education.
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. Advance online publication. https://doi.org/10.1080/14703297.2023.2190148
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approach (5th ed.). SAGE.
Creswell, J. W., & Plano Clark, V. L. (2023). Revisiting mixed methods research designs twenty years later. In C. N. Poth (Ed.), The SAGE handbook of mixed methods research design (pp. 21–36). SAGE Publications.
Curado Fuentes, A. (2025). A qualitative approach to EFL postgraduates’ GenAI-assisted research writing within social sciences. Education Sciences, 15(11), 1521. https://doi.org/10.3390/educsci15111521
Curry, N. (2023). How should digital tools for writing be evaluated? Reflections from digital pedagogies and applied linguistics. Journal of Academic Writing, 13(1), 53–58. https://doi.org/10.18552/joaw.v13i1.970
Czerniewicz, L., Agherdien, N., Badenhorst, J., Belluigi, D., Chambers, T., Chili, M., ... & Wissing, G. (2020). A wake-up call: Equity, inequality and Covid-19 emergency remote teaching and learning. Postdigital science and education, 2(3), 946-967. https://doi.org/10.1007/s42438-020-00187-4
Daepp, M. I. G., & Counts, S. (2024). The emerging AI divide in the United States (arXiv Preprint No. arXiv:2404.11988). arXiv. https://doi.org/10.48550/arXiv.2404.11988
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Deep, P. D., & Chen, Y. (2025). The Role of AI in Academic Writing: Impacts on Writing Skills, Critical Thinking, and Integrity in Higher Education. Societies, 15(9), 247. https://doi.org/10.3390/soc15090247
Department of Higher Education and Training. (2019). National plan for post-school education and training (PSET) 2030. Government of South Africa.
Eaton, S. E. (2023). The Academic Integrity Technological Arms Race and its Impact on Learning, Teaching, and Assessment. Canadian Journal of Learning and Technology, 48(2). https://doi.org/10.21432/cjlt28388
Ellard, J. (2025). To what degree? The influence of low socioeconomic status on the lived experience of graduate development and career transition (Doctoral dissertation, University of Staffordshire)
Faisal, A. (2024). Interpreting qualitative data in tourism crisis research: An interdisciplinary perspective. In Handbook on crisis and disaster management in tourism (pp. 55-67). Edward Elgar Publishing.
Fan, N. (2023). Exploring the Effects of Automated Written Corrective Feedback on EFL Students' Writing Quality: A Mixed-Methods Study. SAGE Open, 13(2). https://doi.org/10.1177/21582440231181296
Fu, J. S., & Heng, L. (2025). Navigating the complexities of emergency remote teaching and learning: challenges, equity, and connectivity in a digital era. International Journal of Inclusive Education, 1-18. https://doi.org/10.1080/13603116.2025.2554245
Goswami, A., & Kamble, M. A. S. (2025). Beyond Chalk and Talk: English Pedagogy in the Digital Classroom. BFC Publications.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education promises and implications for teaching and learning. Center for Curriculum Redesign.
Hyland, K. (2019). Second language writing. Cambridge University Press.
