Exploring how artificial intelligence can transform
children’s literacy learning
Founded in 2024, the AILE Lab investigates how artificial intelligence can serve as a learning partner in children’s literacy learning and development.
We design and evaluate multimodal conversational AI learning systems that adopt structured literacy and multisensory pedagogy to support children’s foundational literacy skills. Our current work includes the design and implementation of Vovo, an AI-enhanced learning system that provides interactive and adaptive learning experiences to support children’s vocabulary development.
We investigate how children interact with AI learning partners, how they make sense of these technologies, and how AI can respond to their learning and developmental needs. Our work centers children’s perspectives to inform thoughtful, age-appropriate learning experiences.
Preparing future teachers to understand, evaluate, and integrate AI critically, effectively, and responsibly in their teaching. We connect interdisciplinary research with teacher preparation to support informed decisions about AI in young children’s learning.
In this six-week home-based study, we evaluated Vovo, a conversational AI system grounded in structured literacy pedagogy, with children ages 3–7. Across 150 AI- and parent-led learning sessions, we examined how conversational AI supports vocabulary learning, how its instructional interactions compare with those of caregivers, and how children and families experience AI as a literacy learning partner.
We examined how traditional, digital, and AI-integrated home literacy environments relate to children’s literacy development. The study explores how emerging AI technologies are becoming part of children’s home learning environments and what their growing presence may mean for literacy development.
View paperWe explored how young children perceive and make sense of conversational AI, with particular attention to whether and why they attribute human-like qualities to AI. The study provides a child-centered perspective on how young learners understand the increasingly blurred boundaries between humans and artificial agents.
View paperBringing together researchers and students across Education, Computer Science, and related fields, the lab designs and evaluates pedagogy-informed AI learning systems that support children’s language and cognitive development across home, school, and community contexts.
Dr. Shuang Quan is an Assistant Professor of Education at Juniata College. She received her Ph.D. from Fordham University. Her research explores how generative AI can support young children’s literacy learning and development. Through AILE, she mentors Education and Computer Science students in interdisciplinary research at the intersection of AI, literacy, and child development.
Early Childhood Education
Laney explores how AI affects learning and how research insights can inform her future teaching.
Early Elementary Education & Special Education
Tatum connects elementary and special education with leadership and learning center experience while exploring AI in student learning.
Biology & Education
Skylar is a sophomore studying Biology and Education. Through her work with the AILE Lab, she hopes to build her research skills and deepen her understanding of how AI can support learning in home environments.
Early Childhood Education
Claire is a sophomore majoring in Early Childhood Education. As a member of the AILE Lab, she is interested in exploring how AI and emerging technologies can support young children’s learning and literacy development.
Early Education & Special Education
Sarah is interested in education’s power to expand access and in supporting meaningful learning opportunities for all students.
Early Childhood Education & Special Education
Emma brings experience supporting an elementary after-school program and is interested in responsible uses of AI in future classrooms.
Early Childhood Education
Courtney is building research skills that will strengthen her future classroom practice and support young learners.
Early Childhood Education
Maddy looks forward to contributing to collaborative research and applying its insights in her future work as an educator.
Early Education & Special Education
Ava is interested in understanding how artificial intelligence can shape student learning across inclusive educational settings.
Early Elementary Education
Hannah advocates for inclusive classrooms and explores how advancing technology can serve as a thoughtful instructional tool.
Early Education
Emily brings a longstanding passion for teaching and enthusiasm for applying AI knowledge in her future classroom.
Early Elementary Education
Aaliyah is eager to explore innovative, thoughtful ways to integrate artificial intelligence into classroom learning.
Computer Science
Jayden explores educational AI use cases and helps implement technology for the lab’s learning interventions.
Early Childhood Education & Special Education
Alisyn brings experience working with children and explores how AI can support thoughtful future classroom practice.