'HistoChat': Leveraging AI-Driven Historical Personas for Personalized and Engaging Middle School History Education

Traditional history education often fails to cultivate historical empathy due to rigid curricula and limited opportunities for personalized, emotionally resonant engagement. We explore the potential of LLM-based historical personas to address these gaps by enabling students to engage in real-time, conversational interactions with simulated historical figures. A formative study with teachers and students surfaced key challenges and expectations around AI-mediated historical dialogue, informing the development of Baseline and Experimental HistoChat, AI persona systems featuring differing prompting strategies. A subsequent user study showed that these interactions fostered deeper inquiry, curiosity, and emotional engagement-while also revealing key limitations. From a CSCW perspective, this work expands the role of AI from task assistant to epistemic partner, contributing to ongoing discourse on how dialogic systems can support meaning-making, empathy, and co-constructed learning in educational settings. Our findings yield valuable insights into the impact of tailored AI interactions on personalized and empathetic history education.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757534
Primary Topic
Persona Design and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

'HistoChat': Leveraging AI-Driven Historical Personas for Personalized and Engaging Middle School History Education

Sangsu Lee, Tak Yeon Lee, Yeon Soo Kim, H. S. Moon
Proceedings of the ACM on Human-Computer Interaction
Persona Design and Applications
article

'HistoChat': Leveraging AI-Driven Historical Personas for Personalized and Engaging Middle School History Education

Sangsu Lee, Tak Yeon Lee, Yeon Soo Kim, H. S. Moon
article en

Abstract

Traditional history education often fails to cultivate historical empathy due to rigid curricula and limited opportunities for personalized, emotionally resonant engagement. We explore the potential of LLM-based historical personas to address these gaps by enabling students to engage in real-time, conversational interactions with simulated historical figures. A formative study with teachers and students surfaced key challenges and expectations around AI-mediated historical dialogue, informing the development of Baseline and Experimental HistoChat, AI persona systems featuring differing prompting strategies. A subsequent user study showed that these interactions fostered deeper inquiry, curiosity, and emotional engagement-while also revealing key limitations. From a CSCW perspective, this work expands the role of AI from task assistant to epistemic partner, contributing to ongoing discourse on how dialogic systems can support meaning-making, empathy, and co-constructed learning in educational settings. Our findings yield valuable insights into the impact of tailored AI interactions on personalized and empathetic history education.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Korea Advanced Institute of Science and Technology (KR)
Openalex Percentile: Top 71%
Persona Design and Applications
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