ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events
Woosuk Seo, Chanmo Yang, Young-Ho Kim
摘要
Children typically learn to identify and express their emotions by sharing stories and feelings with others, particularly family members. However, it is challenging for parents or siblings to have effective emotion communication with children since children are still developing their communication skills. We present ChaCha, a chatbot that encourages and guides children to share personal events and associated emotions. ChaCha combines a state machine and large language models (LLMs) to keep the dialogue on track while carrying on free-form conversations. Through an exploratory study with 20 children (aged 8–12), we examine how ChaCha prompts children to share personal events and guides them to describe associated emotions. Participants perceived ChaCha as a close friend and shared their stories on various topics, such as family trips and personal achievements. Based on the findings, we discuss opportunities for leveraging LLMs to design child-friendly chatbots to support children in sharing emotions.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper33
- MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' JournalingTaewan Kim, Seolyeong Bae, Hyun Ah Kim, Su-Woo Lee 等CHI 2024 · 被引用 112 次
- Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported DataJing Wei, Sungdong Kim, Hyunhoon Jung, Young-Ho KimCSCW 2024 · 被引用 82 次
- The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health SupportInhwa Song, Sachin R. Pendse, Neha Kumar, Munmun De ChoudhuryCSCW 2025 · 被引用 41 次
- How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About ItNanna Inie, Jeanette Falk, Raghavendra SelvanCHI 2025 · 被引用 33 次
- ExploreSelf: Fostering User-driven Exploration and Reflection on Personal Challenges with Adaptive Guidance by Large Language ModelsInhwa Song, SoHyun Park, Sachin R. Pendse, Jessica Lee Schleider 等CHI 2025 · 被引用 31 次
它引用的顶会 Paper12
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 被引用 64,255 次
- Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsJason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma 等NeurIPS 2022 · 被引用 22,562 次
- To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-makingZana Buçinca, Maja Barbara Malaya, Krzysztof Z. GajosCSCW 2021 · 被引用 962 次
- AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model PromptsTongshuang Wu, Michael Terry, Carrie Jun CaiCHI 2022 · 被引用 465 次
- Language Model Tokenizers Introduce Unfairness Between LanguagesAleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, Adel BibiNeurIPS 2023 · 被引用 301 次
相关 Paper
- Enhancing Pediatric Communication: The Role of an AI-Driven Chatbot in Facilitating Child-Parent-Provider InteractionWoosuk Seo, Young-Ho Kim, Ji Eun Kim, Megan Tao Fan 等CHI 2025 · 被引用 14 次
- Characterizing LLM-Empowered Personalized Story Reading and Interaction for Children: Insights From Multi-Stakeholder PerspectivesJiaju Chen, Minglong Tang, Yuxuan Lu, Bingsheng Yao 等CHI 2025 · 被引用 20 次
- Customizing Emotional Support: How Do Individuals Construct and Interact With LLM-Powered ChatbotsXi Zheng, Zhuoyang Li, Xinning Gui, Yuhan LuoCHI 2025 · 被引用 47 次
- EmoEden: Applying Generative Artificial Intelligence to Emotional Learning for Children with High-Function AutismYilin Tang, Liuqing Chen, Ziyu Chen, Wenkai Chen 等CHI 2024 · 被引用 58 次
- Mathemyths: Leveraging Large Language Models to Teach Mathematical Language through Child-AI Co-Creative StorytellingChao Zhang, Xuechen Liu, Katherine Ziska, Soobin Jeon 等CHI 2024 · 被引用 93 次
