Keywords
ISO 9241-210
Multilingual Education
Artificial Intelligence
Natural Language Processing
How to Cite
Abstract
Background: While AI is promoted as a transformative force in education through adaptive platforms and real-time feedback, its implementation for multilingual learners often risks reinforcing educational inequalities. Current scholarship cautions that automated systems still struggle with cultural nuances and idiomatic expressions, highlighting the need for design approaches that foreground equity and human agency.
Objective: This systematic review examines 10 core studies through the lens of the ISO 9241-210 Human-Centered Design framework. The objective is to analyze how AI-based educational technologies are designed and evaluated to support multilingual learners, specifically focusing on the "Context of Use," "User Requirements," "Design Solutions," and "Evaluation" phases.
Methods: Through a systematic search of four databases and subsequent snowballing, 10 core papers were selected to analyze how AI tools address linguistic and cultural diversity.
Results: Across the reviewed studies, reported improvements ranged from quantitative gains, including a 25–31% increase in literacy and vocabulary retention and a rise in academic success rates up to 77.8%. Furthermore, AI-driven systems, when aligned with HCD principles, were associated with saving educators up to 41% of their time. However, evaluations revealed critical 'socio-technical paradoxes': students faced a "trade-off" where they reverted to English-centric prompting due to algorithmic bias in low-resource languages, and risks of "metacognitive laziness" emerged from over-reliance on automated tools.
Conclusion: The successful integration of AI in multilingual contexts depends on a shift from content generation to pedagogical scaffolding. Designers must prioritize "Human-in-the-loop" models that balance computational efficiency with human oversight to provide the emotional engagement and cultural authenticity that AI currently lacks.
References
Aravind, Angalakuduru, M. Durairaj, Preeti Chitkara, et al. “Adaptive AI-Based Personalized Learning for Accelerated Vocabulary and Syntax Mastery in Young English Learners.” International Journal of Advanced Computer Science and Applications 16, no. 4 (2025).
Botarleanu, Robert-Mihai, Micah Watanabe, Mihai Dascalu, Scott A. Crossley, and Danielle S. McNamara. “Multilingual Age of Exposure 2.0.” International Journal of Artificial Intelligence in Education 34, no. 4 (2024): 1353–77. https://doi.org/10.1007/s40593-023-00386-7.
Chen, Xiaojiao, Zhebing Hu, Yuanyuan Li, and Chengliang Wang. “The Journey of Challenges and Triumphs: A Systematic Literature Review of the Dynamic Evolution of Human-Centered Artificial Intelligence in Education.” Interactive Learning Environments 33, no. 8 (2025): 4906–31. https://doi.org/10.1080/10494820.2025.2472288.
Cole, Jennefer York. “Using AI in the Bilingual Classroom to Enhance Writing Skills in Second Language Learning: A Case Study.” Journal of Education, Innovation and Communication 7, no. 3 (2025): 51–58. https://doi.org/10.34097/jeicom-7-3-5.
Dr. Nishat Zafar, Dr. Saira, and Seerat Afzal. “AI-Powered Reading Support for Multilingual Learners in Higher Education: A Critical Review.” Journal for Social Science Archives 3, no. 1 (2025): 776–86. https://doi.org/10.59075/jssa.v3i1.158.
Du, Mingxuan, Lili Zhu, and Mario Di Nardo. “Strategic Application of Deep Learning Methods in Global Educational Collaboration.” Proceedings of the 2025 International Conference on Big Data and Informatization Education, February 21, 2025, 313–17. https://doi.org/10.1145/3729605.3729660.
Hamid, Shazia. Integrating Artificial Intelligence and Multimodality in Language Education: A Systematic Review of Emerging Trends and Practices. 4, no. 2 (2025).
ISO. “ISO 9241-210:2019.” Accessed March 16, 2026. https://www.iso.org/standard/77520.html.
Khan, Razia, Md. Tauseef Qamar, Mohd Sajid Ansari, and Juhi Yasmeen. “Enhancing or Impairing? Exploring Indian EFL Learners’ Academic Writing Narratives with ChatGPT.” Cogent Education 12, no. 1 (2025): 2514329. https://doi.org/10.1080/2331186X.2025.2514329.