Izah, S. C., Sylva, L., & Hait, M. (2023). Cronbach's alpha: A cornerstone in ensuring reliability and validity in environmental health assessment. ES Energy and Environment, 23, 1057. https://doi.org/10.30919/esee1057
Jeon, J., Wei, L., Tai, K. W. H., & Lee, S. (2025). Generative AI and its dilemmas: Exploring AI from a translanguaging perspective. Applied Linguistics, 46(4), 709–717. https://doi.org/10.1093/applin/amaf049
Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Choudhury, M. (2020). The state and fate of linguistic diversity and inclusion in the NLP world. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 6282–6293). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.560
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Khany, R., & Barzan, P. (2026). Leveraging AI-Powered Writing Assistants to Enhance L2 Writing Proficiency: A Mixed-Methods Study. AI and Tech in Behavioral and Social Sciences, 3(4), 1-14. https://doi.org/10.61838/kman.aitech.4287
Kujur, A. (2025). A comparative analysis of AI-generated and human-written text: Linguistic patterns, detection accuracy, and implications for modern communication (SSRN Scholarly Paper No. 5833302). Social Science Research Network. https://doi.org/10.2139/ssrn.5833302
Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3, 100101. https://doi.org/10.1016/j.caeai.2022.100101
Lea, M. R., & Street, B. V. (1998). Student writing in higher education: An academic literacies approach. Studies in higher education, 23(2), 157-172. https://doi.org/10.1080/03075079812331380364
Lee, J., Borchers, C., Alvero, A. J., Joachims, T., & Kizilcec, R. F. (2026). The digital divide in generative AI: Evidence from large language model use in college admissions essays (arXiv:2602.17791). arXiv. https://arxiv.org/abs/2602.17791
Levy, B. (2009). Stereotype embodiment: A psychosocial approach to aging. Current directions in psychological science, 18(6), 332-336. https://doi.org/10.1111/j.1467-8721.2009.01662.x
Li, Y., Zhang, Y., Timofte, R., Van Gool, L., Yu, L., Li, Y., ... & Wang, X. (2023). NTIRE 2023 challenge on efficient super-resolution: Methods and results. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 1922-1960). https://doi.org/10.1109/CVPRW59228.2023.00189
Lim, J., & Polio, C. (2020). Multimodal assignments in higher education: Implications for multimodal writing tasks for L2 writers. Journal of Second Language Writing, 47, 100713. https://doi.org/10.1016/j.jslw.2020.100713
Liu, M., & Yu, D. (2023). Towards intelligent E-learning systems. Education and Information Technologies, 28(7), 7845-7876. https://doi.org/10.1007/s10639-022-11479-6
Liu, M., Zhang, L. J. & Biebricher, C. (2024). Investigating students' cognitive processes in generative AI-assisted digital multimodal composing and traditional writing. Computers & Education, 211, 104977. https://doi.org/10.1016/j.compedu.2023.104977
Mahapatra, S. (2024). Impact of ChatGPT on ESL students’ academic writing skills: A mixed methods intervention study. Smart Learning Environments, 11(1), Article 9. https://doi.org/10.1186/s40561-024-00295-9
Mhlanga, D. (2023). ChatGPT in education: Exploring opportunities for emerging economies to improve education with ChatGPT. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4355758
Mhlanga, D. (2023). Open AI in education: The responsible and ethical use of ChatGPT towards lifelong learning (SSRN Scholarly Paper No. 4354422). Social Science Research Network. https://doi.org/10.2139/ssrn.4354422
Mhlanga, D. (2024). Responsible deployment of technology: Exploring ChatGPT’s current and prospective impact on educational paradigms. In M. Dzingirai (Ed.), Responsible business and sustainable development: The use of data and metrics in the Global South (pp. 10–29). Taylor & Francis. https://doi.org/10.4324/9781032712246-3
Mollick, E., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. arXiv. https://doi.org/10.48550/arXiv.2306.10052
Özer, M., Tanberkan, H., & Perc, M. (2025). Artificial Intelligence Threatens Critical Thinking in Education Systems. Yüksekö?retim Ve Bilim Dergisi, 15(2), 157-164. https://doi.org/10.5961/higheredusci.1747885
Paxton, M., & Frith, V. (2014). Implications of academic literacies research for knowledge making and curriculum design. Higher Education, 67(2), 171-182. https://doi.org/10.1007/s10734-013-9675-z
Pearson, Y., & Borenstein, J. (2021). The impact of robot companions on the moral development of children. In Engineering and Philosophy: Reimagining Technology and Social Progress (pp. 237-248). Cham: Springer International Publishing.
