[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83949-en":3,"doc-seo-83949-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},83949,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","AI Tools in Arab University English Classrooms Looking Back and Forward","This paper synthesizes empirical research on AI tools supporting English as a second/foreign language (EL2) learners in Arab University Classrooms (AUCs) from Jan 1, 2023 to Aug 31, 2025. Searches across Google Scholar, Web of Science, and Scopus using PRISMA-guided criteria yielded 184 studies, with 11 meeting inclusion requirements. Results show positive EL2 attitudes toward AI for drafting, revision, and practice. Writing surface-level improvements are consistent, speaking gains are mixed and often depend on teacher mediation, with recommendations for scaffolded integration and teacher training.","AI tools in Arab University English classrooms: Looking back and forward  \nMohammed Q. Shormani  \nIbb University, Yemen  \n[shormani@ibbuniv.edu.ye/](shormani@ibbuniv.edu.ye/)[https://orcid.org/0000-0002-0138-4793](https://orcid.org/0000-0002-0138-4793)  \nMuneef Yehia Alshawsh  \nIbb University, Yemen  \n(preprint, June, 2026)  \nAbstract  \nThis paper aims to synthesize empirical research on AI tools used to support English as a second/foreign language (EL2) learners in Arab University classrooms (AUCs) between Jan 1st 2023 and Aug 31st 2025. We utilized 3 large databases, namely Google Scholar, Web of Science, and Scopus as the data sources. Using PRISMA-guided searches across these well-known databases, we included only published articles. The search process results in 184 studies, but only 11 studies met the inclusion criteria. Findings unveil that EL2 learners have positive attitudes towards AI for drafting, revision, and practice. Empirical gains were most consistent for surfacelevel outcomes improvements in higher-order writing quality and speaking proficiency was mixed and often contingent on teacher mediation. The paper concludes by proposing a research agenda and practical guidelines for Arab universities seeking evidence-based AI integration in EL2 instruction. It also recommends scaffolded integration, teacher training, reflective tasks to reduce over-reliance on AI tools.  \nKeywords: AI tools, EL2 learners, Arab university classrooms, systematic review  \n1. Introduction  \nTo date, no comprehensive systematic review has synthesized studies investigating AI supporting EL2 acquisition/learning in Arab University classrooms (AUCs) (cf. Alhusaiyan, 2025) . While individual studies provide valuable insights into attitudes, effectiveness, and integration strategies, their scattered nature makes it difficult to discern overarching patterns or evaluate the cumulative evidence. Existing global reviews (e.g., Zhu & Wang, 2025; Wang et al., 2024) tend to include Arab samples only marginally or merge them into broader Middle Eastern categories without contextual specificity. Additionally, the types of AI models deployed, ranging from LLM-based chatbots to ITS platforms and AI grammar evaluators, have not been compared systematically in terms of methodological design, participant profiles, or empirical outcomes. This absence of synthesis limits the ability of educators, policymakers, and researchers to make evidence-based decisions regarding AI adoption in Arab higher education. Thus, a systematic review focusing explicitly on Arab university EL2 classrooms is both timely and necessary to map current hotspts, assess empirical rigor, and identify future research directions.  \nIn the current decade, artificial intelligence (AI) has rapidly developed to influence almost all the academic and nonacademic fields such as translation, research, film making, accounting (see e.g., Shormani, 2025a; Shormani & Alfahad, 2025) . It has also entered the field of acquiring/learning and teaching of English as a second/foreign language (EL2) (see e.g., Han, 2024; Zare et al., 2025, 1 & 2) . The emergence of LLMs such as ChatGPT, and other AI-based educational tools like Grammarly, ELSA, and intelligent tutoring systems, has generated unprecedented opportunities  \nfor personalized learning, automated feedback, and enhanced engagement. In L2 contexts, AI applications have been increasingly adopted to assist with writing correction, pronunciation practice, vocabulary expansion, and conversational simulation. These technologies promise to complement teacher-led instruction by offering immediate feedback, adapting to learners’individual needs, and promoting autonomy (Zhu & Wang, 2025; Wang et al., 2024) .  \nA systematic review is simply defined as a method for synthesizing intellectual knowledge produced in a particular field of study, establishing insights and study inquiries into that field, for looking in the past, present and future (see e.g., Colquho","cbCaicrZbZyOXkxm","https://ap.wps.com/l/cbCaicrZbZyOXkxm","pdf",461929,4,1,18,"English","en",105,"# Abstract\n# Introduction\n## Research gap and motivation\n## AI tools in EL2 learning\n## Review approach and scope\n## Conceptual framing and concerns","[{\"question\":\"What time period and search databases does the review cover?\",\"answer\":\"The review covers studies from Jan 1, 2023 to Aug 31, 2025 and uses Google Scholar, Web of Science, and Scopus as data sources.\"},{\"question\":\"How many studies were initially identified and how many were included?\",\"answer\":\"The search returned 184 studies, and only 11 studies met the inclusion criteria under the PRISMA-guided process.\"},{\"question\":\"What effects of AI tools on EL2 learners does the paper report most consistently?\",\"answer\":\"Findings indicate positive learner attitudes toward AI for drafting, revision, and practice, with the most consistent empirical gains in surface-level improvements in higher-order writing quality, while speaking results are mixed and often contingent on teacher 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