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.

翻译：基于游戏的亲子互动为学龄前儿童提供了丰富的日常外语学习机会，但许多家长难以将开放式游戏转变为有效的家庭英语作为外语（EFL）学习体验。为探索人工智能如何支持这一过程，我们通过访谈和"巫师之奥"（Wizard-of-Oz）研究开展了形成性调研，识别出四大关键挑战：内容选择、语言表达、教学与游戏平衡、以及问题解决。针对这些挑战，我们提出PAPEL这一家长-人工智能协作系统，其基于当前游戏场景提供建议，并将支持功能组织为四大核心模块：内容生成、语言适配、平衡性评估与扩展应答。在包含16对亲子组的平衡受试者内研究中，相较于本研究所采用的轻量级聊天机器人基线，PAPEL展现出更多融合游戏性与教学内容的整合性家长话语，以及更多的亲子对话轮次。