The Role of AI in Historical Simulation Design: A TPACK Perspective on a French Revolution Simulation Design Experience

This study explores the integration of generative artificial intelligence (GenAI), specifically ChatGPT, in designing a historical simulation of the French Revolution for eighth-grade students. Using the technological pedagogical content knowledge (TPACK) framework, the research examines how GenAI facilitated and obstructed the creation of an immersive educational experience, addressing the challenges and opportunities it presents. The study employs an explanatory case study methodology combined with autoethnographic elements, capturing the dynamic interplay between AI tools and educators in the design process. The simulation incorporated faction-based role-playing to engage students in historical decision-making, influenced by both pre-revolutionary and revolutionary events. GenAI played multiple collegial roles in the design process, including as a subject matter expert, game mechanics designer, and content communicator, enhancing efficiency and creativity. However, its limitations—such as unverified information, anachronisms, and biases—necessitated careful consideration, drawing on content matter expertise and knowledge of curriculum and class context. Findings indicate that the effective use of GenAI to assist simulation design requires a robust integration of content knowledge, technological proficiency, and pedagogical strategies within the TPACK framework. The study contributes to emerging research on AI’s role in pedagogical design process, with implications for history education and beyond.

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Publication Details

Journal
Education Sciences
Published
2025-02-06
DOI
https://doi.org/10.3390/educsci15020192
Citations
5
Primary Topic
Statistics Education and Methodologies
Type
article
Field-Weighted Citation Impact
13.15
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article

The Role of AI in Historical Simulation Design: A TPACK Perspective on a French Revolution Simulation Design Experience

Björn Kindenberg
5 citations
Education Sciences
Statistics Education and Methodologies
13.15
article

The Role of AI in Historical Simulation Design: A TPACK Perspective on a French Revolution Simulation Design Experience

Björn Kindenberg
article en
5 citations

Abstract

This study explores the integration of generative artificial intelligence (GenAI), specifically ChatGPT, in designing a historical simulation of the French Revolution for eighth-grade students. Using the technological pedagogical content knowledge (TPACK) framework, the research examines how GenAI facilitated and obstructed the creation of an immersive educational experience, addressing the challenges and opportunities it presents. The study employs an explanatory case study methodology combined with autoethnographic elements, capturing the dynamic interplay between AI tools and educators in the design process. The simulation incorporated faction-based role-playing to engage students in historical decision-making, influenced by both pre-revolutionary and revolutionary events. GenAI played multiple collegial roles in the design process, including as a subject matter expert, game mechanics designer, and content communicator, enhancing efficiency and creativity. However, its limitations—such as unverified information, anachronisms, and biases—necessitated careful consideration, drawing on content matter expertise and knowledge of curriculum and class context. Findings indicate that the effective use of GenAI to assist simulation design requires a robust integration of content knowledge, technological proficiency, and pedagogical strategies within the TPACK framework. The study contributes to emerging research on AI’s role in pedagogical design process, with implications for history education and beyond.

Education SciencesVol. 15(2)
Stockholm University (SE)
Openalex Percentile: Top 1%
Statistics Education and Methodologies
13.15
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The Role of AI in Historical Simulation Design: A TPACK Perspective on a French Revolution Simulation Design Experience — Björn Kindenberg · Education Sciences (2025) | TGRS Research Map | TGRS