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Evaluating mixed reality as a platform to monitor data on maps : Impact of interaction and visualization techniques on user experience and performance
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2024 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Mixed Reality(MR) offers a new medium for information visualisation and interaction with data. Merging physical with the virtual, MR can enhance both visual and interaction experience. This MR exploration is situated at the intersection of visualization and interaction with geospatial and movement related data.

The research investigates two interaction modalities - Poke and Gaze-Pinch interactions, and two visualization techniques - Stationary and Non-stationary, for objects moving on a map, assessing their influence on the user experience, performance, and cognitive load. The study involved N=12 participants using a custom MR application developed with a Design Science Research Methodology, and data collection centered around Usability Testing strategy. The interactions and visualisation techniques, are recommended to elevate the user experience for tasks requiring interaction with objects moving on a map. The study identifies optimal strategies for engaging with dynamic data such as real-time vehicle information, to potentially support decision-making in transportation and logistics industry, when monitoring vehicles in a MR context. This research contributes to the fields of Immersive Analytics, Human-Computer Interaction, and geospatial visualization, with implications for enhancing operational efficiency and user engagement in professional settings.

Place, publisher, year, edition, pages
2024.
Keywords [en]
Human-Computer Interaction, Mixed Reality, Head-Mounted Display, Hand Tracking, Eye Tracking, Information Visualisation, Immersive Analytics, Geospatial Data, Transportation, Logistics
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:su:diva-242701OAI: oai:DiVA.org:su-242701DiVA, id: diva2:1955592
Available from: 2025-04-30 Created: 2025-04-30

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf