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PAPEL: A Collaborative System for Parental Guidance during Preschool Play-Based English Learning
June 10, 2026 ยท Grace Period ยท ๐ CSCW 2026 / To appear in Proceedings of the ACM on Human-Computer Interaction
Authors
Xutong Wang, Yu Mei, Qinwei Li, Muyu Liu, Xiwen Yao, Chang Liu, Zhoutong Ye, Jie Cai, Chun Yu, Yuanchun Shi
arXiv ID
2606.11896
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
CSCW 2026 / To appear in Proceedings of the ACM on Human-Computer Interaction
Abstract
Play-based parent-child interaction offers preschoolers rich opportunities for everyday foreign language learning, yet many parents struggle to turn open-ended play into effective English-as-a-Foreign-Language (EFL) learning experiences at home. To explore how AI might support this process, we conducted formative studies through interviews and a Wizard-of-Oz study. We identified four key challenges: content selection, language expression, balancing instruction and play, and problem solving. To address these challenges, we present PAPEL, a parent-AI collaborative system that grounds suggestions in the ongoing play scene and organizes support into four core modules: content generation, language adaptation, balance assessment, and extended response. In a counterbalanced within-subjects study with 16 parent-child dyads, PAPEL was associated with more integrated parent utterances that combined playful and instructional content, as well as more parent-child conversational turns, than the lightweight chatbot baseline used in our study.
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