PACEE: Parent-Centered AI Scaffolding for Emotion Education in Early Childhood Conversations
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arXiv
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| Format: | Preprint |
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2025
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| author | Mei, Yu Wang, Xutong Zhang, Ziyao Fu, Yiming Wang, Shiyi Wan, Qingyang Lan, Qinghuan Liu, Chang Cai, Jie Yu, Chun Shi, Yuanchun |
| author_facet | Mei, Yu Wang, Xutong Zhang, Ziyao Fu, Yiming Wang, Shiyi Wan, Qingyang Lan, Qinghuan Liu, Chang Cai, Jie Yu, Chun Shi, Yuanchun |
| contents | Emotion education is critical for children aged 3 to 6. However, existing technologies largely focus on children's direct interaction with AI, overlooking the central role of parents in guiding early emotional development at home. To address this gap, we conducted co-design sessions with five kindergarten teachers and five parents to identify key parental challenges and opportunities for AI support in family emotion education. Based on these insights, we developed PACEE, an LLM-based assistant designed to support parents in guiding children's emotional development through conversations, rather than directly interacting with children. PACEE provides parent-centered AI scaffolding that supports parents in real-time conversation through personalized guidance, post-hoc reflection through trackable feedback, and understanding children's emotional states through modeling. We evaluated PACEE with 16 families. Results show that PACEE enhances parent-child engagement, fosters deeper emotional communication, and improves parents' expertise and overall experience in guiding their children. Our findings extend emotion coaching practices to the context of generative AI and offer design insights for building AI systems that support parent-centered family education. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_14414 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PACEE: Parent-Centered AI Scaffolding for Emotion Education in Early Childhood Conversations Mei, Yu Wang, Xutong Zhang, Ziyao Fu, Yiming Wang, Shiyi Wan, Qingyang Lan, Qinghuan Liu, Chang Cai, Jie Yu, Chun Shi, Yuanchun Human-Computer Interaction Emotion education is critical for children aged 3 to 6. However, existing technologies largely focus on children's direct interaction with AI, overlooking the central role of parents in guiding early emotional development at home. To address this gap, we conducted co-design sessions with five kindergarten teachers and five parents to identify key parental challenges and opportunities for AI support in family emotion education. Based on these insights, we developed PACEE, an LLM-based assistant designed to support parents in guiding children's emotional development through conversations, rather than directly interacting with children. PACEE provides parent-centered AI scaffolding that supports parents in real-time conversation through personalized guidance, post-hoc reflection through trackable feedback, and understanding children's emotional states through modeling. We evaluated PACEE with 16 families. Results show that PACEE enhances parent-child engagement, fosters deeper emotional communication, and improves parents' expertise and overall experience in guiding their children. Our findings extend emotion coaching practices to the context of generative AI and offer design insights for building AI systems that support parent-centered family education. |
| title | PACEE: Parent-Centered AI Scaffolding for Emotion Education in Early Childhood Conversations |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2511.14414 |