Research on the Role and Development Path of AI in Writing Instruction Feedback

This study explores the differences between artificial intelligence (AI) tools and teachers in writing feedback and the practical path of burden reduction.Empirical analysis shows that there are significant differences between the two in the core dimensions: in terms of feedback content, AI takes grammatical accuracy and structural specifications as the core, and relies on algorithms to achieve standardized error identification; Teacher feedback focuses on content logic, cross-cultural adaptation, and personalized expression, and has the characteristics of dynamic adjustment to the situation.In terms of implementation mechanism, AI handles batch mechanical error correction with its immediacy and scale advantages, and teachers strengthen metacognitive reflection through interactive guidance and emotional support.Learners' preferences for AI feedback are differentiated, partly recognizing efficiency and partly relying on teachers' humanistic care.In practice, teachers can achieve AI empowerment through a triple path: handing over repetitive tasks such as grammar error correction to AI, freeing up mechanical labor time; building a collaborative mechanism of "AI preprocessing-teacher deep processing"; and improving AI integration through professional development programs.It is recommended to achieve a human-machine collaborative balance through a hierarchical feedback system, targeted training, and ethical norms.