We study the performance and user experience of two popular mainstream text entry devices, desktop keyboards and touchscreen keyboards, for use in Virtual Reality (VR) applications. We discuss the limitations arising from limited visual feedback, and examine the efficiency of different strategies of use. We analyze a total of 24 hours of typing data in VR from 24 participants and find that novice users are able to retain about 60% of their typing speed on a desktop keyboard and about 40-45% of their typing speed on a touchscreen keyboard. We also find no significant learning effects, indicating that users can transfer their typing skills fast into VR. Besides investigating baseline performances, we study the position in which keyboards and hands are rendered in space. We find that this does not adversely affect performance for desktop keyboard typing and results in a performance trade-off for touchscreen keyboard typing.

Figure 1: Views on the conditions studied in the experiment on effects of hand representations for typing in VR. From left to right: NoHand, IKHand, Fingertip and VideoHand. AbstractAlphanumeric text entry is a challenge for Virtual Reality (VR) applications. VR enables new capabilities, impossible in the real world, such as an unobstructed view of the keyboard, without occlusion by the user's physical hands. Several hand representations have been proposed for typing in VR on standard physical keyboards. However, to date, these hand representations have not been compared regarding their performance and effects on presence for VR text entry. Our work addresses this gap by comparing existing hand representations with minimalistic fingertip visualization. We study the effects of four hand representations (no hand representation, inverse kinematic model, fingertip visualization using spheres and video inlay) on typing in VR using a standard physical keyboard with 24 participants. We found that the fingertip visualization and video inlay both resulted in statistically significant lower text entry error rates compared to no hand or inverse kinematic model representations. We found no statistical differences in text entry speed.

Saving money is usually a tedious task that requires a high degree of self-control for many of us. Some people have one or more specific savings targets in mind and thus need to prioritize them. We propose connecting a savings box with a personal smartphone. Thus, people become motivated to keep track of their savings for multiple targets. Using a savings box capable of counting money and connecting it to an app, we believe people stick to their plans to save with higher motivation and are happier with their behavior. In this paper, we present first evidence for the success of this concept. We gathered feedback through an online user study in which participants were shown a video prototype. We propose further research directions with our SmartPiggy, to confirm the feasibility of behavioral economics in HCI.

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