Experiential Augmentation: Uncovering The Meaning of Qualitative Visualizations when Applied to ...
summary
Study uses mocked-up images and short videos (about 30 mostly graduate participants) to test six augmentations—float, sink, rigidity loss, opacity, color loss, two sound types—and finds interpretation depends on object identity, not just the effect. Participants read float as a positive “look at me” notification, sinking = heavy data links to debt or fullness, water sounds fail because they conflict with electronics, and wood is not a neutral control. Authors propose a model of three building blocks (object, augmentation, meaning) and four meaning types and recommend high craftsmanship and using slightly negative signals to provoke specific interpretations.
AI-written summary · about
chapters (4)
related talks
18mOne Reality: Augmenting How the Physical World is Experienced by Combining Multiple Mixed ...
12mInSituTale: Enhancing Augmented Data Storytelling with Physical Objects
16mJuicy Game Design: Understanding the Impact of Visual Embellishments on Player Experience
10mQualitative Dimensions of Technology-Mediated Reflective Learning: The Case of VR Experience of ...
20mSketching Shape-changing Interfaces: Exploring Vocabulary, Metaphors Use, and Affordances
19mAffective Colour in Visualization
17mSeeing Differently: Filling the Space between the Real and Digital
01h 02mSenses Working Overtime
