Using Artificial Intelligence Tools for Providing Feedback as A Strategic Response to Addressing Challenges in Students’ Academic Writing
Innocent Zitha 
, Ditshego Masete & Sarah Matsetela
Issue: Vol.6 No.7 Article 12 pp. 1096 -1111
DOI: https://doi.org/10.38159/ehass.20256712 | Published online 18th June, 2025
© 2025 The Author(s). This is an open access article under the CCBY license (http://creativecommons.org/licenses/by/4.0/).
The domain of academic writing poses a series of persistent challenges for students transitioning into higher education, particularly stemming from deficiencies in fundamental writing competencies. This paper, therefore, examined these obstacles and advocated for the implementation of personalised digital feedback through artificial intelligence (AI) tools to enhance students’ writing abilities. The researchers collected data from 147 participants using purposive sampling among the ECP (Extended Curriculum Programme) students, a group specifically selected for their need for writing support. Data was collected using questionnaires, narrative inquiries, and an analysis of written essays. The Field-Mode-Tenor framework from Register theory was used to categorise language usage mistakes and errors systematically. The integration of AI tools, particularly Meta AI and Grammarly, was found to improve students’ writing skills by providing timely and individualised feedback. The findings of this study highlight key academic writing challenges, such as redundancy, orthographic errors, and the misuse of contractions. The findings of this study demonstrate that both Meta AI and Grammarly provided substantial feedback on assessments. They offered practical solutions and enhanced confidence in the effectiveness of these AI tools. Furthermore, the findings suggest that AI tools possess the capacity to bridge gaps in academic proficiency, thereby contributing to a more equitable education system. This study contributes to the literature on integrating AI tools in language teaching and providing constructive feedback that significantly improves students’ writing skills. Consequently, this promotes digital literacy and critical thinking, encouraging students to be engaged users of technology rather than passive consumers.
Keywords: Error Tagging, AI, Discursive Writing, Peer Feedback, Prowess.
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Innocent Zitha is a Lecturer and Researcher specialising in English Academic Literacy within the School of Languages in the Faculty of Humanities at North-West University. My experience in the field of Higher Education spans over five years. Furthermore, I have authored and co-authored 18 papers and 3 book chapters that have been published in peer-reviewed journals.
Ditshego Masete is a Lecturer of English Academic Literacy in the Faculty of Law at North-West University, Potchefstroom Campus, South Africa. He has worked for over 3 years in the higher education sector. He specialises in Post-Colonial Studies, Feminism, and Crime narratives.
Sarah Matsetela is a Lecturer in the Department of Academic Literacy, School of Languages, Faculty of Humanities, North-West University, Mafikeng Campus, Republic of South Africa. Her research interests encompass linguistics, academic literacy, and literature. She serves as the head of the Academic Literacy department.
Zitha, Innocent, Ditshego Masete and Sarah Matsetela. “Using Artificial Intelligence Tools for Providing Feedback as A Strategic Response to Addressing Challenges in Students’ Academic Writing,” E-Journal of Humanities, Arts and Social Sciences 6, no.7 (2025): 1096 – 1111. https://doi.org/10.38159/ehass.20256712
© 2025 The Author(s). Published and Maintained by Noyam Journals. This is an open access article under the CCBY license (http://creativecommons.org/licenses/by/4.0/).
