Co-design of a virtual training tool with emergency management stakeholders for extreme weather response

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Abstract

Emergency services usually prepare for the most frequent or predictable types of disasters, such as fires. However, preparation for complex, unpredictable disaster scenarios is infrequent, probably because of high resource demand and difficulty of covering dynamic training needs of multiple stakeholders. The use of serious game techniques as the core of simulated or virtual training tools opens for new ways of training and learning in emergency and crisis scenarios. However, the number of virtual training tools customized to specific disaster or crisis scenario that address needs of diverse user groups is limited. Existing tools are often tailored with a particular geographical setting and local threats, requiring an extensive adaptation outside the pre-defined settings. This paper describes the co-design process aimed at the creation of an emergency and disaster virtual training tool prototype linked to a Norwegian context. Two co-design workshops were run involving local emergency management actors. The general setting included an extreme weather scenario because of its high probability of occurrence and societal impact. The first workshop was used to gather end-user requirements for the training tool, explore the current gaps in the training practices, information needs and elements to improve training on decision making. In the second workshop, we focused on scrutinizing the detailed design, user interface, training use-case and learning points. Finally, we ran a small-scale usability testing of the initial prototype using SeGUE (Serious Game Usability Evaluator) instrument. The results of the prototype activities and the testing are reported in this paper.

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APA

Radianti, J., Martinez, S. G., Munkvold, B. E., & Konnestad, M. (2018). Co-design of a virtual training tool with emergency management stakeholders for extreme weather response. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10918 LNCS, pp. 185–202). Springer Verlag. https://doi.org/10.1007/978-3-319-91797-9_14

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