Evidence on AI Tools in Second Language Writing: A Systematic Review of SLA Outcomes, Learner Experiences, and Pedagogical Dynamics

Abstract

Artificial intelligence (AI) tools have transformed second language (L2) writing instruction, yet empirical evidence spanning traditional Automated Writing Evaluation (AWE) and modern Generative AI (GenAI) remains fragmented. This systematic literature review synthesized 22 primary empirical studies published between 2018 and 2025 to evaluate the effects of AI tools on L2 writing performance and map associated pedagogical benefits, operational challenges, and ethical concerns within Second Language Acquisition (SLA) frameworks. Guided by PRISMA 2020 protocols, literature was gathered across five academic databases and analyzed using SLA performance constructs and thematic synthesis. Findings reveal that most included studies focusing on accuracy (11 out of 14) reported improvements in surface-level linguistic error reduction, whereas effects on syntactic complexity were variable across 8 studies depending on tool type (AWE vs. GenAI). GenAI also showed promising effects on coherence and structural organization when accompanied by explicit instructional scaffolding. While AI tools provide immediate scaffolding and reduce writing anxiety, operational challenges, such as declining engagement, feedback overload, and cognitive passivity, and ethical risks concerning academic integrity and loss of learner voice persist. The review concludes that AI tools are most productive when used as supportive writing companions within explicitly scaffolded and collaborative learning environments. Future research should employ longitudinal designs, include more diverse learner populations, and empirically examine critical AI literacy interventions and the transfer of AI-assisted gains to unassisted L2 writing. Educators should integrate AI critically while fostering learner agency, ethical awareness, and independent writing development.