Prior work on dark patterns, or manipulative online interfaces, suggests they have potentially detrimental effects on user autonomy. Dark pattern features, like those designed for attention capture, can potentially extend platform sessions beyond what users would have otherwise intended. Existing research, however, has not formally measured the quantitative effects of these features on user engagement in subscription video-on-demand platforms (SVODs). In this work, we conducted an experimental study with 76 Netflix users in the US to analyze the impact of a specific attention capture feature, autoplay, on key viewing metrics. We found that disabling autoplay on Netflix significantly reduced key content consumption aggregates, including average daily watching and average session length, partly filling the evidentiary gap regarding the empirical effects of dark pattern interfaces. We paired the experimental analysis with users' perceptions of autoplay and their viewing behaviors, finding that participants were split on whether the effects of autoplay outweigh its benefits, albeit without knowledge of the study findings. Our findings strengthen the broader argument that manipulative interface designs can and do affect users in potentially damaging ways, highlighting the continued need for considering user well-being and varied preferences in interface design.

In this paper, we introduce Physica, a tangible physics simulation system and approach based on tabletop mobile robots. In Physica, each tabletop robot can physically represent distinct simulated objects that are controlled through an underlying physics simulation, such as gravitational force, molecular movement, and spring force. It aims to bring the benefits of tangible and haptic interaction into explorable physics learning, which was traditionally only available on screen-based interfaces. The system utilizes off-the-shelf mobile robots (Sony Toio) and an open-source physics simulation tool (Teilchen). Built on top of them, we implement the interaction software pipeline that consists of 1) an event detector to reflect tangible interaction by users, and 2) target speed control to minimize the gap between the robot motion and simulated moving objects. To present the potential for physics education, we demonstrate various application scenarios that illustrate different forms of learning using Physica. In our user study, we investigate the effect and the potential of our approach through a perception study and interviews with physics educators.

This paper introduces Sketched Reality, an approach that combines AR sketching and actuated tangible user interfaces (TUI) for bi-directional sketching interaction. Bi-directional sketching enables virtual sketches and physical objects to “affect” each other through physical actuation and digital computation. In the existing AR sketching, the relationship between virtual and physical worlds is only one-directional — while physical interaction can affect virtual sketches, virtual sketches have no return effect on the physical objects or environment. In contrast, bi-directional sketching interaction allows the seamless coupling between sketches and actuated TUIs. In this paper, we employ tabletop-size small robots (Sony Toio) and an iPad-based AR sketching tool to demonstrate the concept. In our system, virtual sketches drawn and simulated on an iPad (e.g., lines, walls, pendulums, and springs) can move, actuate, collide, and constrain physical Toio robots, as if virtual sketches and the physical objects exist in the same space through seamless coupling between AR and robot motion. This paper contributes a set of novel interactions and a design space of bi-directional AR sketching. We demonstrate a series of potential applications, such as tangible physics education, explorable mechanism, tangible gaming for children, and in-situ robot programming via sketching.