Computing and Information Systems - Theses
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ItemAttentional Reality: Understanding and Managing Limited Attentional Resources in Augmented Reality( 2022)Limits of human attention restrict the amount of information we can perceive when using augmented reality (AR) applications. This leads to consequences when the unperceived information, either from the digital content or the real surrounding, is vital for the user's experience or safety. Despite such consequences, it is unclear how attentional resources are allocated in AR applications and what measures can be taken to improve attention management in AR. This thesis aims to better our understanding of attention allocation in AR applications, isolate variables related to AR that demand excessive attentional resources, and develop and evaluate adaptive techniques to improve efficiency of attention allocation in AR. Our findings show that users excessively focus on the digital content in AR at the cost of neglecting information from other sources. We demonstrate how the excessive allocation of attention towards the AR content is related to the task of scanning for and processing task-relevant digital content. Finally, we show how an intelligent adaptive agent, based on the theories of selective attention, can improve attention management in AR but faces challenges when users are less receptive to the agent's support. These findings and the resulting discussions presented in this thesis yield novel insights regarding user attention in AR and provide valuable lessons in designing AR applications.