Family learning takes place in everyday routines where children and caregivers read, practice, and develop new skills together. Despite growing interest in AI tutors, most existing systems are designed for single learners or classroom settings and do not address the distributed planning, coordination, and execution demands of learning at home. This paper introduces ParPal, a human-centred, LLM-powered system that supports multi-actor family learning by decomposing learning goals into actionable subtasks, allocating them across caregivers under realistic availability and expertise constraints, and providing caregiver-in-the-loop tutoring support with visibility into individual and collective contributions. Through expert evaluation of generated weekly learning plans and a one-week field deployment with 11 families, we identify systematic failure modes in current LLM-based planning, including misalignment with role expertise, unnecessary or costly collaboration, missing pedagogical learning trajectories, and physically or temporally infeasible tasks. While ParPal improves coordination clarity and recognition of caregiving effort, these findings expose fundamental limitations in how current LLMs operationalize pedagogical knowledge, reason about collaboration, and account for real-world, embodied constraints. We discuss implications for human-centred AI design and AI methodology, positioning multi-actor family learning as a critical testbed for advancing planning, adaptation, and pedagogical structure in next-generation AI systems.

翻译：家庭学习发生于日常惯例中，儿童与照料者共同阅读、练习并发展新技能。尽管人们对人工智能导师的兴趣日益增长，但现有系统大多为单一学习者或课堂环境设计，未能满足家庭学习中分布式规划、协调与执行的需求。本文介绍ParPal，一个以人为中心、由大语言模型驱动的系统，它通过将学习目标分解为可执行的子任务，在现实的可用性与专业能力约束下将其分配给不同照料者，并提供照料者在环的辅导支持，同时使个体与集体贡献可见，从而支持多方参与的家庭学习。通过对生成的周度学习计划进行专家评估，以及对11个家庭为期一周的实地部署，我们识别出当前基于大语言模型的规划中存在的系统性失效模式，包括与角色专业能力不匹配、不必要或高成本的协作、教学学习轨迹的缺失，以及物理或时间上不可行的任务。尽管ParPal提升了协调的清晰度与对照料者付出的认可，但这些发现揭示了当前大语言模型在如何将教学知识操作化、对协作进行推理以及考虑现实世界中具身约束方面存在根本性局限。我们讨论了其对以人为中心的人工智能设计与人工智能方法论的意义，并将多方参与的家庭学习定位为推动下一代人工智能系统中规划、适应与教学结构发展的关键试验场。