Context- and Data-driven Satisfaction Analysis of User Interface Adaptations Based on Instant User Feedback

Abstract

Modern User Interfaces (UIs) are increasingly expected to be plastic, in the sense that they retain a constant level of usability, even when subjected to context (platform, user, and environment) changes at runtime. Adaptive UIs have been promoted as a solution for context variability due to their ability to automatically adapt to the context-of-use at runtime. However, evaluating end-user satisfaction of adaptive UIs is a challenging task, because the UI and the context-of-use are both constantly changing. Thus, an acceptance analysis of UI adaptation features should consider the context-of-use when adaptations are triggered. Classical usability evaluation methods like usability tests mostly focus on a posteriori analysis techniques and do not fully exploit the potential of collecting implicit and explicit user feedback at runtime. To address this challenge, we present an on-the-fly usability testing solution that combines continuous context monitoring together with collection of instant user feedback to assess end-user satisfaction of UI adaptation features. The solution was applied to a mobile Android mail application, which served as basis for a usability study with 23 participants. A data-driven end-user satisfaction analysis based on the collected context information and user feedback was conducted. The main results show that most of the triggered UI adaptation features were positively rated.