Konca, Ahmet Sami, Ahmet Simsar, Reem Alhajji, and Afra Al Mansoori. “Cross-Cultural Perspectives on AI Adoption in Teacher Education: A Comparative Study of Pre-Service Teachers in Turkey and the United Arab Emirates.”
Interactive Learning Environments 33, no. 10 (2025): 5820–46. https://doi.org/10.1080/10494820.2025.2488143.
Krstinić, Marija, and Lucija Bačić. Understanding the Language Gap in Artificial Intelligence. 19.12.2025.
Liaqat, Amna, and Cosmin Munteanu. “Leveraging Peer Support for Mature Immigrants Learning to Write in Informal Contexts.” Proceedings of the ACM on Human-Computer Interaction 4, no. CSCW2 (2020): 1–24. https://doi.org/10.1145/3415177.
Miranda, Sergio, and Rosa Vegliante. “Leveraging AI-Generated Virtual Speakers to Enhance Multilingual E-Learning Experiences.” Information 16, no. 2 (2025): 132. https://doi.org/10.3390/info16020132.
Mirnig, Alexander G., Alexander Meschtscherjakov, Daniela Wurhofer, Thomas Meneweger, and Manfred Tscheligi. “A Formal Analysis of the ISO 9241-210 Definition of User Experience.” Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, April 18, 2015, 437–50. https://doi.org/10.1145/2702613.2732511.
Özyurt, Sinan. “AI-Assisted English Language Learning for Cross-Cultural Medical Education in Multilingual Settings.” Experimental and Applied Medical Science 5, no. 2 (2024): 83–92. https://doi.org/10.46871/eams.1464830.
Prather, James, Brent N. Reeves, Paul Denny, et al. “Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners.” arXiv:2412.12800. Preprint, arXiv, December 17, 2024. https://doi.org/10.48550/arXiv.2412.12800.
Rivero, Edward, and Peng Yin. “Navigating the Contradictions of AI: Critiquing AI’s Standardized English and Developing Creative Bilingual Possibilities.” Frontiers in Education 10 (July 2025): 1616458. https://doi.org/10.3389/feduc.2025.1616458.
Saddhono, Kundharu, Muhammad Rohmadi, Try Annisa Lestari, Kaleb E. Simanungkalit, and Indriyo K. Sukmono. “The Role of AI in Facilitating Multilingual Literacy and Cross-Cultural Understanding.” 2024 International Conference on IoT, Communication and Automation Technology (ICICAT), November 23, 2024, 366–71. https://doi.org/10.1109/ICICAT62666.2024.10923254.
Saini, Mohit. Educators and AI in Collaboration: Enhancing Multilingual Teaching and Learning in Higher Education Through Natural Language Processing. 3, no. 1 (2025).
Schmager, Stefan, Ilias O. Pappas, and Polyxeni Vassilakopoulou. “Understanding Human-Centred AI: A Review of Its Defining Elements and a Research Agenda.” Behaviour & Information Technology 44, no. 15 (2025): 3771–810. https://doi.org/10.1080/0144929X.2024.2448719.
Shoeibi, Nastaran, Roberto Therón Sánchez, and Francisco José Garcia-Peñalvo. Evaluating the Effectiveness of Human-Centered AI Systems in Education. 2023.
Virvou, Maria. “Artificial Intelligence and User Experience in Reciprocity: Contributions and State of the Art.” Intelligent Decision Technologies 17, no. 1 (2023): 73–125. https://doi.org/10.3233/IDT-230092.
Youness Moudettir, Siham Ouhrir, and Said Lotfi. “Enhancing Cognitive Ergonomics and Pedagogical Quality a Comprehensive Evaluation Framework for Technological Pedagogical Tools in Physical Education.” Cuestiones de Fisioterapia 54, no. 3 (2025): 5007–29. https://doi.org/10.48047/53m9x307.
Zhang, Xinyu. “Leveraging AI Tools for Discourse Analysis in Early Childhood Bilingual Education: Enhancing Language Development.” Journal of Education and Educational Policy Studies 2, no. 1 (2024): 24–32. https://doi.org/10.54254/3049-7248/2/2024011.