Work

Al-driven tools in English language education: A systematic review of pedagogical efficacy and learner outcomes

Year: 2026

Type: article

Abstract: The integration of Artificial Intelligence (AI) into English as a Foreign Language (EFL) education is transforming pedagogical approaches and learner outcomes. This systematic literature review investigates the efficacy of AI tools such as chatbots, adaptive assessments, and generative models across six core themes: linguistic competence, teacher roles, learner engagement, ethical-institutional challenges, and methodological insights. The review analyses 131 peer-reviewed empirical studies published between 2020 and 2025, using the PRISMA framework for study selection and the CASP checklist for quality appraisal. Findings indicate that AI enhances vocabulary acquisition, speaking fluency, and writing accuracy, and supports learner engagement and autonomy through personalized and interactive platforms. Teachers' attitudes significantly influence AI adoption, shaped by perceptions of usefulness, technological ease, and institutional support. However, challenges persist, including insufficient infrastructure, concerns about academic integrity, algorithmic bias, and the ethical use of student data. The Technology Acceptance Model (TAM) and TPACK framework provide critical lenses for interpreting how AI is integrated and accepted in EFL classrooms. The review further highlights methodological limitations in current studies, such as the dominance of quantitative designs, limited longitudinal data, and underrepresentation of diverse learner demographics. This study underscores the transformative potential of AI in EFL education while emphasizing the need for balanced ethical considerations and context-specific implementation strategies. Recommendations include enhanced teacher training, robust privacy policies, and inclusive, evidence-based integration practices. The review contributes to a more holistic understanding of how AI can support equitable and effective EFL instruction globally.

Source: Multidisciplinary Reviews

Authors: Hamid, Sitti Maryam, Said, Try Gustaf, Mannong, Andi Bulkis Maghfirah, Harun, Jamaluddin

Institutions: Muhammadiyah University of Makassar, University of Technology Malaysia

Language: English

Topic: Artificial Intelligence in Education

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W7220225287

FWCI:

Cites:

Cited by:

Related to: 10