People access applications and services through different devices depending on location and needs. During a single day, people can use a smartphone, tablet, PC and a TV, sequentially or simultaneously, depending on the context of use. Even within a single task, people often start with one device, such as a smartphone, and continue with another device, such as a PC, as the task evolves. To provide fluent task continuation, the system should provide ways to migrate on-going sessions from one device to another in a seamless manner. In this paper, we present a solution for migrating user interface and maintaining the interaction session across devices when changing situations. With two studies we gain insights into user needs and technical requirements for context-aware information sharing in multi-device environments. A longitudinal diary study was conducted to uncover specific situations where users have needs for information sharing, and how they would prefer the system to react in those situations. We also conducted a controlled user study using a prototype system for session migration between devices in changing contexts, with three different operational modes: manual, assisted and automatic, to gain a deeper knowledge into the requirements. The findings indicate a need for easier interaction whilst switching between devices and that these needs are often situation-specific. We also report in detail how people would prefer the system to perform migrations automatically and intelligently suggest them in some situations. Moreover, we draw technical requirements for such a system in order to develop seamless context-aware migration.
|Journal||Journal of Ambient Intelligence and Humanized Computing|
|Publication status||Published - 2015|
|MoE publication type||A1 Journal article-refereed|
- device ensembles
- migratory user interfaces
- multi-device environments
Ghiani, G., Polet, J., Antila, V., & Mäntyjärvi, J. (2015). Evaluating context-aware user interface migration in multi-device environments. Journal of Ambient Intelligence and Humanized Computing, 6(2), 259-277. https://doi.org/10.1007/s12652-013-0214-7