Using Artificial Intelligence Tools for Providing Feedback as A Strategic Response to Addressing Challenges in Students’ Academic Writing

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.