Multilingual Education in the AI Era: Letter from the Editors
Laura B. Liu, Indiana University Columbus, US
Nelli Bondareva, University of the People, Pasadena, US
Kirti Kapur, National Council of Educational Research and Training, New Delhi, India
TESOL’s Fall 2026 Bi-Multilingual Education Interest Section (BMEIS) Newsletter, Multilingual Connections, builds on the Spring 2026 newsletter by continuing an exploration for how artificial intelligence is reshaping multilingual teaching and learning. This Fall edition pays particular attention to the roles of the learner and technology in the learning process, including what may be gained or lost in relation to cognitive development. This newsletter attends to when and how technology enhances learning -- such as mapping visuals complementing linguistic comprehension, or providing academic language as building blocks to support learner engagement in higher level cognitive discourses. At the same time, the articles in this newsletter raise questions as to when and how technology might minimize or hinder learning by acting as the cognitive processer in thinking spaces intended for the learner and the learner’s presumed development. How can educators and teacher educators determine when AI enhances learning and when it may compromise learning? How might practitioners leverage AI in ways that prioritize educational developmental outcomes as much as or more than performance outcomes?
This newsletter contributes to the landscape of academic perspectives on AI in education and multilingual education by inviting authors to move beyond general descriptions of AI tools to critically consider developmental outcomes – cognitive, linguistic, cultural, social, ethical – of AI use in education.
This newsletter invited submissions that addressed a variety of questions, including the following:
- How can AI support multilingual meaning-making without replacing learner voice, creativity, and agency?
- In what ways can AI strengthen translanguaging, biliteracy, and heritage language development?
- Which languages, language varieties, and cultural perspectives are represented in AI systems, and which remain marginalized or absent?
- What knowledge and professional judgment do teachers need when selecting AI tools for multilingual classrooms?
- How can educators evaluate whether an AI tool is linguistically inclusive, culturally responsive, and pedagogically appropriate?
- What forms of inequality may emerge when some learners, institutions, and communities have greater access to AI technologies than others?
- How can artificial intelligence be used to support multilingual education without reinforcing dominant language hierarchies?
The articles in this newsletter present unique perspectives that collectively consider how AI may be leveraged to support learning while addressing key questions about AI’s limitations and the complementarity of traditional instructional approaches to maintain a focus on developmental learning outcomes.
The first article in this newsletter, Preparing Multilingual Educators for GenAI Integration: Moving Beyond Tool Use Toward Professional Judgment by Alothman and Milman, provides professional guidance for educators seeking to engage generative artificial intelligence in ways that maintain teacher agency, promote equitable learning experiences, and keep teacher professional judgment central to responsible AI integration in education. The authors suggest a variety of ways GenAI can support multilingual learner education, such as adapting reading passages for specific proficiency levels, developing vocabulary activities, designing formative assessments, and drafting multilingual communications for families. This article resonates with others in the newsletter by encouraging educators to ensure that “technology enhances, rather than substitutes for, meaningful learning experiences” (para. 2), and that “professional development should guide educators to explore both the opportunities and challenges of GenAI” (para. 9). The authors provide guiding questions for this.
The second article, AI is Multilingual, But Is It Translanguaging? by Sarmiento Quezada, specifically examines GenAI’s capacity for translation, while distinguishing this ability from the learner’s practice of translanguaging as an asset for linguistic development. The author invites educators to consider when AI may serve as a translation tool and when it may take the place of the learner in meaning-making at pivotal moments --- and either enhance or minimize learning. The author invites educators to consider the “paradox” that “an AI-supported classroom might contain more languages than it did before GenAI without giving learners greater agency over how they use their repertoires” (para. 17), and encourages purposeful pedagogical engagement with AI. The third article, The Correcting Default: How AI’s Convenience May Narrow the Multilingual Educator’s Skill by Kavaklı Ulutaş, raises a related concern that AI’s language corrections are based on standard language data models favoring narrow ‘prestigious’ versions of language. The author invites educators to exercise professional discernment for how AI use may be leveraged to support inclusive language development valuing diverse forms of linguistic expression.
Finally, the fourth newsletter article, Who is the Human in the Loop? AI and the Future of Multilingual Education by Kapur, encourages practitioners and policy to keep community knowledge central to understanding how GenAI uses language so human linguistic agency is the driver of professional pedagogical practice. The author recognizes that “standard AI literacy focuses on prompting, spotting hallucinations and basic bias awareness” while “critical multilingual AI literacy asks a sharper question: who is the human in the loop, and what knowledge do they bring?” (para. 13) with consideration for representation, agency, and governance (para. 16). She offers a three-part framework for analysis that includes linguistic, communicative, and relational components of community knowledge. Together, these four articles highlight the value of AI to enhance learning, as well as concerns for AI use being prioritized over developmental learning. This emphasized point across all four articles raises considerations for educators regarding the role of humans and the role of technology in the learning process, as well as broader societal considerations for the nature of the human-technology relationship in K-12 classrooms and beyond.
