AI and Multilingualism Lab
Innovating Language, Technology and Human Communication
The SILC AI & Multilingualism Lab is an interdisciplinary research hub dedicated to advancing human-centered artificial intelligence in language education, bilingual communication, cultural studies and the humanities.
Bringing together faculty, graduate students and collaborators across ASU and international institutions, the lab integrates linguistics, artificial intelligence, computational modeling, literature, education and public health.
The lab’s mission is to develop ethical, transparent and socially responsible AI tools that enhance multilingual learning, support vulnerable communities and deepen our understanding of human communication across languages and cultures. Through collaboration with ASU’s School of Computing and Augmented Intelligence (SCAI), the School of Mathematical and Statistical Sciences, Biomedicine and global research partners, the lab positions SILC at the forefront of AI-driven multilingual research.
Students at all levels actively participate in research, gaining hands-on experience in computational linguistics, AI development, educational technology and digital humanities — preparing them for careers in global industries, education, healthcare and technology.
Our impact
The SILC AI & Multilingualism Lab:
- Advances ethical, human-centered AI
- Supports multilingual and low-resource communities
- Bridges the humanities and computational sciences
- Trains students for careers in global industries, education, healthcare, and technology
- Positions SILC as a leader in the future of language education and AI
By combining multilingual expertise with cutting-edge AI research, the lab positions SILC as a national leader in the future of language, technology and global communication.
Director of the Lab
Marta Tecedor Cabrero
Associate Professor, School of International Letters and Cultures
Marta Tecedor is an associate professor in Spanish linguistics. Her primary area of research is computer-assisted language learning with a focus on flipped and online curricular models and AI-enhanced language learning. Over the past few years, her work on these topics has appeared in peer-reviewed journals, such as Applied Linguistics, Computer Assisted Language Learning, Foreign Language Annals, ReCALL and Pragmatics.
Contact: [email protected]
Research areas and faculty projects
AI and Bilingual Communication
Lead: Olga Kellert
This research program uses large language models (LLMs) and computational tools to study bilingual communication, particularly in low-resource languages.
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Impact:
- Advancing research on code-switching
- AI tools for multilingual analysis
- Training students in computational linguistics
Key initiatives include:
- BILINGUA Parser – Computational modeling of bilingual language structure
- Multilingual Topic Modeling – AI-driven analysis of multilingual discourse
- Agentive AI – Investigating cognitive and agentive dimensions of AI in bilingual processing
These projects bring together SILC, SCAI, the University of A Coruña (Spain) and international collaborators.
Contact:
Olga Kellert
Associate Professor,
School of International Letters and Cultures
David Parks
Learning Support Services Head,
School of International Letters and Cultures
AI and Health Education in Vulnerable Bilingual Communities
Lead: Olga Kellert
This internationally funded research applies AI and computational methods to improve health communication in vulnerable bilingual communities, particularly Spanish–Quechua speakers in Ecuador and Peru.
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Impact:
- AI for public health communication
- Support for low-resource bilingual communities
- Global partnerships in Peru, Ecuador and Germany
Originally supported by the German Research Foundation (DFG), the project combines linguistics, public health, and computational analysis to examine how bilingual populations access and interpret health information.
At ASU, the project continues through advanced computational and statistical modeling in collaboration with students in mathematics, statistics, and biomedicine.
Contact:
Olga Kellert
Associate Professor,
School of International Letters and Cultures
AI and Human-Centered Language Education
Lead: Olga Kellert
This research explores how authentic student–teacher interaction data can be used to build reliable datasets for AI applications in language education.
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The goal is to design transparent, interpretable, and ethically responsible AI tools that support human-centered language learning rather than replace it.
Impact:
- Ethical AI for language education
- Transparent AI tutoring systems
- Student training in AI + linguistics research
By systematically analyzing classroom interactions, this work contributes to the development of AI-assisted tutors that enhance student engagement, communication, and learning outcomes.
This interdisciplinary initiative involves collaboration between SILC and SCAI, with graduate student researchers contributing across linguistics and artificial intelligence. Faculty collaborators include Marta Tecedor and Michael Gradoville.
Contact:
Olga Kellert
Associate Professor,
School of International Letters and Cultures
AI Conversation Partners: Japanese ChatGPT
Lead: Aya Nakanishi McDaniel
The Japanese program has begun to test the use of similar prompt engineering language with ASU’s OpenAI ChatGPT, building on the initial version of Language Buddy that was tested in German courses.
