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The Stories We Tell: Uncovering Hidden Narratives in History Textbooks Through Epistemic Network Analysis

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Advances in Quantitative Ethnography (ICQE 2023)

Abstract

This study delves into the unique perspectives of authors of U.S. history textbooks on critical events, such as World War II, the Cold War, and the Vietnam War, employing quantitative ethnography (QE) and epistemic network analysis (ENA). These methodologies offer a lens through which divergent viewpoints can be analyzed, thereby revealing differences among documents sharing a common theme yet presenting varying narratives. The study presents the epistemic networks of two history textbooks and compares three shared events routinely discussed in each book. The findings emphasize the diverse patterns of perspective-taking by both the topic and the author, as evident in the connections drawn between common constructs of historical narratives. This research underscores the need to acknowledge the presence of multiple historical viewpoints and political perspectives, even within history textbooks from the same country. Exploring these perspectives is essential to fostering a more comprehensive understanding of historical events and promoting critical thinking and nuanced interpretations. The outcomes of this study suggest that applications of QE and ENA can be instrumental in critically examining how history is constructed and communicated, thereby advancing our understanding of the pedagogical implications in history education.

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Acknowledgements

We thank the research team for their invaluable contributions. We also acknowledge ChatGPT for enhancing the language clarity of our drafts, but human authors rigorously reviewed all content before submission.

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Correspondence to Juhan Kim .

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Kim, J., Barany, A., Liu, X., Zambrano, A.F. (2023). The Stories We Tell: Uncovering Hidden Narratives in History Textbooks Through Epistemic Network Analysis. In: Arastoopour Irgens, G., Knight, S. (eds) Advances in Quantitative Ethnography. ICQE 2023. Communications in Computer and Information Science, vol 1895. Springer, Cham. https://doi.org/10.1007/978-3-031-47014-1_18

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  • DOI: https://doi.org/10.1007/978-3-031-47014-1_18

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-47014-1

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