THE RESEARCH
Building on UCI research in early literacy and AI-supported dialogic learning, My Story Detective brings together Professor Young-Suk Kim’s foundational early-literacy research and the UCI Digital Learning Lab’s work with conversational agents. The project’s planned research will examine how these foundations can support children’s language, comprehension, and word reading.
PLANNED RESEARCH FOR MY STORY DETECTIVE
My Story Detective will be developed, studied, and refined alongside the educators and families who use it. The project will include stories from the established Story Detective and COMPASS collections, as well as The Science Adventures of Luna and Leo, a science storybook series designed for young children. The planned work will examine oral-language and word-reading supports alongside children’s engagement with stories and comprehension.
RESEARCH OVERVIEW
This project will refine My Story Detective with input from children, educators, and families, with attention to usability, accessibility, engagement, and fit in real learning settings.
The research will examine implementation in classrooms and family reading contexts, alongside resources that help educators and caregivers use the platform.
The project will study platform use, implementation, and children’s language and literacy development to guide ongoing improvement.
PROFESSOR YOUNG-SUK KIM’S EARLY LITERACY RESEARCH
Professor Young-Suk Kim’s research connects the language, knowledge, and word-reading skills that children draw on as they become readers.
RESEARCH OVERVIEW
Kim’s model brings together language comprehension, word reading, vocabulary, background knowledge, and higher-order thinking. It helps guide My Story Detective’s combined focus on making meaning and reading words.
These teacher-led interventions use stories to support vocabulary, grammar, text structure, inference, and comprehension monitoring. Their research-informed materials and prompts provide an important foundation for My Story Detective.
SELECTED PUBLICATIONS
Kim, Y.-S. G. (2020). Toward integrative reading science: The Direct and Indirect Effects Model of Reading. Journal of Learning Disabilities, 53(6), 469–491.
Kim, Y.-S. G. (2023). Simplicity meets complexity: Expanding the Simple View of Reading with the Direct and Indirect Effects Model of Reading. In S. Q. Cabell, S. B. Neuman, & N. Patton Terry (Eds.), Handbook on the science of early literacy (pp. 9–22). Guilford Press.
Kim, Y.-S. G., & Leachman, M. (2026). From ears to eyes: Supporting reading comprehension through systematic instruction on listening comprehension. In R. D. Silverman & K. Keane (Eds.), Language and Literacy Beyond Decoding: Evidence-Based Instruction in Grades PreK–6 (pp. 73–92). Guilford Press.
CONVERSE TO LEARN DIALOGIC READING RESEARCH
The UCI Digital Learning Lab’s Converse to Learn research explores how conversational agents can support children’s learning with stories, video, and shared reading. This research informs My Story Detective’s dialogue-based reading experience.
RESEARCH OVERVIEW
Converse to Learn research examines children’s story comprehension and engagement while reading with a conversational agent.
Studies compare children’s conversations with a conversational agent and a human reading partner, helping inform the design of story-centered exchanges.
Bilingual conversational-agent research explores ways to support vocabulary, engagement, and family conversation during shared reading.
SELECTED PUBLICATIONS
Xu, Y., Aubele, J., Vigil, V., Bustamante, A. S., Kim, Y.-S., & Warschauer, M. (2022). Dialogue with a conversational agent promotes children’s story comprehension via enhancing engagement. Child Development, 93(2), e149–e167.
Xu, Y., Wang, D., Collins, P., Lee, H., & Warschauer, M. (2021). Same benefits, different communication patterns: Comparing children’s reading with a conversational agent vs. a human partner. Computers & Education, 161, Article 104059.
He, K., Cervera, K., Levine, J., Xu, Y., Collins, P., & Warschauer, M. (2025). Promoting parent-child shared reading with a bilingual conversational agent. International Journal of Human-Computer Studies, 199, Article 103489.
Learn more about the Converse to Learn projectMY STORY DETECTIVE