"Ask Sir Oliver Ingham": LLM-based Social Simulations for History Education
Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '25)
CHI 2025 EA · Extended Abstract
📝Abstract
Authentic historical inquiry supports deeper historical understanding, yet it is often underutilized due to time constraints and limited instructional tools. This study investigates the feasibility and potential of an LLM-based historical simulation platform designed to balance immersive student engagement with teacher-directed customization. We developed a prototype that provides interactive historical contexts, AI-driven character conversations, and structured quests, while allowing teachers to adapt maps, characters, and content. Fifteen elementary and middle school teachers evaluated its feasibility through think-aloud protocols and in-depth interviews. Participants reported high usability and indicated benefits such as flexible customization, multi-perspective learning, and self-paced inquiry. Although concerns over AI limitations emerged, participants noted that such challenges can be addressed through appropriate instructional strategies which are currently used in-practice. This study introduces a novel instructional tool, offers insights into teachers’ perspectives on LLM-based simulations and highlights opportunities to enhance historical thinking and AI literacy.
🔖BibTeX
@inproceedings{park2025oliveringham,
title = {"Ask Sir Oliver Ingham": LLM-based Social Simulations for History Education},
author = {Kieun Park and Hyungwoo Song and Seungbae Seo and Junghwan Kim and Bongwon Suh},
booktitle = {Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '25)},
year = {2025},
doi = {10.1145/3706599.3719728}
}