Miniature representations, like CAD and blueprints, are useful for designing a larger physical space. While experts are trained to use these methods, non-experts often lack this training. Nonetheless, non-experts can benefit from designing with miniature representations, yet their interactions with these tools are not well understood. In our work, we observed participants designing two rooms using three tools: an online planner, pen and paper, and Lego. We collected and analyzed data from the Desirability Toolkit, a semi-structured interview, and observations of their design sessions. Our findings suggest that participants found each tool engaging and satisfying for different reasons, but paper more empowering and Lego more familiar, efficient, and unconventional. Participants also suggested that these tools had value at different design stages. We also identified that participants often had difficulty scaling objects to match realistic expectations in the paper and Lego miniature representations.

Open offices are cost-effective and continue to be popular. However, research shows that these environments, brimming with distractions and sensory overload, frequently hamper productivity. Our research investigates the use of virtual reality (VR) to mitigate distractions in an open office setting and improve one's ability to be in flow. In a lab study, 35 participants performed visual programming tasks in four combinations of physical (open or closed office) and virtual environments (beach or virtual office). While participants both preferred and were in flow more in a closed office without VR, in an open office, the VR environments outperformed the no VR condition in all measures of flow, performance, and preference. Especially considering the recent rapid advancements in VR, our findings illustrate the potential VR has to improve flow and satisfaction in open offices.

Intensive exploration and navigation of hierarchical lists on smartphones can be tedious and time-consuming as it often requires users to frequently switch between multiple views. To overcome this limitation, we present PinchList, a novel interaction design that leverages pinch gestures to support seamless exploration of multi-level list items in hierarchical views. With PinchList, sub-lists are accessed with a pinch-out gesture whereas a pinch-in gesture navigates back to the previous level. Additionally, pinch and flick gestures are used to navigate lists consisting of more than two levels. We conduct a user study to refine the design parameters of PinchList such as a suitable item size, and quantitatively evaluate the target acquisition performance using pinch-in/out gestures in both scrolling and non-scrolling conditions. In a second study, we compare the performance of PinchList in a hierarchal navigation task with two commonly used touch interfaces for list browsing: pagination and expand-and-collapse interfaces. The results reveal that PinchList is significantly faster than other two interfaces in accessing items located in hierarchical list views. Finally, we demonstrate that PinchList enables a host of novel applications in list-based interaction?

Autostereograms are 2D images that can reveal 3D content when viewed with a specific eye convergence, without using extra-apparatus. We contribute to autostereogram studies from an HCI perspective. We explore touch inputs and output design options when interacting with autostereograms on smartphones. We found that an interactive help (i.e. to control the autostereogram stereo-separation), a color-based feedback (i.e. highlight of the screen), and a direct touch input can provide support for faster and more accurate interaction than a static help (i.e. static dots indicating the stereo-separation), an animated feedback (i.e., a 'pressed' effect), and an indirect input. In addition, results reveal that participants learn to perceive smaller and smaller autostereogram content faster with practice. This learning effect transfers across display devices (smartphone to desktop screen).

In recent years, around device input has emerged as a complement to standard touch input, albeit in limited tasks and contexts, such as for item selection or map navigation. We push the boundaries for around device interactions to facilitate an entire smartphone application: browsing through large information lists to make a decision. To this end, we present AirPanes, a novel technique that allows two-handed in-air interactions, conjointly with touch input to perform analytic tasks, such as making a purchase decision. AirPanes resolves the inefficiencies of having to switch between multiple views or panes in common smartphone applications. We explore the design factors that make AirPanes efficient. In a controlled study, we find that AirPanes is on average 50% more efficient that standard touch input for an analytic task. We offer recommendations for implementing AirPanes in a broad range of applications.