Understanding and Streamlining App Switching Experiences in Mobile Interaction

Abstract Despite a large body of literature analyzing mobile device usage, app switching is still an overlooked interaction. To better understand and streamline the app switching experience in modern smartphones, we first explore how to automatically extract and characterize habitual app switching behaviors from smartphone usage data. By applying a data analytic methodology based on association rules to a large dataset of smartphone usage, in particular, we demonstrate that users repeatedly switch between the same applications under different contexts (e.g., location and time). We then implemented the methodology in RecApps, an interactive floating widget that proactively suggests the next apps to be used while the user is interacting with their smartphone. We evaluate RecApps through an in-the-wild study with 18 participants. Findings show that RecApps simplifies and supports the transitions between the users’ favorite apps, while highlighting the need for novel interactions supporting app switching behavior. We use such results to explore trade-offs in the design space for proactively supporting app switching behavior in mobile interaction.