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In Yemen’s conflict-affected settings, adoption requires overcoming infrastructural limits, socioeconomic barriers, and cultural-fit demands. Using a mixed-methods design, the study analyzes outcomes from 75 Yemeni university-level EFL students interacting with AI vocabulary tools, focusing on engagement, socio-technical obstacles, and comparison with traditional approaches. Results highlight benefits in retention, engagement, and confidence while stressing the role of cost, connectivity, and localized cultural alignment through hybrid and policy-supported models.",{"@graph":69,"@context":114},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/ai-enhanced-vocabulary-acquisition-in-conflict-affected-contexts-a-study-of-yemeni-efl-learners-adaptations-challenges-and-outcomes/426470/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/ai-enhanced-vocabulary-acquisition-in-conflict-affected-contexts-a-study-of-yemeni-efl-learners-adaptations-challenges-and-outcomes/426470.png","ImageObject",300,407,{"name":92,"@type":93},"Nguyễn Văn Học","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-13","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":19},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108],{"name":109,"@type":110,"acceptedAnswer":111},"What conditions are necessary for AI tools to achieve their full impact?","Question",{"text":112,"@type":113},"The study concludes that meaningful impact depends on addressing socio-technical barriers using localized solutions, policy interventions, and hybrid models that balance innovation with accessibility.","Answer","https://schema.org",{"og:url":83,"og:type":116,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":118,"canonical":83},"index,follow",{"doc_id":120,"site_id":62},426470,1790719276,{"code":4,"msg":5,"data":123},{"doc_id":120,"user_id":124,"nickname":92,"user_avatar":125,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":126,"file_id":127,"file_url":128,"file_type":129,"file_size":130,"view_count":19,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":131,"language":132,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":133,"faqs":134,"seo_title":135,"seo_description":67,"update_tm":136,"read_time":26},1374402739827,"https://ap-avatar.wpscdn.com/avatar/14000c97e7351f1a627?x-image-process=image/resize,m_fixed,w_180,h_180&k=1787885694763230660","Education and Linguistics Research  \nISSN 2377-1356  \n 2025, Vol. 11, No. 1  \nAI-Enhanced Vocabulary Acquisition in Conflict-Affected Contexts: A Study of Yemeni EFL Learners’Adaptations, Challenges, and Outcomes  \nDr. Abdulrahman Mokbel Mahyoub Hezam  \nDepartment of Languages and Translation, Taibah University, Saudi Arabia  \nE-mail: [arahmanhezam@gmail.com](arahmanhezam@gmail.com)  \nRian Abdulrahman Moqbel Mahyoub  \na PhD scholar at the Department of Education, EFLU, Hyderabad, India.  \nE-mail: [rianmahyoub@gmail.com](rianmahyoub@gmail.com)  \nReceived: March 25, 2025  \ndoi:10.5296/elr.v11i1.22789  \nAccepted: May 28, 2025 Published: June 17, 2025 URL: [https://doi.org/10.5296/elr.v11i1.22789](https://doi.org/10.5296/elr.v11i1.22789)  \nAbstract  \nArtificial intelligence (AI) technologies have revolutionized language learning, offering personalized, adaptive, and interactive tools for enhancing vocabulary acquisition. However, implementing AI-driven solutions in conflict-affected regions like Yemen presents unique challenges, including infrastructural constraints, socioeconomic barriers, and the need for cultural relevance. This study explores the effectiveness and obstacles of AI-enhanced vocabulary learning among 75 Yemeni university-level English as a Foreign Language (EFL) students through a mixed-methods approach. The research examines learners’ engagement with AI vocabulary tools, socio-technical barriers impeding adoption, and the comparative effectiveness of AI-mediated versus traditional learning methods. The findings reveal a complex interplay between AI’s potential for improving retention, engagement, and confidence, and the systemic challenges of cost, internet access, and cultural alignment. While AI tools demonstrate promise, their full impact hinges on addressing these barriers through localized solutions, policy interventions, and hybrid models that balance innovation with accessibility. This study contributes to the discourse on AI in education by highlighting the importance of contextually grounded approaches that account for the socioeconomic realities of marginalized learning environments.  \nKeywords: AI-mediated vocabulary learning, Conflict-affected education, Socio-technical  \n64 [http://elr.macrothink.org](http://elr.macrothink.org)  \nEducation and Linguistics Research  \nISSN 2377-1356  \n 2025, Vol. 11, No. 1  \nbarriers, Technology-Enhanced Language Learning (TELL), Vocabulary Acquisition Theory, Yemeni EFL learners  \n65 [http://elr.macrothink.org](http://elr.macrothink.org)  \nEducation and Linguistics Research  \nISSN 2377-1356  \n 2025, Vol. 11, No. 1  \n1. Introduction  \nArtificial intelligence (AI) has revolutionized language learning through adaptive and interactive tools that enhance vocabulary and fluency development. Popular applications like ChatGPT, Duolingo, and Rosetta Stone leverage machine learning and natural language processing to deliver personalized instruction, real-time feedback, and engaging gamified exercises (De La Vall & Araya, 2023) . While these technologies enable flexible, self-paced learning, issues around AI accuracy, cultural representation, data privacy, and equal access pose ongoing challenges for educational integration (Gutiérrez, 2023) . Nonetheless, research demonstrates that AI-powered tools significantly improve both language mastery and cross-cultural communication abilities, making them valuable complements to conventional teaching methods (St. Fountoulakis, 2024) . The technology’s ability to adapt to individual needs while providing consistent practice opportunities has transformed how learners approach language acquisition, though careful consideration must be given to addressing its current limitations and ethical implications.  \nAI technology shows significant potential for transforming education in conflict-affected regions, offering ways to personalize learning and maintain educational continuity despite challenging conditions (Ahmed et al., 2024; Fedorenko & ","cbCaihyJiJvKQVjB","https://ap.wps.com/l/cbCaihyJiJvKQVjB","pdf",322113,24,"English","# Abstract\n# Keywords\n# 1. Introduction","[{\"question\":\"What conditions are necessary for AI tools to achieve their full impact?\",\"answer\":\"The study concludes that meaningful impact depends on addressing socio-technical barriers using localized solutions, policy interventions, and hybrid models that balance innovation with accessibility.\"}]","AI-Enhanced Vocabulary Acquisition in Conflict-Affected Contexts - A Study of Yemeni EFL Learners’ Adaptations, Challenges, and Outcomes | PDF",1790640675]