Artificial Intelligence as a Source of Feedback in L2 Writing Classrooms: Best Practices and Pedagogical Strategies

Abstract

Writing proficiency is a key element of academic success for English as a Second Language (ESL) and English as a Foreign Language (EFL) students, but it presents ongoing challenges that demand innovative pedagogical solutions. The rapid advancement of Artificial Intelligence (AI) has created unprecedented opportunities for enhancing writing instruction through automated feedback systems. This article brings together theoretical frameworks, empirical research, and pedagogical best practices to examine how AI tools can serve as effective sources of feedback in second language (L2) writing classrooms. Drawing on cognitive, sociocultural, and contrastive rhetoric theories of writing, the article explores the nature of L2 writing difficulties, the critical role of feedback in writing development, and the strengths and limitations of AI-generated feedback. A systematic review of recent empirical studies reveals that AI-powered feedback systems are consistently effective in enhancing micro-level writing skills, particularly grammatical accuracy and lexical diversity. However, limitations remain in addressing macro-level writing concerns, and hybrid feedback models that combine AI with teacher input appear to yield the most comprehensive benefits. The article presents evidence-based recommendations for teachers and students, including strategies for scaffolding AI use, developing feedback literacy, designing effective prompts, and integrating AI feedback with teacher and peer feedback. It also addresses ethical considerations and practical concerns to ensure effective use of AI tools. It concludes with implications for pedagogy and directions for future research. This article argues that the thoughtful integration of AI feedback with teacher feedback, grounded in pedagogical principles and human judgment, can significantly enhance L2 writing instruction.