A Systematic Comparative Review of Generative AI vs. Teacher Feedback in EFL Writing: Learner Perceptions, Preferences, and Psychological Factors

The introduction of GenAI into instruction in a second language puts the conventional focus on teacher feedback in question. Although tools such as ChatGPT are quickly spreading, whether algorithmic or human feedback are more effective in education is an issue in pedagogical discussion. The systematic review consolidates findings on 17 empirical studies (2023–2025) with a unique focus on GenAI and teacher feedback comparison in EFL writing situation. With reference to the self-determination and cognitive load theories, our analysis reveals the steady division of labor in feedback efficacy where GenAI performs more effectively as a nurturing factor in reducing anxiety and surface-level error-correction skills than teacher feedback, which performs better in fostering higher-order level argumentation, coherent and metacognitive awareness. Most importantly, this review empirically confirms the superiority in hybrid feedback models, which allow using AI to achieve immediacy and accuracy, with a human-focused viewpoint used only to respond to the situation. We suggest that GenAI should exist and operate in a culturally competent, collaborative structure intelligence that does not replace, but adds the scaffold that will streamline the work of the teacher and increase student autonomy. The results can serve as an evidence-based guideline to applying AI in writing classes and reducing the risks of overdependence.