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Teaching Quantitative Ethnography as Data Science Education: How Novices Learned in Using Epistemic Network Analysis

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Advances in Quantitative Ethnography (ICQE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1895))

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Abstract

This study aims to bridge teaching quantitative ethnography (QE) and data science education. For this purpose, this study proposed and conducted the educational program using epistemic network analysis (ENA) and analyzed students’ reports. The research questions were (1) What do novices learn in introductory QE education? and (2) How do students learn in the proposed educational program? Recently, education for data science and data literacy has been discussed in many countries because data science knowledge and skills have become essential in the 21st century. It is required to develop the educational program in literacy level as well as growing data scientists. Moreover, teaching QE has become a high-profile topic in the QE community. Consequently, I examined the potential of an experiential education program in which novices analyze data by ENA. As a result, the students understood the operation and usefulness of ENA through the course. Besides, they enjoyed interpreting the data with diverse team members. This study discusses the course design and educational materials as the first step to QE democratization.

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Acknowledgment

I would like to thank Yuanru Tan and the QE researchers for their advice in creating the course. Also, three graduate students supported to create the course materials and work as teaching assistants in the course. The present research was supported by JSPS KAKENHI Grant Numbers JP18K13238, JP19H01715, JP20K03066, JP22H01043, and JP 23K11357. This work was funded in part by the National Science Foundation (DRL-1661036, DRL-1713110, DRL-2100320), the Wisconsin Alumni Research Foundation, and the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison. The opinions, findings, and conclusions do not reflect the views of the funding agencies, cooperating institutions, or other individuals.

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  1. Shinshu University, 4-17-1, Wakasato, Nagano, 3808553, Japan

    Ayano Ohsaki

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  1. Ayano Ohsaki
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Correspondence to Ayano Ohsaki .

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Editors and Affiliations

  1. Clemson University, Clemson, SC, USA

    Golnaz Arastoopour Irgens

  2. University of Technology Sydney, Ultimo, NSW, Australia

    Simon Knight

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Ohsaki, A. (2023). Teaching Quantitative Ethnography as Data Science Education: How Novices Learned in Using 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_33

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  • DOI: https://doi.org/10.1007/978-3-031-47014-1_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47013-4

  • Online ISBN: 978-3-031-47014-1

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