Attuning notification design to user goals and attention costs
Communications of the ACM
International Journal of Human-Computer Studies - Notification user interfaces
If not now, when?: the effects of interruption at different moments within task execution
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predicting human interruptibility with sensors
ACM Transactions on Computer-Human Interaction (TOCHI)
Matching attentional draw with utility in interruption
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Effects of intelligent notification management on users and their tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The cost of interrupted work: more speed and stress
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluating user preferences for adaptive reminding
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Considerate home notification systems: a field study of acceptability of notifications in the home
Personal and Ubiquitous Computing
Automatically generating personalized user interfaces
Automatically generating personalized user interfaces
Proceedings of the Ergonomie et Informatique Avancee Conference
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We studied people's perception of and response to a set of visual and auditory notifications issued in a multi-task environment. Primary findings show that participants' reactive preference ratings of notifications delivered in various contexts during experimentation appear to contradict their reflective, overall ratings of the notification formats when elicited independently of contextual information, indicating a potential difficulty in people's abilities to articulate their preferences in the absence of context. We also found people to vary considerably in their preferences for different notification formats delivered in different contexts, such that simple approaches to selecting notification delivery formats will be dissatisfying to users a substantial portion of the time. These findings can inform the designs of future systems: rather than target the general user alone, they should strive to better understand each user individually.