The use of eye movements in human-computer interaction techniques: what you look at is what you get
ACM Transactions on Information Systems (TOIS) - Special issue on computer—human interaction
A performance model of system delay and user strategy selection
CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
How machine delays change user strategies
ACM SIGCHI Bulletin
The importance of percent-done progress indicators for computer-human interfaces
CHI '85 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predicting text entry speed on mobile phones
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
XWand: UI for intelligent spaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
HCI aspects of mobile devices and services
Personal and Ubiquitous Computing
Stroke break analysis: a practical method to study timeout value for handwriting recognition input
Proceedings of the 7th international conference on Human computer interaction with mobile devices & services
Towards mobility oriented interaction design: experiments in pedestrian navigation on mobile devices
Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
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In many user interfaces with restricted input capabilities, a time-out is used to automatically change the user interface (UI) from one mode to another. In this paper, we study the learning of time-outs and the effect of feedback on it in the case of mobile phone text entry. The effects of three different feedback schemes (auditory/visual/no feedback) on the learning of two different time-out lengths were compared. We measured the response time (RT) from the time-out occurrence to the time of the user’s action. Error rates and the development of the RTs in different schemes were used as measures of learning. We also studied if the users learned to estimate the time-out lengths, or if they just reacted to the available feedback. There were three main findings. Without feedback, RTs had a great variation. Auditory feedback enabled faster RTs than visual feedback. Finally, we found evidence of short-term learning, but not much of a lasting effect. The possible application of adapting time-out length to user RT is discussed.