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Contact:
Aya Nakanishi McDaniel
Associate Teaching Professor,
School of International Letters and Cultures
AI Conversation Partners: Language Buddy
Lead: Kristin Elwood, along with the German, French and Spanish programs
Developed as part of the ASU AI Innovation Challenge through the German program and initially pilot tested in their courses, SILC has coordinated with EdPlus, Enterprise Technology and the Learning Engineering Institute to expand the Language Buddy project.
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This AI agent prototype is integrated in Canvas to allow online students to experience real time conversation practice based on pre-set curricular scenarios. Mariana Bahtchevanova, Teaching Professor of French, and Duncan Lien, Instructor of German, provided initial beta testing, and we are currently conducting data analysis in sections of SPA 101 taught by Steven Flanagan, Associate Teaching Professor and Director of Spanish Second Language Acquisition, and Luiza Zanchi Instructor of Spanish.
Contact:
Kristin Elwood
Clinical Associate Professor,
School of International Letters and Cultures
AI Conversation Partners: Student Conversation Practice
Lead: David Parks
Being developed by SILC Learning Support Services, this project aims to create an AI-powered foreign-language practice tool for students who want extra, low-stakes conversation practice outside of class.
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Impact:
- AI conversation partners for language learners
- Increased student speaking practice
- Technology-enhanced curriculum innovation
The intent is to provide interactive, scaffolded, voice-based dialogues that adjust in real time to a learner’s level and interests, helping build listening and speaking skills through natural conversational flow.
Contact:
Learning Support Services Head,
School of International Letters and Cultures
AI Conversation Partners: Student Tutoring and Support
Lead: David Parks
Being developed by SILC Learning Support Services, this project aims to create an AI-powered tutoring tool for language learners. The intent is to help students get answers to specific language questions, help clarify what kind of support they might need, and connect them to targeted practice, learning guidance, and study strategies.
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Impact:
- AI tutoring and support for language learners
- Increased student engagement
- Technology-enhanced curriculum innovation
The intent is to help students get answers to specific language questions, help clarify what kind of support they might need, and connect them to targeted practice, learning guidance, and study strategies. The tool will also point students to relevant SILC/ASU resources and opportunities.
Contact:
Learning Support Services Head,
School of International Letters and Cultures
AI Language Skills, Lexicography and Lexical Generation
Lead: Danko Šipka
This research applies AI to practical language learning, lexicology and lexicography and the creation of new words.
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Key projects include:
- AI Language Skills Tutoring – A project devoted to practical language learning
- AI Education and Facilitation – Enhancing AI prompting through education and knowledge base interventions, drawing on content and activities from a forthcoming lexicology and lexicography textbook under contract with Cambridge University Press
- AI Lexical Generation – Creating new words with AI, including cross-linguistic comparisons, primarily with English
Contact:
Danko Šipka
Professor of Slavic Languages and Applied Linguistics,
School of International Letters and Cultures
AI, Literature and Emotional Environments
Lead: Madalina Meirosu
This humanities-focused research explores how literature has historically shaped emotional responses to artificial beings and intelligent machines.
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Impact:
- Historical and cultural perspectives on AI
- Humanities-driven AI ethics and imagination
- Integration of AI tools into literature instruction
Book Project: Feeling AI: Environments of Emotion in Literature and Technology, 1815–1940
Examines how Central European literature embedded artificial beings in emotional and environmental contexts — shaping public perception of technology. Related work includes published scholarship on artificial bodies and emotion in German literature.
Courses such as:
- Artificial Humans and Emotion
- AI in Literature and Film
- AI, Power and the Human Imagination
extend this research into the classroom. Meirosu also developed Gigi the Study Buddy, a GPT-based writing companion for students.
Contact:
Madalina Meirosu
Assistant Professor,
School of International Letters and Cultures
AI-Mediated L2 Interaction & Communication
Lead: Marta Tecedor
This research cluster investigates how AI-powered tutors shape second language (L2) communication, perception and learning outcomes.
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Impact:
- Evidence-based AI integration in L2 curricula
- Research on digital literacy and learner psychology
- Pedagogical innovation grounded in interaction analysis
Key projects include:
AI-L2 Conversations & Willingness to Communicate
Examines how students’ attitudes toward AI influence their willingness to speak in AI-mediated vs. human interactions. Findings highlight the importance of digital literacy and learner disposition in AI-based education.
Sequence Organization in AI Conversations
Analyzes conversational structure in AI–learner exchanges using Conversation Analysis, exploring how learners treat AI as an interactional partner.
AI and L2 Speech Perception
Studies how dialect-specific AI bots influence learners’ perceptual adaptation to phonetic variation in Spanish.
Error Correction in AI Conversations
Investigates whether AI tutors can create meaningful form-focused learning episodes through corrective feedback.