UNESCO (2025a, 2025b) relatedly has called for a human-centered approach to AI that addresses inequalities in knowledge access and limited diversity of cultural expressions. Additional academic research on AI and multilingual education presents some promising practices in working toward UNESCO’s mandate. For example, one study on the implementation of an AI literacy summer camp for elementary and middle school youth in Southern California found benefits in pairing AI literacy and second language acquisition, particularly when using translanguaging, multimodal instruction, and creative storytelling (Ojeda-Ramirez, Ritchie, & Warschauer, 2024). International scholarship on AI use also raises good questions for when AI supports learning and when traditional instructional approaches are needed to attain developmental learning outcomes. For example, Yu, et al. (2025) examine ChatGPT use by educators in western China to conclude that the integration of ChatGPT in multilingual education should stay focused on the educational objectives and complement AI use with traditional teaching methods more attuned to cultural context and depth than AI. Additionally, Albedah (2025) conducted a systemic review of 161 international studies from 2015 to 2024 on AI-driven change in language education to find that AI technologies reduced learner anxiety through tools such as conversational agents, pronunciation support, and writing assistants --- the LLMs also demonstrated cultural misrepresentation, linguistic biases for high-resource languages, gender stereotyping, and gaps related to marginal languages, long-term educational impacts, and impacts on human interaction (Albedah, 2025).
The identified strengths and issues of AI use found in recent research warrant consideration by educators.
A helpful lens in this conversation may be the English Language Development (ELD) Standards Framework developed by the World-class Instructional Design and Assessment (WIDA) Consortium (2020), adopted as the ELD standards for 42 U.S. states and utilized by over 100 nations. WIDA encourages simultaneous content-language instruction and supports teachers in identifying interpretive and expressive language objectives in a lesson. This is a helpful step before considering how AI use might enhance developmental learning, rather than taking the place of it. For instance, AI use to translate a text may support a learner whose primary learning objective is to develop a thesis statement on the main theme of the text. AI translation of a text may hinder learning if text comprehension is at the learner’s zone of proximal development, and context clues should be used to facilitate interpretation of the text. In the absence of guidance, learners facing performance pressure may use AI for all tasks at the loss of developmental learning. The articles in this newsletter invite education policy makers and practitioners across grade levels and languages to consider how technology might be used to support developmental learning, rather than replacing learning with technology-generated performance.
References
Albedah, F. (2025). Artificial intelligence in language education: A systematic review of multilingual applications, large language models, and emerging challenges. Language Teaching Research Quarterly 49, 247–268. https://doi.org/10.32038/ltrq.2025.49.13
Ojeda-Ramirez, S., Ritchie, D., & Warschauer, M. (2024). AI literacy for multilingual learners: Storytelling, role-playing, and programming. The CATESOL Journal, 35(1), 1-11. https://doi.org/10.5070/B5.35861
UNESCO. (2025a). AI and education: Protecting the rights of learners. UNESCO Publishing. https://doi.org/10.54675/ROQH4287
UNESCO. (2025b). AI and the future of education: Disruptions, dilemmas and directions. https://doi.org/10.54675/KECK1261
WIDA. (2020). WIDA English language development standards framework, 2020 edition: Kindergarten–grade 12. Board of Regents of the University of Wisconsin System. https://wida.wisc.edu/sites/default/files/resource/WIDA-ELD-Standards-Framework-2020.pdf
Yu, H., Guo, Y., Yang, H., Zhang, W. & Dong, Y. (2025), Can ChatGPT revolutionize language learning? Unveiling the power of AI in multilingual education through user insights and pedagogical impact. European Journal of Education, 60: e12749. https://doi.org/10.1111/ejed.12749
Laura B. Liu is Associate Professor of Education and English as a New Language Program Coordinator at Indiana University Columbus. Her research focuses on glocalization, diversity sustaining practices, and teacher international professional development. Laura served as faculty at Beijing Normal University’s Center for Teacher Education Research after completing a postdoctoral degree there on teacher educator international professional development as 仁 (ren).
Nelli Bondareva is an English language educator, literacy specialist, and independent researcher with teaching experience in Armenia, Russia, China, and the United States. She designs literature-rich, student-centered lessons that build global competence and a love for reading. Nelli shares her work through conferences and publications, focusing on heritage language maintenance, translanguaging, and innovative approaches to literacy development for multilingual learners.
Kirti Kapur is a former Professor of English at NCERT, New Delhi, India. As a Fulbright Fellow 2021, she conducted research in multicultural education and TESOL at Hawaii Pacific University, USA. Her areas of work are the development of syllabi, textual materials, comparative research, and teachers’ handbooks. She has led over 100+ teacher training workshops across all stages of school education. She has contributed to over 90 papers (national and international) on cultural contexts and language learning. She has trained teachers from Afghanistan, Tibet, and Mauritius on making ELT effective and learner-centric in their context.