This systematic review examines the effectiveness of Artificial Intelligence (AI)-powered tools in English Language Teaching (ELT) among higher education students. Guided by PRISMA 2020 guidelines, this review analyzed 30 peer-reviewed quantitative studies published from 2020 to 2024, sourced from Scopus, PubMed, and Google Scholar. Inclusion criteria required empirically grounded quantitative studies focused on AI tool integration in ELT within higher education contexts, providing evidence-based insights applicable to pedagogy, teacher training, and institutional policy. The study aimed to identify the primary factors contributing to or hindering the effectiveness of AI tools and to examine how outcomes vary across learner demographics including age, language proficiency, and institutional context. Key findings reveal that AI-powered tools such as Automated Writing Evaluation (AWE) systems, intelligent tutoring systems (ITS), AI chatbots, and adaptive learning platforms substantially improve learner performance in writing, grammar, vocabulary, and speaking. However, their effectiveness is moderated by the quality of teacher guidance, learner digital literacy, and equitable access to technology. Writing anxiety and low self-efficacy are notably reduced when AI tools provide low-stakes, immediate feedback, while socioeconomic disparities and cultural biases embedded in AI platforms remain significant barriers. The review underscores the need for holistic, teacher-guided AI integration strategies, robust professional development programs, and policy reforms that ensure equitable access to AI resources in ELT. Collaboration among educators, policymakers, and technology developers is paramount in harnessing the full potential of AI-powered tools to enhance English language proficiency in higher education.
- Citation du texte
- Aileen Decipolo (Auteur), 2026, The Effectiveness of AI-Powered Tools in English Language Teaching Among Higher Education Students: A Systematic Review, Munich, GRIN Verlag, https://www.grin.com/document/1708506
