Integrating AI into EFL Education in the Arab World: A Systematic Review

• In Event: Investigating Generative AI Use and Integration in International Contexts: Opportunities, Challenges, and Insights

Abstract

While global research highlights AI’s benefits in EFL education (Bender, 2024; Huang, 2024; Rincon, 2024), systematic analysis of its integration in Middle Eastern classrooms remains limited (Oraif, 2024; Jamshed et al., 2024). Therefore, this systematic review aims to address this gap by investigating the integration of AI in English as a Foreign Language (EFL) education across the Middle East, with a focus on the Arab world. It aims to identify the opportunities AI presents for language learning, examine the challenges hindering its adoption, and explore the perceptions of both EFL teachers and students toward AI technologies.

The study is grounded in socio frameworks, which emphasize the interaction between technology, learning, and culture to construct meaning (Harasim, 2017). Rather than simply memorizing facts, this theory emphasizes the role of interaction to knowledge making (Kalina & Powell, 2009). AI tools—particularly generative AI, align well with this theory by offering personalized, real-time feedback to enhance foreign language learning skills, and its application in culturally and linguistically distinct contexts such as the Middle East.

A systematic literature review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to ensure methodological rigor, transparency, and replicability (Pollock & Berge, 2018; Moher et al., 2009). The Scopus database was searched for peer-reviewed studies published within the last five years, focusing on AI applications in formal language learning settings in Arab countries. Initial screening yielded 69 studies, which were filtered using inclusion criteria: focus on language learning, use of AI, relevance to the Arab world, and formal educational contexts. Thirteen studies met the criteria and were analyzed using thematic analysis and descriptive quantitative synthesis.

Results reported positive perceptions of AI tools among both students and teachers, especially in terms of enhancing engagement, language proficiency, and providing personalized feedback. For instance, Jamshed et al. (2024) found that Saudi EFL learners had highly favorable views towards AI in education, recognizing its potential to improve the learning process in universities. Similarly, Alenazi (2024) highlighted that while many students were interested in AI, only a small percentage were eager to incorporate it into their learning, with varying readiness across different proficiency levels. On the other hand, other studies such as those by Alsalem (2024) and Abd Algane et al. (2023) underscore concerns over the reliability and validity of AI tools in assessing critical thinking and language competence. Teachers expressed reluctance to fully trust AI grading tools and emphasized the need for professional training. Therefore, while AI holds significant promise, its full adoption in the region requires more attention and support.

This review addresses the literature gap by synthesizing evidence on AI use in EFL education within the Arab world. It also offers insights for educators, policymakers, and researchers to innovate EFL education and reimagine the AI’s role in shaping the future of language education in the Middle East.

Authors

• Raghad Faisal Alsaka, University of Idaho

• Nesma Ragab Nasr, Northern Arizona University