Yeon Soo Kim, Hyun Seung Moon, Sangsu Lee, Tak Yeon Lee
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.