Artificial intelligence in school language education
TL;DR
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.
Abstract
Artificial intelligence (AI) is increasingly transforming language education, yet research on its pedagogical integration in school settings remains limited. This systematic review synthesizes findings from 20 studies published between 2018 and 2025, selected using the PRISMA framework from Web of Science, Scopus, and Google Scholar. The review examined AI technologies, pedagogical integration, and developmental outcomes in elementary and secondary language education. Results identified four major AI functions: evaluative feedback, adaptive scaffolding, generative language support, and conversational assistance. Most studies focused on writing, with limited attention to speaking, listening, and reading. AI proved most effective when integrated into teacher-guided instruction, while learner self-regulation influenced outcomes. Key challenges included algorithm reliability, institutional readiness, data privacy, academic integrity, and equitable implementation, highlighting the need for human-centered, ethically guided AI integration.