THE ROLE OF AI-BASED FEEDBACK IN ENHANCING ACADEMIC WRITING SKILLS OF UNIVERSITY STUDENTS:AN APPLIED LINGUISTICS PERSPECTIVE

Abstract

The rapid integration of Artificial Intelligence (AI) into higher education has introduced new possibilities for supporting academic writing development. This study examines the role of AI-based feedback in enhancing university students’ writing skills from an applied linguistics perspective. The paper synthesizes recent empirical findings (2020–2025) and categorizes them into five models: (1) effectiveness of AI feedback on academic writing, (2) comparative insights between AI and human feedback, (3) trust, perceptions, and learner autonomy, (4) broader educational dynamics and ethical concerns, and (5) systematic reviews, tools, and future directions. A comparative methodology is employed, combining thematic analysis and descriptive comparison across models, supported by analytical tables. Findings suggest that AI feedback significantly improves grammar, vocabulary, and coherence in student writing, though challenges remain in addressing higher-order skills such as argumentation and critical thinking. Moreover, students’ trust in AI feedback is mediated by transparency, prior exposure to technology, and cultural context. While AI offers immediacy, scalability, and objectivity, human feedback continues to provide depth, empathy, and sustainability. The study concludes that a hybrid approach, combining AI efficiency with human guidance, holds the greatest promise for long-term academic writing development. Implications for applied linguistics include the need to update feedback frameworks, develop AI literacy among students, and establish ethical guidelines for responsible integration.