Founded in 2024, the AILE Lab investigates how artificial intelligence can serve as a learning partner in children’s literacy learning and development.

What We Study

Conversational AI for Literacy Learning

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.

Child-AI Interaction

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.

AI-Literate Teacher Preparation

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.

Current Projects

Home Literacy in the Age of AI

In a study of 74 families with children ages 5–7, we examined how print-based activities, digital media, and AI use relate to early literacy skills. AI use alone was not significantly associated with the literacy outcomes measured. This work informs our focus on purposeful learning experiences, caregiver participation, and equitable access to resources - not technology adoption alone.

View paper

Understanding Children’s Perspectives on AI Learning Partners

We investigate how young children understand the AI systems they learn with. Following six weeks of home use, children and caregivers explained what made a conversational AI seem human-like - or not. Children emphasized physical presence and the distinction between people and computers, while caregivers focused on conversational performance. These perspectives inform developmentally responsive, human-centered design for children’s learning.

View paper

Digital Tools for Bilingual Language and Literacy Assessment

We explore how digital tools can help families and researchers understand bilingual children’s language skills as a foundation for literacy learning. In a collaborative study of MERLS, a web-based Mandarin-English language screener, we examined parent–child interactions and assessment reliability across in-person and remote settings. This work informs AILE’s broader design goals for inclusive, family-centered AI learning tools that respond to children’s diverse language backgrounds.

View paper

Parent–Child–AI Interaction in Everyday Learning

Through interviews with parents of children ages 6–13, we explored how families use ChatGPT for questions, schoolwork, storytelling, and play. The study examines both shared parent–child use and children’s independent interaction, highlighting how caregiver mediation shapes AI experiences at home. These insights inform our work on family-centered AI that supports children’s curiosity, language-rich conversation, and responsible engagement with technology.

View paper

Meet Our Team

Who We Are

Bringing 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.

AILE Lab faculty director and student researchers gathered on campus
Dr. Shuang Quan, AILE Lab Director and Principal Investigator

Lab Director & PI

Dr. Shuang Quan

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.

Lab Members

Laney E. Gerdich

Laney E. Gerdich

Early Childhood Education

Laney explores how AI affects learning and how research insights can inform her future teaching.

Tatum E. Livelsberger

Tatum E. Livelsberger

Early Elementary Education & Special Education

Tatum connects elementary and special education with leadership and learning center experience while exploring AI in student learning.

Skylar Grabarski

Skylar Grabarski

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.

Claire Smith

Claire Smith (she/her)

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.

Sarah F. Bradley

Sarah F. Bradley

Early Education & Special Education

Sarah is interested in education’s power to expand access and in supporting meaningful learning opportunities for all students.

Emma L. Childers

Emma L. Childers

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.

Courtney S. Clippinger

Courtney S. Clippinger

Early Childhood Education

Courtney is building research skills that will strengthen her future classroom practice and support young learners.

Maddy C. Detz

Maddy C. Detz

Early Childhood Education

Maddy looks forward to contributing to collaborative research and applying its insights in her future work as an educator.

Ava S. Gummer

Ava S. Gummer

Early Education & Special Education

Ava is interested in understanding how artificial intelligence can shape student learning across inclusive educational settings.

Hannah F. Johnston

Hannah F. Johnston

Early Elementary Education

Hannah advocates for inclusive classrooms and explores how advancing technology can serve as a thoughtful instructional tool.

Emily D. Ketrow

Emily D. Ketrow

Early Education

Emily brings a longstanding passion for teaching and enthusiasm for applying AI knowledge in her future classroom.

Aaliyah D. McGee

Aaliyah D. McGee

Early Elementary Education

Aaliyah is eager to explore innovative, thoughtful ways to integrate artificial intelligence into classroom learning.

Jayden M. Strausbaugh

Jayden M. Strausbaugh

Computer Science

Jayden explores educational AI use cases and helps implement technology for the lab’s learning interventions.

Alisyn S. Wildner

Alisyn S. Wildner

Early Childhood Education & Special Education

Alisyn brings experience working with children and explores how AI can support thoughtful future classroom practice.