Characterizing LLM-Empowered Personalized Story Reading and Interaction for Children: Insights From Multi-Stakeholders' Perspective

要旨

Personalized interaction is highly valued by parents in their story-reading activities with children. While AI-empowered story-reading tools have been increasingly used, their abilities to support personalized interaction with children are still limited. Recent advances in large language models (LLMs) show promise in facilitating personalized interactions, but little is known about how to effectively and appropriately use LLMs to enhance children's personalized story-reading experiences. This work explores this question through a design-based study. Drawing on a formative study, we designed and developed StoryMate, an LLM-empowered personalized interactive story-reading tool for children, following an empirical study with children, parents, and education experts. Our participants valued the personalized features in StoryMate, and also highlighted the need to support personalized content, guiding mechanisms, reading context variations, and interactive interfaces. Based on these findings, we propose a series of design recommendations for better using LLMs to empower children's personalized story reading and interaction.

著者
Jiaju Chen
East China Normal University, Shanghai, China
Minglong Tang
East China Normal University, Shanghai, China
Yuxuan Lu
Northeastern University, Boston, Massachusetts, United States
Bingsheng Yao
Northeastern University, Boston, Massachusetts, United States
Elissa Fan
Lexington High School, Lexington, Massachusetts, United States
Xiaojuan Ma
Hong Kong University of Science and Technology, Hong Kong, Hong Kong
Ying Xu
University of Michigan, Ann Arbor, Michigan, United States
Dakuo Wang
Northeastern University, Boston, Massachusetts, United States
Yuling Sun
East China Normal University, Shanghai, China
Liang He
East China Normal University, Shanghai, China
DOI

10.1145/3706598.3713275

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713275

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Storytelling and Sense-Making

G302
6 件の発表
2025-04-28 20:10:00
2025-04-28 21:40:00
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