Laboratoire d'Informatique de Grenoble Équipe Ingénierie de l'Interaction Homme-Machine

Équipe Ingénierie de l'Interaction
Homme-Machine

SplitSlider: a Tangible Interface to Input Uncertainty

In Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction (INTERACT 2019). pages 493-510. 2019.

Miriam Greis, Hyunyoung Kim, Andreas Korge, Albrecht Schmidt, Céline Coutrix

Résumé

Experiencing uncertainty is common when answering questionnaires. E.g., users are not always sure to answer how often they use trains. Enabling users to input their uncertainty is thus important to increase the data’s reliability and to make better decision based on the data. However, few interfaces have been explored to support uncertain input, especially with TUIs. TUIs are more discoverable than GUIs and better support simultaneous input of multiple parameters. It motivates us to explore different TUI designs to input users’ best estimate answer (value) and uncertainty. In this paper, we first generate 5 TUI designs that can input both value and uncertainty and build low-fidelity prototypes. We then conduct focus group interviews to evaluate the prototypes and implement the best design, SplitSlider, as a working prototype. A lab study with SplitSlider shows that one third of the participants (4/12) were able to discover the uncertainty input function without any explanation, and once explained, all of them could easily understand the concept and input uncertainty.