Augmented Reality (AR) applications can enable geographically distant users to collaborate using shared video feeds or interactive 3D holograms, and may be particularly useful in the socially distant context of the Covid-19 pandemic. However, a good user experience is key for their success and could be negatively impacted by network impairments, which are an inevitable occurrence in today's best-effort Internet. In this paper, we present the findings of an empirical user study, aimed at understanding the effects of network outages, on user experience and behavior, in a collaborative AR task. We highlight how network outages affected users in different ways depending on their role in the collaborative task, and how giving users explicit information about poor network conditions helped them deal with some of these negative effects. Furthermore, we report the strategies that users themselves adopted, to deal with outages, such as batching instructions, or shifting to a different spatial referencing style when communicating with their partners. Lastly, based on our findings, we present some design implications for future remote-collaborative AR applications. 
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                            Woes, Workarounds, and Wishes of Users Living in a Multinetwork Reality
                        
                    
    
            Despite efforts towards pervasive, high-speed broadband connectivity, users worldwide continue to experience a persistent multinetwork reality–a reality of intermittent Internet access over multiple networks of varying capacities across space and time. In this late-breaking work, we investigate the challenges users face while using different Internet-based services and the mitigating strategies they adopt to overcome those challenges in a multinetwork reality. In addition, we also investigate how users envision software-based interventions that might augment their existing strategies and help them better manage their activities in a multinetwork reality. Finally, based on our findings from a qualitative analysis of semi-structured interviews, we explore a two-dimensional design space defined by cognitive and resource costs and discuss directions for future work. 
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                            - Award ID(s):
- 2145861
- PAR ID:
- 10433163
- Date Published:
- Journal Name:
- CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
- Page Range / eLocation ID:
- 1-7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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