Leveraging characteristics of task structure to predict the cost of interruption

Shamsi T. Iqbal, Brian P. Bailey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A challenge in building interruption reasoning systems is to compute an accurate cost of interruption (COI). Prior work has used interface events and other cues to predict COI, but ignore characteristics related to the structure of a task. This work investigates how well characteristics of task structure can predict COI, as objectively measured by resumption lag. In an experiment, users were interrupted during task execution at various boundaries to collect a large sample of resumption lag values. Statistical methods were employed to create a parsimonious model that uses characteristics of task structure to predict COI. A subsequent experiment with different tasks showed that the model can predict COI with reasonably high accuracy. Our model can be expediently applied to many goal-directed tasks, allowing systems to make more effective decisions about when to interrupt.

Original languageEnglish (US)
Title of host publicationCHI 2006
Subtitle of host publicationConference on Human Factors in Computing Systems, Conference Proceedings SIGCHI
PublisherAssociation for Computing Machinery
Pages741-750
Number of pages10
ISBN (Print)1595931783, 9781595931788
DOIs
StatePublished - 2006
EventCHI 2006: Conference on Human Factors in Computing Systems - Montreal, QC, Canada
Duration: Apr 22 2006Apr 27 2006

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume2

Other

OtherCHI 2006: Conference on Human Factors in Computing Systems
CountryCanada
CityMontreal, QC
Period4/22/064/27/06

Keywords

  • Attention
  • Interruption
  • Learning
  • Task Models
  • Workload

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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