Ongoing Research Projects
Most recently, the projects that I work on in focus on advancing our understanding of childhood learning and cognition with AI technologies.
Children’s STEM Learning with Conversational Technologies
This project, headed by Dr. Mark Warschauer and Dr. Ying Xu, and partnered with PBS Kids, investigates the use of conversational agents to support children’s learning during interactive educational television consumption. The end goal of this project is to distribute the conversational videos as publicly accessible content via PBS KIDS platforms to millions of children across the country.
Conversational Agents as Bilingual Reading Partners
To enhance children’s home literacy environments, this project, led by Ying Xu, explores the use of conversational agents to promote language learning through interactive, bilingual English-Spanish storybook reading. Drawing on the principles of dialogic reading, Xu has developed, implemented, and evaluated fully automated smart speaker reading companions that not only narrate stories to children but also engage them in meaningful, open-ended conversations in both languages.
Patterns of Neural Engagement During Reading with AI
This project investigates the neural responses of children during interactions with both AI and human partners. The current study, led by Dr. Chi-Lin Yu of OSU, looks at how children's developing brains process social interactions with both humans and AI, focusing on the differences in neural and behavioral responses. By combining neuroimaging techniques like functional near-infrared spectroscopy (fNIRS) with naturalistic tasks such as story-listening and real-time verbal interactions, the project aims to uncover the mechanisms underlying children’s social communication in ecologically valid contexts.
Understanding and Being Understood: AI and the Child’s Perspective
This project explores two interrelated efforts to build more ethical AI systems for children. One thread examines how children perceive AI agents—how they assign human-like qualities, form relationships, and navigate trust. We study the social and cognitive processes that shape these interactions, especially when AI begins to feel “too human.” The second line of investigation focuses on the cultural and linguistic dimensions of fairness in AI. We analyze how bilingual and dialect-diverse children experience speech recognition systems, surfacing patterns of exclusion and bias. This work asks how AI might be designed to better serve—and be accountable to—diverse young users. Together, these strands offer a broader view of what ethical AI means when the users are children: not just fair or accurate, but attentive to the ways young people relate to and are represented by intelligent systems.
Educational Storytelling: The Role of Generative AI in Children's Learning
This research, led By Dr. Ying Xu, aims to explore how large language models (LLMs) and generative AI can impact children's learning. As an initial step, we have launched a study that involves using generative AI to co-create STEM-focused narratives with children. To ensure the AI-generated content is educationally enriching, we experimented with various strategies, including theory-based prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques. These methods help optimize the AI's dialogue output to better support children's educational experiences.
Generative AI and Youth Learning Across the Globe
In this series of studies, we set out to explore how adolescents are using AI in their learning processes and understand the individual, social, and contextual factors that shape how and why students choose to engage with AI in the first place. The project aims to generate actionable insights to support Ministries of Education in developing inclusive, evidence-based AI integration strategies in schools. My role focuses on survey development, multilingual accessibility, and framing the findings in ways that support ethical and equitable AI adoption in education systems.
2017–2023: Does who you are talking to affect what you remember?
Basque Center on Cognition, Brain, and Language & University of the Basque Country
Explored how speaker characteristics affect cognitive processes in attention and memory using behavioral and electrophysiological techniques.
2016–2017: Age-related changes in cognitive and sensory processing
Indiana University Bloomington
Investigated links between sensory processing and cognition in aging adults through cognitive batteries and sensory tests.
2014–2017: Phonotactic repairs in L2 learners of English
Indiana University Bloomington
Studied the lexical encoding of perceptual epenthetic vowels in English as a second language learners.
2013–2017: Visual perception and chronic cannabis use
Indiana University Bloomington
Researched the effects of long-term cannabis use on perceptual, structural, and cognitive processes using EEG and eye tracking data.
Past Research Highlights
With a background in linguistics and cognitive science, much of my past research experience focused on investigating cognitive mechanisms of multilingual processing.
Selected Publications & Presentations
Thomas, T., Martin, C. D., & Caffarra, S. (2025). The impact of speaker accent on discourse processing: A frequency investigation. Brain and Language, 260, 105509. [DOI]
Xu, Y., Thomas, T., Yu, C. L., & Pan, E. Z. (2025). What makes children perceive or not perceive minds in generative AI? In Computers in Human Behavior: Artificial Humans. [DOI]
Xu, Y., Thomas, T., Li, Z., Chan, M., Lin, G., & Moore, K. (2024). Examining children’s perceptions of AI-enabled interactive media characters. In International Journal of Child-Computer Interaction. [DOI]
Thomas, T., Takahesu-Tabori, A., Stoehr, A., & Xu, Y. (2025). The impact of voice onset time variability on ASR performance in bilingual Spanish-English children. Oral presentation at ISB15, Donostia–San Sebastián.
Li, Z., Thomas, T., Yu, C. L., & Xu, Y. (2024, June). “I Said Knight, Not Night!”: Children’s Communication Breakdowns and Repairs with AI Versus Human Partners. In Proceedings of the 23rd Annual ACM Interaction Design and Children Conference. [DOI]
Thomas, T., Takahesu-Tabori, A., Stoehr, A., & Xu, Y. (2024). The impact of bilingual language proficiency on ASR accuracy in children. ISBPAC, Swansea.