Difference: C-TOCLiteratureReview (60 vs. 61)

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META TOPICPARENT	name="C-TOC"

C-TOC Literature Review

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Fogarty J, Ko AJ, Aung HH, et al. Examining task engagement in sensor-based statistical models of human interruptibility. Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '05. 2005:331. Available at: http://portal.acm.org/citation.cfm?doid=1054972.1055018

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best paper award, CHI 05

task engagement as predictor of interruptibility rather than task engagement;

simultaneous or repeated demands can quickly become disruptive

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Horvitz E, Apacible J. Learning and reasoning about interruption. Proceedings of the 5th international conference on Multimodal interfaces - ICMI '03. 2003:20. Available at: http://portal.acm.org/citation.cfm?doid=958432.958440

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abstract: methods for inferring cost of interrupting users based on multiple streams of events;
acoustical and visual sensors, monitor activity of a user interacting with different client devices, pending availability of microphone and camera, computing devices for reporting visual pose / head tracking, online appointment information; capture and share out the state of low-level and higher-level events; information about application in and out of focus
focus on learning models that predict the state of interruptibility of users in office settings, pursue models that characterise the user's interruptibility
related research: Coordinate, Seer
summary: effort to build models that can predict cost of interrupting users; tools for logging and tagging a database of cases, probe sensitivity of classification;

[Cutrell 01]

Cutrell E, Czerwinski M, Horvitz E. Notification, disruption, and memory: Effects of messaging interruptions on memory and performance. Human Factors. 2001;(1999). Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.26.418.

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