This paper synthesizes empirical studies published from 2023 to 2026 to discuss the growing position of AI-aided writing feedback for L2 students. Drawing upon the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) statement, this study organizes and critically reviews past findings in the context of instructional transformation from existing AWE systems to LLM-empowered collaborative Human-AI writing feedback in L2 education; influence of learner engagement, trust, and AI writing feedback literacy on the adoptability and applicability of AI feedback; and (3) instructional and research limitations that need to be addressed in subsequent research. Our systematic review demonstrates that generative AI facilitates writing quality improvement, revision processes, learner autonomy and increased writing access by providing on-time, tailored and interactive support. Moreover, this review reveals that the contribution of tool-aided feedback to learning lies not just in the features of AI feedback alone, but more in the users’ ability to critically understand, judge and utilize the suggested pieces of writing to advance writing competence within the teacher-supervised writing environment. Thus, the results would recommend the Human-AI Partnership framework, in which LLMs would substitute or at least assist the role of the human tutor rather than directly replace; at the same time, it would also shed light upon issues of conducting longitudinal, methodologically robust, and theoretically grounded studies regarding generative AI for L2 writing pedagogy.
Muhammad Imran, Z. Ali, Mohammad Musab Bin Azmat Ali· International journal of com...· 0 citations
Key challenges included algorithm reliability, institutional readiness, data privacy, academic integrity, academic integrity, and equitable implementation, highlighting the need for human-centered, ethically guided AI integration.
Muhammad Imran, N. Almusharraf, Khurram Shehzad· Journal of Interdisciplinary...· 0 citations
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