Aug 2026· Frontiers in Education· Vol 11· 0 citations· 79 references
TL;DR
This review examines how AI is integrated into EFL/ESL education across language skills, instructional domains, and educational contexts and conceptualises AI in EFL/ESL education as a pedagogical ecology in which tools, learners, teachers, feedback regimes, assessment practices, institutional infrastructures, and governance arrangements interact.
Abstract
Artificial intelligence (AI) is increasingly embedded in English as a Foreign/Second Language (EFL/ESL) education, yet existing research remains fragmented across tools, skills, and short-term outcomes. This review examines how AI is integrated into EFL/ESL education across language skills, instructional domains, and educational contexts.
This PRISMA-guided systematic review synthesised 221 unique peer-reviewed publications. Moving beyond a tool-centred inventory, the review analysed AI through four interrelated dimensions: pedagogical roles, mediating processes, reported outcomes, and contextual constraints.
AI systems increasingly operated as multifunctional pedagogical actors rather than isolated instructional aids. The most frequently coded roles were teacher orchestration/support, content and materials generation, assessment or diagnosis, coaching or practice companionship, tutoring or scaffolding, and conversational partnership. AI-mediated learning was especially concentrated in writing and speaking/communication, where text-based, voice-based, multimodal, immersive, and adaptive systems supported feedback, revision, rehearsal, and learner–system interaction. Reported benefits included expanded practice opportunities, accelerated feedback cycles, redistributed instructional labour, skill development, learner autonomy, affective support, assessment and monitoring, collaboration, and multilingual engagement. Recurring challenges included technical reliability and feedback quality, teacher readiness, privacy and data security, learner over-reliance, infrastructural inequality, bias and cultural mismatch, authorship and academic-integrity concerns, and methodological weaknesses.
Interpreted through a three-layer framework of efficiency, pedagogy, and ideology, the synthesis conceptualises AI in EFL/ESL education as a pedagogical ecology in which tools, learners, teachers, feedback regimes, assessment practices, institutional infrastructures, and governance arrangements interact. The review provides a theory-informed framework for analysing, designing, and governing AI-mediated language education beyond simple claims of technological effectiveness.
This research presents a systematic review of the use of artificial intelligence (AI) in language education, synthesising evidence on tools used for teaching and learning. The review encompassed empirical, conceptual and review studies identified from key education and language databases and is focused on AI use by language learners and teachers in both formal and non-formal contexts. The review is organised under five main dimensions: (1) stakeholder perceptions and readiness; (2) AI applications and associated technologies; (3) AI tools’ impact on language skills and affective factors; (4) pedagogical integration and instructors’ professional development; and (5) overall affordances/challenges and the future implications. The findings reveal that generative AI and conversational agents are increasingly becoming integral components in language education, utilised by educators to offer personalised feedback, adaptive practice, and student engagement and motivation. Evidence also indicates positive impacts regarding writing quality, oral performance, vocabulary, and academic motivation. However, the integration of AI is not universally beneficial: its value is heavily contingent upon learner proficiency, task design and teacher mediation, coupled with risks of learners’ over-reliance, diminished metalinguistic awareness, anxiety or threats to academic integrity. AI literacy, infrastructural and policy constraints, data privacy and bias, and geographic and linguistic inequities in evidence-based research are the most highlighted challenges necessitating system-wide planning of AI harnessing in education.
Iman El-Nabawi Abdel Wahed Shaalan, Ayman Shaaban Khalifa Ahmad· Journal of Language Teaching...· 0 citations
Artificial intelligence (AI) has rapidly transformed language education by providing innovative tools that support teaching, learning, and assessment. In English for Specific Purposes (ESP) and English for Academic Purposes (EAP), AI technologies such as ChatGPT, automated writing evaluation, grammar assistants, machine translation, and intelligent tutoring systems have increasingly been adopted to facilitate academic and professional communication. However, evidence regarding AI implementation in ESP/EAP remains fragmented across educational technology, applied linguistics, artificial intelligence in education, and language assessment research. This study aims to map current AI-mediated pedagogical practices, identify major challenges, and propose future research directions for AI integration in ESP and EAP. A scoping review methodology guided by the Joanna Briggs Institute framework and PRISMA-ScR reporting guidelines was employed. Literature was identified using the Population–Concept–Context (PCC) framework, resulting in 45 relevant sources consisting of empirical studies, review articles, policy reports, methodological references, technical papers, and ESP/EAP theoretical works. The findings reveal that AI has primarily been utilized for writing feedback, revision support, materials development, prompt-based learning, simulated communication, AI literacy, and assessment redesign. Nevertheless, concerns remain regarding hallucination, linguistic bias, disciplinary authenticity, privacy, academic integrity, and learner overdependence. The review concludes that effective AI implementation in ESP/EAP requires human verification, genre-based pedagogy, AI literacy, learner agency, and transparent assessment practices. These findings provide practical implications for language teachers, curriculum developers, and higher education institutions seeking responsible AI integration.
Luluk Iswati, Abd. Rajab· Jurnal Pendidikan dan Sastra...· 0 citations
Across the reviewed studies, generative AI was found to enhance language learning through personalized feedback, increased learner autonomy, and greater learning engagement, but concerns regarding academic integrity, AI literacy, ethical issues, and institutional readiness remain significant challenges to its sustainable implementation.
N. H. Hong Nhung· International journal of soc...· 0 citations
A synthesized conceptual perspective is contributes a synthesized conceptual perspective that integrates pedagogical, ethical, governance, and sustainability dimensions into a unified framework for responsible AI-augmented higher education.
Montadzah A. Abdulgani, Jonathan M. Mantikayan· International Journal of Lat...· 0 citations
This mixed-methods study examines English as a Foreign Language (EFL) teachers’ perceptions of AI tools, focusing on usage practices, perceived opportunities, challenges, and professional development needs, and highlights a dual identity in teacher discourse.
Memidin Braha, Rezarta Ramadani· Open Research Europe· 0 citations
It is argued that the teacher’s role in AI-based instruction is being reconfigured rather than diminished, offering implications for teacher professional development and the design of teacher-facing AI systems.
