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Artificial Intelligence-Supported English as a Foreign Language Learning: A Narrative Review of Personalisation, Feedback, Engagement and Pedagogical Collaboration

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Title: Artificial Intelligence-Supported English as a Foreign Language Learning: A Narrative Review of Personalisation, Feedback, Engagement and Pedagogical Collaboration
Language: English
Authors: Sultan Hammad Alshammari (ORCID 0000-0001-7294-9053), Amal Alhamazany (ORCID 0000-0002-9298-6983)
Source: International Journal of Technology in Education and Science. 2026 10(2):219-236.
Availability: International Society for Technology, Education, and Science. e-mail: ijtesoffice@gmail.com; Web site: http://www.ijtes.net
Peer Reviewed: Y
Page Count: 18
Publication Date: 2026
Document Type: Journal Articles
Information Analyses
Descriptors: Literature Reviews, Artificial Intelligence, Technology Uses in Education, English (Second Language), Second Language Learning, Individualized Instruction, Feedback (Response), Learner Engagement, Learning Motivation, Skill Development
ISSN: 2651-5369
Abstract: The rapid advancement of artificial intelligence (AI) has substantially reshaped educational practices substantially, particularly within English as a Foreign Language (EFL) learning contexts. This narrative review synthesises peer-reviewed research published between 2020 and 2025 to examine how AI supports EFL learners across six key dimensions: learning personalisation and adaptation; assessment and feedback; student engagement and motivation; study support and skills development; teacher-student-AI pedagogical collaboration; and critical challenges and ethical considerations. Drawing on recent high-quality peer-reviewed journal articles, the review employs a thematic synthesis approach to integrate diverse theoretical perspectives, empirical evidence and pedagogical insights. The findings indicate that AI-supported technologies can enhance EFL learning by enabling adaptive instruction, delivering timely and formative feedback, fostering learner engagement and motivation, and supporting self-regulated learning and language skill development. Simultaneously, the review underscores the importance of human-centric pedagogical design, highlighting that AI is most effective when positioned as a complement to, rather than a substitute for, teacher expertise and learner agency. Key challenges -- including academic integrity, ethical concerns, data privacy, algorithmic bias, overreliance on technology and inequitable access -- also are identified as significant constraints on effective AI integration. Overall, this review offers an integrative and pedagogically grounded account of AI-supported EFL learning and poses implications for instructional practice, teacher education and future research aimed at promoting responsible, equitable and sustainable uses of AI in language education.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506371
Database: ERIC
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  Data: Artificial Intelligence-Supported English as a Foreign Language Learning: A Narrative Review of Personalisation, Feedback, Engagement and Pedagogical Collaboration
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  Data: <searchLink fieldCode="AR" term="%22Sultan+Hammad+Alshammari%22">Sultan Hammad Alshammari</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7294-9053">0000-0001-7294-9053</externalLink>)<br /><searchLink fieldCode="AR" term="%22Amal+Alhamazany%22">Amal Alhamazany</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9298-6983">0000-0002-9298-6983</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Technology+in+Education+and+Science%22"><i>International Journal of Technology in Education and Science</i></searchLink>. 2026 10(2):219-236.
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  Data: International Society for Technology, Education, and Science. e-mail: ijtesoffice@gmail.com; Web site: http://www.ijtes.net
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  Data: The rapid advancement of artificial intelligence (AI) has substantially reshaped educational practices substantially, particularly within English as a Foreign Language (EFL) learning contexts. This narrative review synthesises peer-reviewed research published between 2020 and 2025 to examine how AI supports EFL learners across six key dimensions: learning personalisation and adaptation; assessment and feedback; student engagement and motivation; study support and skills development; teacher-student-AI pedagogical collaboration; and critical challenges and ethical considerations. Drawing on recent high-quality peer-reviewed journal articles, the review employs a thematic synthesis approach to integrate diverse theoretical perspectives, empirical evidence and pedagogical insights. The findings indicate that AI-supported technologies can enhance EFL learning by enabling adaptive instruction, delivering timely and formative feedback, fostering learner engagement and motivation, and supporting self-regulated learning and language skill development. Simultaneously, the review underscores the importance of human-centric pedagogical design, highlighting that AI is most effective when positioned as a complement to, rather than a substitute for, teacher expertise and learner agency. Key challenges -- including academic integrity, ethical concerns, data privacy, algorithmic bias, overreliance on technology and inequitable access -- also are identified as significant constraints on effective AI integration. Overall, this review offers an integrative and pedagogically grounded account of AI-supported EFL learning and poses implications for instructional practice, teacher education and future research aimed at promoting responsible, equitable and sustainable uses of AI in language education.
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