<i>Webstrates</i>

Klokmose, Clemens Nylandsted; Eagan, James; Baader, Siemen; Mackay, Wendy E.; Beaudouin-Lafon, Michel

doi:10.1145/2807442.2807446

Cited by 109 publications

(60 citation statements)

References 34 publications

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“…Cross-device or "Distributed User Interfaces" (DUIs) offer appealing features including, more pixels [48], new forms of engagement at varying scales [49], reduction in system complexity by splitting and sharing functionality [3] and targeting interactions across and between devices (e.g., [34]). This vision has given rise to sustained research interest within the HCI community from research on taxonomies [49,31], interaction techniques, and middleware [21]. We briefly discuss related work across several related areas from DUIs to UI optimization.…”

Section: Related Workmentioning

confidence: 99%

“…Existing toolkits have explored cross device interaction with combinations of mobile devices [13,37,41,47,48], mobile/desktop devices [15,28,32,34], mobile/display wall devices [1,21] and wearables [2,10,17]. Alternative approaches have focused on the development of conceptual frameworks [23,39].…”

Section: Toolkits and Middlewarementioning

confidence: 99%

“…Prior work on cross-device interfaces have proposed methods for synchronizing elements across devices [7,21,32,33,51] or distributing elements of a workspace over multiple displays [41,47]. Panelrama [51] uses a suitability measure for associating (single user) UI panels to devices with an integer programming formulation.…”

Section: Introductionmentioning

confidence: 99%

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AdaM

Park

Gebhardt

Rädle

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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Optimization & Real-time Adaptation Figure 1. Given a graphical user interface (left), AdaM automatically decides which UI elements should be displayed on each device in real-time. Our optimization is designed for multi-user scenarios and considers user roles and preferences, device access restrictions and device characteristics. ABSTRACTDeveloping cross-device multi-user interfaces (UIs) is a challenging problem. There are numerous ways in which content and interactivity can be distributed. However, good solutions must consider multiple users, their roles, their preferences and access rights, as well as device capabilities. Manual and rule-based solutions are tedious to create and do not scale to larger problems nor do they adapt to dynamic changes, such as users leaving or joining an activity. In this paper, we cast the problem of UI distribution as an assignment problem and propose to solve it using combinatorial optimization. We present a mixed integer programming formulation which allows realtime applications in dynamically changing collaborative settings. It optimizes the allocation of UI elements based on device capabilities, user roles, preferences, and access rights. We present a proof-of-concept designer-in-the-loop tool, allowing for quick solution exploration. Finally, we compare our approach to traditional paper prototyping in a lab study.

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Section: Related Workmentioning

confidence: 99%

Section: Toolkits and Middlewarementioning

confidence: 99%

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AdaM

Park

Gebhardt

Rädle

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Self Cite

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“…We built a system based on Webstrates [20] in three different variants: (1) a user interface with a fixed toolbar at the top of a canvas (classic) and two spatially distributed interfaces, (2) one representing tools as digital panels (panels), and (3) one running them on individual smartphones (phones).…”

Section: Systemmentioning

confidence: 99%

“…[22,23,28]) or based on software using built-in resources (e.g. [11,20,31]). On the theoretical side, working styles known from traditional work practices using pens and rulers have been taken as a basis to establish models that conceptually guide the combination of multiple interactive artifacts into one coherent work environment [2,19].…”

Section: Introductionmentioning

confidence: 99%

Studying the benefits and challenges of spatial distribution and physical affordances in a multi-device workspace

Zagermann

Pfeil

Acevedo

et al. 2017

Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia

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In recent years, research on cross-device interaction has become a popular topic in HCI leading to novel interaction techniques mutually interfering with new evolving theoretical paradigms. Building on previous research, we implemented an individual multi-device work environment for creative activities. In a study with 20 participants, we compared a traditional toolbar-based condition with two conditions facilitating spatially distributed tools on digital panels and on physical devices. We analyze participants' interactions with the tools, encountered problems and corresponding solutions, as well as subjective task load and user experience. Our findings show that the spatial distribution of tools indeed offers advantages, but also elicits new problems, that can partly be leveraged by the physical affordances of mobile devices.

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Lessons Learned from Using Reprogrammable Prototypes with End-User Developers

Borowski

Larsen-Ledet

2021

End-User Development

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Involving end-users in the development of a product before it is deployed has great potential to increase the fit between a product and individual users' needs. While end-users can be directly involved in modifying low-fidelity prototypes, they are left out when it comes to high-fidelity interactive prototypes -in part because these cannot be modified directly or require time-consuming edit-compile-run cycles. High-fidelity prototypes, however, are more engaging for users. We created a reprogrammable high-fidelity prototype and explored its use in shortterm prototyping workshops with end-user developers, i.e. end-users with programming experience, in the domain of collaborative writing. We report observations and pitfalls, and distill four lessons learned into guidelines on how to use reprogrammable high-fidelity prototypes with end-users in contexts with limited resources. Our experiences demonstrate, among other things, that reprogrammable high-fidelity prototypes are difficult to work with -even for experienced programmers -and emphasize the need for careful attention to guiding participants, time for familiarization, and catering to multiple levels of programming experience.

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Webstrates

Cited by 109 publications

References 34 publications

AdaM

AdaM

Studying the benefits and challenges of spatial distribution and physical affordances in a multi-device workspace

Lessons Learned from Using Reprogrammable Prototypes with End-User Developers

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