AI vs. Parent: Supporting Early Literacy at Home Through Conversational Agents

• In Event: AERA Poster Session Saturday 9:45 am
  In Poster Session: AI and Technology Integration in K-12 Education

Abstract

This study developed an LLM-powered conversational agent to support children’s formal home literacy activities and examined its instructional delivery and learning outcomes compared with human caregivers using a within-subject experimental design. Data were collected from 10 children (aged 3.7 to 7.7 years) across 150 learning sessions over six weeks in home settings. Results showed that AI and parents delivered structured instruction with comparable fidelity, but younger children yielded a better outcome learning with parents, while older children performed equally well or better with AI. These findings highlight AI’s potential as a scalable tool for formal home literacy practices, while underscoring the continued importance of parental involvement, especially for younger learners, and the need for age-responsive AI design.

Authors

• Shuang Quan, Juniata College

• Laney E. Gerdich, Juniata College

• Tatum E. Livelsberger, Juniata College

• Xintian Tu-Shea, University at Buffalo - SUNY

• Qingxiao Zheng, University at Buffalo - SUNY

• Yao Du, University of Southern California

• Yi Ding, Fordham University