发表机构
The Hong Kong University of Science and Technology (Guangzhou); Nan Kai university; The Hong Kong University of Science and Technology; Tsinghua University（香港科技大学（广州）; 南开大学; 香港科技大学; 清华大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本综述基于活动理论分析53项HCI研究，揭示LLM在家庭教育中通过对话与具身系统支持互动、重新分配教育劳动，但持续个性化与规则协商证据有限。
AI 中文摘要
大语言模型（LLMs）日益介入家庭教育，然而人机交互（HCI）领域尚未系统性地解释围绕这些模型所产生的教育互动。本范围综述分析了来自19个 venues 的6,540条记录中的53项HCI研究。借助活动理论和AODM方法，该综述将参与者与教育对象同中介、劳动和规则相关联。我们发现，现有文献聚焦于亲子互动以及语言、AI素养和关系学习。LLMs的引入使得对话式、具身式和空间化系统能够从不断展开的互动情境中生成支持。LLMs重新分配了教育劳动，而家庭和机构规则则使家长和专业人员在解释输出以及决定其如何进入实践方面承担主要责任。跨家庭和教育目的的证据仍然有限，尤其是在持续个性化、修复劳动以及家庭如何协商权威和规则方面。该综述提供了一个框架，用以解释LLM能力如何通过家庭参与得以组织化。
英文摘要
Large language models (LLMs) are increasingly involved in family education, yet HCI has not systematically explained the educational interactions that emerge around them. This scoping review analyzes 53 HCI studies from 6,540 records across 19 venues. Using activity theory and AODM, it relates participants and educational objects to mediation, labour, and rules. We find that the literature centers on child--parent interaction and on language, AI literacy, and relational learning. The introduction of LLMs enabled conversational, embodied, and spatial systems to generate support from the context of an unfolding interaction. LLMs redistributed educational labour, while family and institutional rules left parents and professionals responsible for interpreting outputs and deciding how they entered practice. Evidence across families and educational purposes remains limited, especially on sustained personalization, repair labour, and how families negotiate authority and rules. The review offers a framework explaining how LLM capabilities become organized through family participation.