Perkins, M., & Roe, J. (2024). Academic publisher guidelines on AI usage: A ChatGPT-supported thematic analysis. F1000Research, 12, 1398. https://doi.org/10.12688/f1000research.142411.2
Qiang, X. (2024). Zone of proximal development. In Z. Kan (Ed.), The ECPH encyclopedia of psychology (pp. 1642–1643). Springer. https://doi.org/10.1007/978-981-97-7874-4_398
Ranalli, J. (2018). Automated written corrective feedback: How well can students make use of it? Computer Assisted Language Learning, 31(7), 653–674. https://doi.org/10.1080/09588221.2018.1428994
Resebotsa, H. M. (2025). Multilingualism in Sepedi Home Language essay writing in grade 11 classroom at Dimamo Circuit, Capricorn South District, in Limpopo Province, South Africa (Unpublished Doctoral dissertation, University of Limpopo).
Sar?ca, T., & Deneme Genço?lu, S. (2025). EFL students’ perceptions of AI-assisted writing tools: A systematic narrative hybrid review. The Literacy Trek, 11(1), 1-31. https://doi.org/10.47216/literacytrek.1669804
Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.
Selwyn, N. (2016). Is technology good for education? Polity Press.
Selwyn, N. (2004). Reconsidering political and popular understandings of the digital divide. New Media & Society, 6(3), 341–362. https://doi.org/10.1177/1461444804042519
Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(1), 54. https://doi.org/10.1186/s41239-021-00292-9
Sithole, M., & Moyo, I. (2024). Urban informality and overcoming marginality: Female Street traders and the COVID-19 pandemic in uMhlathuze City, South Africa. African Journal of Gender, Society & Development, 13(4), 443.
Skulmowski, A. (2024). Placebo or assistant? Generative AI between externalization and anthropomorphizing. Educational Psychology Review, 36, 58. https://doi.org/10.1007/s10648-024-09894-x
Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in psychology, 14, 1260843. https://doi.org/10.3389/fpsyg.2023.1260843
South African Qualifications Authority. (2014). National policy for the development and implementation of qualifications frameworks in South Africa. SAQA.
Tan, X. (2023). Stories behind the scenes: L2 students’ cognitive processes of multimodal composing and traditional writing. Journal of Second Language Writing, 59. https://doi.org/10.1016/j.jslw.2022.100958
Tyack, D., & Cuban, L. (1995). Tinkering with utopia: A century of public-school reform. Harvard University Press.
UNESCO. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.
Warschauer, M., Tseng, W., Yim, S., et al. (2023). The affordances and contradictions of AI-generated text for L2 writers. Journal of Second Language Writing, 62. https://doi.org/10.1016/j.jslw.2023.101071
Widiati, U., Rusdin, D., Darwin, W, & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2). https://doi.org/10.1080/2331186X.2023.2236469
Williamson, B. (2024). The social life of AI in education. International Journal of Artificial Intelligence in Education, 34, 97–104. https://doi.org/10.1007/s40593-023-00342-5
Xu, Z. (2025). Disciplinary diversity in academic AI adoption: A comparative analysis of Tool Usage Declarations. ALISE Conference Proceedings. https://doi.org/10.21900/j.alise.2025.2052
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International journal of educational technology in higher education, 16(1), Article 39. https://doi.org/10.1186/s41239-019-0171-0
Zhai, N., & Ma, X. (2023). The effectiveness of automated writing evaluation on writing quality: A meta-analysis. Journal of Educational Computing Research, 61(4), 875–900. https://doi.org/10.1177/07356331221127300
Zhang, Y. (2026). AI-associated academic writing anxiety in AI-assisted contexts: evidence from Chinese EFL postgraduate students. Frontiers of Psychology, 17, 1841607. https://doi.org/10.3389/fpsyg.2026.1841607
Zhao, X. (2022). Leveraging artificial intelligence (AI) technology for English writing: Introducing Wordtune as a digital writing assistant for EFL writers. RELC Journal, 54(3), 878–882. https://doi.org/10.1177/00336882221094089
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ezile Mazathana, Benjamin Tatira
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published by IJLTER are licensed under a Creative Commons Attribution Non-Commercial No-Derivatives 4.0 International License (CCBY-NC-ND4.0).
