Tahar Golea
University of Batna 2, Algeria; https://orcid.org/0009-0001-7590-3488
DOI: https://doi.org/10.36534/erlj.2025.02.01
Bibliographic citation: (ISSN 2657-9774) Educational Role of Language Journal. Volume 2025-2(14). THE ACTIVE DIMENSION OF LANGUAGE AND OF LINGUISTIC EDUCATION, pp. 6-23.
Abstract
The integration of artificial intelligence in the domain of English as a Foreign Language (EFL) education has introduced a transformative approach to addressing diverse learner needs, albeit systematic evidence on how AI applications support inclusive and differentiated instruction remains under-addressed. The present systematic review looks at empirical evidence from studies on AI applications that enhance inclusive and differentiated instruction in EFL settings and examines the effectiveness, equity implications as well as methodological quality of studies carried out between 2020 and 2025. Adhering to the updated PRISMA guidelines (2021), the search featured Web of Science, Scopus, ERIC, IEEE, and ACM databases for empirical studies published between January 2020 and October 2025. Inclusion criteria followed the PICOS framework with population of K-18 EFL learners, intervention of AI-based instructional tools, comparison with traditional or non-AI methods, outcomes of equity, access, achievement, and engagement, and empirical study designs. Twenty-seven studies were selected as they have made use of AI applications which included automated writing evaluation systems, chatbots and conversational agents, adaptive learning platforms, and multimodal AI systems. Recent research shows that AI-powered chatbots enhance significantly English-speaking learning outcomes, confidence and engagement (Du & Daniel, 2024), while automated writing evaluation systems feature medium effect sizes (g = 0.55) for writing performance improvement (Fleckenstein et al., 2023). Nonetheless, equity gap analysis revealed persistent disparities for learners from lower socioeconomic backgrounds with an equity gap index of negative 0.23. Critical examination identified concerns regarding algorithmic bias, data privacy, and linguistic hegemony. Contemporaneously, while AI applications hold promise for enhancing EFL instruction through personalized feedback and adaptive learning pathways, current implementations may inadvertently perpetuate existing inequities.
Keywords: artificial intelligence, English as foreign language, inclusive education, differentiated instruction, systematic review, educational equity
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