Writing with AI (with Ilona Elola)
Examines how heritage and L2 learners use AI tools like ChatGPT during collaborative writing tasks, using Activity Theory to analyze decision-making and learning processes.
Contact:
Marta Tecedor Cabrero
Associate Professor,
School of International Letters and Cultures
Colonialism and Migration in a Global Perspective
Lead: Anita Huizar-Hernández
Colonialism has fundamentally shaped human mobility. Yet analysis of colonialism’s influence on contemporary migration politics and governance is highly uneven, being frequently discussed in some countries with evident colonial legacies, while rarely in others.
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Funded by the British Academy
Amid claims that settler and ex-metropole societies are “converging” in their approaches to migration, this project addresses major limitations in these debates by deepening the analysis historically and broadening it geographically.
Drawing on the humanities to excavate the complex social meanings and identities surrounding colonialism, and on the social sciences to analyse how these are mobilised, the project examines diverse settler and ex-metropole contexts across all six inhabited continents, many of which are rarely compared. It breaks new ground through a historically rooted global study illuminating the complex ways in which colonialism continues to shape migration governance.
The project also includes a computational component led by researchers at Universidad Adolfo Ibáñez in Chile, including Mayra Feddersen and Carla Sepúlveda. This strand builds on earlier research that created and analysed a corpus of South American immigration laws and regulations using collaborative human coding and natural-language-processing techniques. For the present project, the team is extending this methodological foundation and adapting its coding framework to investigate colonialism’s influence on migration governance. The revised codes are designed to identify how colonial histories, categories, assumptions and governing logics are expressed in immigration law across the project’s wider comparative settings. Expert team coding will produce the contextualised data needed to develop and evaluate AI-assisted analysis of the larger legal corpus, combining computational scale with historically and legally informed interpretation. This approach will enable systematic comparison of how colonial legacies persist, change or converge across settler and former metropolitan societies.
Contact:
Anita Huizar-Hernández
Associate Professor,
School of International Letters and Cultures
CulturaLens Project
Lead: Kristin Elwood and David Parks
The CulturaLens project is being developed as part of The College of Liberal Arts and Sciences AI Academy. This project explores how an interactive, AI-supported experience can help people navigate language and communication across different cultural contexts.
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Impact:
- Explore cross-linguistic competence and intercultural communication
- Encourage campus and community engagement
- Spotlight SILC courses, programs, and career fields
Through guided reflection rather than one-to-one translation, it aims to support learning and understanding while informing research on intercultural communication.
Contact:
Kristin Elwood
Clinical Associate Professor,
School of International Letters and Cultures
David Parks
Learning Support Services Head,
School of International Letters and Cultures
Emilio Villa International Research Center
Lead: Serena Ferrando
The Center brings together scholars working on the legacy of Emilio Villa, an experimental poet, artist, translator, and critic, whose work crossed languages and disciplines.
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Ferrando is currently contributing to the development of a virtual exhibit dedicated to Villa’s archive, held at the Biblioteca Panizzi in Reggio Emilia, Italy. The project explores how AI and digital tools can support archival research and improve access to complex multilingual materials as well as create new ways for students, researchers, and the broader public to engage with Villa’s work across different media and cultures.
Contact:
Serena Ferrando
Assistant Professor of Environmental Humanities and Italian,
School of International Letters and Cultures
Hylas Project: AI and Classical Languages
Lead: Mike Tueller
The Hylas Project is an AI-driven system that algorithmically scans ancient Greek and Latin poetry without human intervention. It has achieved 100% tested accuracy across a dataset of 250,000 lines of ancient poetry.
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Impact:
- AI applications in classical philology
- Digital humanities innovation
- Computational analysis of ancient texts
Currently, the project is being expanded with a more robust machine learning framework, advancing digital humanities research in classical studies.
Contact:
Mike Tueller
Professor of the Classics,
School of International Letters and Cultures
Invited Talk — September 11, 2026
Methods and Tools for Automatic Quality Assessment of Wikipedia Articles and Their Information Sources
Speaker: Dr. Włodzimierz Lewoniewski, Assistant Professor, Department of Information Systems, Poznań University of Economics and Business
The Multilingual AI Lab and the Digital Humanities Cluster hosted Dr. Lewoniewski for an invited talk on computational tools for assessing the quality of Wikipedia articles and the reliability of their information sources — of interest to faculty, students and researchers working in digital humanities, multilingual data, information quality, AI-assisted knowledge production and computational approaches to online encyclopedic content.
Location: Durham Hall 135, The Collaboratory
Hosted by: Multilingual AI Lab (SILC) and Digital Humanities Cluster (Humanities Institute)
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