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Implementation of a Learning Assistance Framework for Prolonged Evacuation Life in an Era of Massive Natural Disasters

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1226))

Abstract

In this research, we have implemented of a learning assistance framework for evacuated students. As natural disasters intensify due to climate change, evacuation timespans are becoming prolonged. This is not an exception for learners like university students. Current e-learning environments assume the existence of a stable Internet connection. However, the Internet may not be sufficiently accessible in evacuation centers for e-learning. In unstable communication environments such as makeshift Wi-Fi networks used in evacuation centers, it is difficult to conduct e-learning. Thus, a mechanism that can allow students to engage in e-learning in evacuation situations is required. In this paper, we describe the detail of implementation the learning assistance framework for evacuated learners and show the results of our experimental use of the framework.

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References

  1. World Meteorological Organization: WMO confirms 2019 as second hottest year on record, Press Release Number 01/15/2020. https://public.wmo.int/en/media/press-release/wmo-confirms-2019-second-hottest-year-record

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  4. Togawa, S., Kondo, A., Kanenishi, K.: Design of a learning assistance framework for prolonged evacuation life in an era of massive natural disasters. In: Proceedings of 14th International Technology Education and Development Conference (INTED 2020) (2020, in Press). 5 pages

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Numbers 18K02922.

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Correspondence to Satoshi Togawa .

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Togawa, S., Kondo, A., Kanenishi, K. (2020). Implementation of a Learning Assistance Framework for Prolonged Evacuation Life in an Era of Massive Natural Disasters. In: Stephanidis, C., Antona, M. (eds) HCI International 2020 - Posters. HCII 2020. Communications in Computer and Information Science, vol 1226. Springer, Cham. https://doi.org/10.1007/978-3-030-50732-9_62

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  • DOI: https://doi.org/10.1007/978-3-030-50732-9_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50731-2

  • Online ISBN: 978-3-030-50732-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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