Multi-format Notifications for Multi-tasking

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5726)


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.


Notification interfaces multi-format notification user preferences 


  1. 1.
    Adamczyk, P.D., Bailey, B.P.: If not now, when?: the effects of interruption at different moments within task execution. In: CHI 2004: Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 271–278. ACM, New York (2004)CrossRefGoogle Scholar
  2. 2.
    Cutrell, E., Czerwinski, M., Horvitz, E.: Notification, disruption, and memory: Effects of messaging interruptions on memory and performance. In: Interact (2001)Google Scholar
  3. 3.
    Czerwinski, M., Cutrell, E., Horvitz, E.: Instant messaging: Effects of relevance and time. In: People and Computers XIV: Proceedings of HCI 2000, vol. 2, pp. 71–76. British Computer Society (2000)Google Scholar
  4. 4.
    Edwards, A.: Balanced latin-square designs in psychological research. American Journal of Psychology, 598–603 (1951)Google Scholar
  5. 5.
    Fogarty, J., Hudson, S.E., Atkeson, C.G., Avrahami, D., Forlizzi, J., Kiesler, S., Lee, J.C., Yang, J.: Predicting human interruptibility with sensors. ACM Trans. Comput.-Hum. Interact. 12(1), 119–146 (2005)CrossRefGoogle Scholar
  6. 6.
    Gajos, K.: Automatically generating personalized user interfaces, phd dissertation (2008)Google Scholar
  7. 7.
    Gluck, J., Bunt, A., McGrenere, J.: Matching attentional draw with utility in interruption. In: Proceedings of CHI 2007, pp. 41–50 (2007)Google Scholar
  8. 8.
    Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. In: Hancock, P., Meshkati, N. (eds.), Elsevier Science, Amsterdam (1988)Google Scholar
  9. 9.
    Iqbal, S.T., Bailey, B.P.: Effects of intelligent notification management on users and their tasks. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2008), Florence, Italy (2008)Google Scholar
  10. 10.
    Levitt, J.: Internet zone: Good help is hard to find. Information Week: Listening Post (2001),
  11. 11.
    Mark, G., Gudith, D., Klocke, U.: The cost of interrupted work: more speed and stress. In: CHI 2008: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, pp. 107–110. ACM, New York (2008)CrossRefGoogle Scholar
  12. 12.
    McCrickard, D.S., Chewar, C.M.: Attuning notification design to user goals and attention costs. Communications of the ACM 46, 67–72 (2003)CrossRefGoogle Scholar
  13. 13.
    Nishikado, T.: Space invaders (1978)Google Scholar
  14. 14.
    Trafton, J.G., Altmann, E.M., Brock, D.P., Mintz, F.E.: Preparing to resume an interrupted task: effects of prospective goal encoding and retrospective rehearsal. Int. J. Hum.-Comput. Stud. 58(5), 583–603 (2003)CrossRefGoogle Scholar
  15. 15.
    Vastenburg, M.H., Keyson, D.V., de Ridder, H.: Considerate home notification systems: A field study of acceptability of notifications in the home. Personal and Ubiquitous Computing (2007)Google Scholar
  16. 16.
    Weber, J.S., Pollack, M.E.: Evaluating user preferences for adaptive reminding. In: CHI Extended Abstracts (2008)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  1. 1.Computer Science & EngineeringUSA
  2. 2.School of InformationUniversity of MichiganAnn ArborUSA

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