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dc.contributor.authorSuh, Ashleyen_US
dc.contributor.authorMosca, Aben_US
dc.contributor.authorRobinson, Shannonen_US
dc.contributor.authorPham, Quinnen_US
dc.contributor.authorCashman, Dylanen_US
dc.contributor.authorOttley, Alvittaen_US
dc.contributor.authorChang, Remcoen_US
dc.contributor.editorAgus, Marcoen_US
dc.contributor.editorAigner, Wolfgangen_US
dc.contributor.editorHoellt, Thomasen_US
dc.description.abstractDesigning suitable tasks for visualization evaluation remains challenging. Traditional evaluation techniques commonly rely on 'low-level' or 'open-ended' tasks to assess the efficacy of a proposed visualization, however, nontrivial trade-offs exist between the two. Low-level tasks allow for robust quantitative evaluations, but are not indicative of the complex usage of a visualization. Open-ended tasks, while excellent for insight-based evaluations, are typically unstructured and require time-consuming interviews. Bridging this gap, we propose inferential tasks: a complementary task category based on inferential learning in psychology. Inferential tasks produce quantitative evaluation data in which users are prompted to form and validate their own findings with a visualization. We demonstrate the use of inferential tasks through a validation experiment on two well-known visualization tools.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.subjectCCS Concepts: Human-centered computing → Information visualization; Visualization design and evaluation methods
dc.subjectcentered computing → Information visualization
dc.subjectVisualization design and evaluation methods
dc.titleInferential Tasks as an Evaluation Technique for Visualizationen_US
dc.description.seriesinformationEuroVis 2022 - Short Papers
dc.description.sectionheadersEvaluation and Representation
dc.identifier.pages5 pages

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License