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Visually supported reasoning under uncertain conditions: Effects of domain expertise on air traffic risk assessment
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2900-9335
2016 (English)In: Spatial Cognition and Computation, ISSN 1387-5868, E-ISSN 1573-9252, Vol. 16, no 2, p. 133-153Article in journal (Refereed) Published
Abstract [en]

This article investigates the impact that domain expertise has on risk assessment when analyzing uncertain geographical and sensor data. The differences between novice and expert air traffic operators were examined taking into account the performance of identifying and classifying threatening targets, the time needed to carry out such classifications, and the confidence reported for each decision. The results show that confidence was significantly higher for the expert group. This was supported by the after-test questionnaire because none of the novice participants reported being more confident with the visualizations of uncertainty provided. No significant differences regarding time and performance were found between the groups, even if experts needed, on average, more time to make a decision. Based on the collected logs, the experienced participants more often accessed the detailed information for each object presented by the tool tip. Both the time taken and the data accessed might indicate that experts had better situation awareness. Finally, the experts reported higher workload values related to performance.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2016. Vol. 16, no 2, p. 133-153
Keywords [en]
decision-making, evaluation, expertise, risk assessment, uncertainty visualization
National Category
Human Computer Interaction
Research subject
Natural sciences; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-12182DOI: 10.1080/13875868.2015.1137576ISI: 000372891100003Scopus ID: 2-s2.0-84959037315OAI: oai:DiVA.org:his-12182DiVA, id: diva2:925299
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NOVA
Funder
Knowledge FoundationAvailable from: 2016-05-01 Created: 2016-05-01 Last updated: 2018-03-28Bibliographically approved

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Riveiro, Maria

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CiteExportLink to record
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Citation style
  • apa
  • apa-cv
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  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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  • de-DE
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  • en-US
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Output format
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