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Cognitive Overload in Mixed-Reality Interactions: A Qualitative Analysis
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2023 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Mixed reality (MR) technology is trending in various sectors at the present time. In MR applications, due to the interactions between two realities, the potential of experiencing Cognitive Overload is high. Hence, the present qualitative study has been conducted to broaden the understanding of Cognitive Load in MR interventions. Six participants were recruited for the study who were University students. The study was conducted with an activity, based on a car chasing scenario in police interventions. The participants were instructed to complete a questionnaire after the activity, which was designed based on Cognitive Load Theory (CLT), and thereafter semi-structured interviews were conducted. The data were analyzed through the Thematic Analysis method (TA), which resulted in generating three themes; Prevention of Intrinsic Load, Prevention of Extraneous Load, and Increase of Germane Load. Each theme was divided into categories, and the codes were generated and analyzed under the categories. Our findings elaborate on several elements that influence cognitive load in MR interactions. The major elements of our findings include; Expertise in operating HoloLens and MR, Prevention of Split-attention, Prioritizing and Grouping of information, Vigilance, Design of HoloLens and MR, and Comprehensibility. The study findings can be used in designing MR applications, especially for the use case of police interventions. Yet, we believe that further studies are needed to broaden the understanding of causes and prevention methods of Cognitive overload in MR interactions. 

Place, publisher, year, edition, pages
2023. , p. 35
Series
UMNAD ; 1436
Keywords [en]
Mixed Reality Interaction, Cognitive Load Theory, Context Understanding
National Category
Human Computer Interaction Computer Sciences Applied Psychology
Identifiers
URN: urn:nbn:se:umu:diva-212304OAI: oai:DiVA.org:umu-212304DiVA, id: diva2:1783578
Educational program
Master's Programme in Cognitive Science
Supervisors
Examiners
Available from: 2023-09-04 Created: 2023-07-22 Last updated: 2023-09-04Bibliographically approved

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Human Computer InteractionComputer SciencesApplied Psychology

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • de-DE
  • en-GB
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  • nn-NO
  • nn-NB
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