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JACIII Vol.19 No.1 pp. 109-117
doi: 10.20965/jaciii.2015.p0109
(2015)

Paper:

An Approach to Obtain Proper Time for Interruption with Self Initiated Intermission

Shreejana Prajapati, Koichi Yamada, and Muneyuki Unehara

Graduate School of Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka-machi, Nagaoka, Niigata 940-2188, Japan

Received:
May 21, 2014
Accepted:
October 3, 2014
Published:
January 20, 2015
Keywords:
self-initiated intermission, interruption, application switching, regular intervals, notification
Abstract
Notification delivered at an inappropriate time is usually considered an interruption. To ensure appropriate timing, we considered treating the self-initiated intermission as a period for interrupting users without causing distractions. This intermission is the time to report oneself as being available for an interaction or being ready for an interruption. This gives users the privilege of choosing a suitable time to handle interruptions without hampering any currently active task. Users’ interruptibility is compared at the time of self-initiated intermission with two alternative types of interruption presentation: application switching and regular intervals. An empirical study showed that the self-initiated intermission is the best approach for interrupting users because their interruptibility is high at this time. We also found that users report on their intermission approximately up to four times during an hour long time span.
Cite this article as:
S. Prajapati, K. Yamada, and M. Unehara, “An Approach to Obtain Proper Time for Interruption with Self Initiated Intermission,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.1, pp. 109-117, 2015.
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References
  1. [1] S. T. Iqbal and B. P. Bailey, “Oasis: A Framework for Linking Notification Delivery to the Perceptual Structure of Goal Directed tasks,” J. ACM Trans. on Computer-Human Interaction (TOCHI), Vol.17, Iss.4, No.15, 2010.
  2. [2] R. F. Adler and R. Benbunan-Fich, “Self-Interruption in Discretionary Multitasking,” Computer in Human Behavior, Vol.29, Iss.4, pp. 1441-1449, 2013.
  3. [3] J. Jin and L. A. Dabbish, “Self-Interruption on the Computer: A Typology of Discretionary Task Interleaving,” Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 1799-1808, 2009.
  4. [4] V. M. Gonzalez and G. Mark, “Constant, Constant, Multi-Tasking Craziness: Managing Multiple Working Spheres,” Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 113-120, 2004.
  5. [5] T. Tanaka and K. Fujita, “Study of User Interruptibility Estimation Based on Focused Application Switching,” Proc. of the ACM Conf. on Computer, pp. 721-724, 2011.
  6. [6] S. T. Iqbql and B. P. Bailey, “Effects of Intelligent Notification Management on Users and Their Tasks,” CHI Proc., 2008.
  7. [7] P. D. Adamczyk and B. P. Bailey, “If not now when? The effect of interruptions of different moments within task execution,” Proc. of the SIGCHI conference on Human factors in computing systems, pp. 271-278, 2004.
  8. [8] M. Nilsson, M. Drugge, U. Liljedahl, K. Synnes, and P. Parnes, “A Study on Users’ Preference on Interruption When Using Wearable Computers and Head Mounted Displays,” in Communications IEEE PerCom05, pp. 149-158, 2005.
  9. [9] M. Czerwinski, E. Cutrell, and E. Horvitz, “Instant Messaging and Interruption:Effects of Relevance and Timing,” People and Computers XIV: Proc. of HCI 2000, British Computer Society, Vol.2, pp. 71-76, 2000.
  10. [10] Mitya and Norman, “Psychological Issues in Support of Multiple Activities,” in D. A. Norman and S. W. Draper (Eds.), User Centered Systems Design: New Perspectives on Human-Computer Interaction, Hillsdale: Lawrence Erlbaum Associates, pp. 265-284, 1986.
  11. [11] T. Gillie and D. Broadbent, “What Makes Interruptions Disruptive? A Study of Length, Similarity, and Complexity,” Psychological Research, Vol.50, Iss.4, pp. 243-250, 1989.
  12. [12] M. Czerwinski, E. Cutrell, and E. Horvitz, “Instant Messaging and Interruption:Influence of Task Type on Performance,” OZCHI 2000 Conf. Proc., pp. 356-361, 2000.
  13. [13] E. Cutrell, M. Czerwinski, and E. Horvitz, “Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance,” Proc. of Human-Computer Interaction, pp. 263-269, 2001.
  14. [14] H. Muller, A. Kazakova, M. Pielot, W. Heuten, and S. Boll, “Ambient Timer Unobtrusively Reminding Users of Upcoming Tasks with Ambient Light,” Proc. of Human-Computer Interaction – INTERACT, Vol.8117, pp. 211-228, 2013.
  15. [15] H. Mueller, M. Pielot, and R. Oliveira, “Towards Ambient Notification,” Peripheral Interaction: Embedding HCI into Everyday Life – Workshop at INTERACT, 2013.
  16. [16] J. Fogarty, S. E. Hudson, and J. Lai, “Examining the Robustness of Sensor-Based Statistical Models of Human Interruptibility,” Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 207-214, 2004.
  17. [17] S. E. Hudson, J. Fogarty, C. G. Atkeson, D. Avrahami,J. Forlizzi, S. Kiesler, J. C. Lee, and J. Yang, “Predicting Human Interruptibility with Sensors: A Wizard of Oz Feasibility Study,” Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 257-264, 2003.
  18. [18] E. Horvitz, J. Breese, D. Heckerman, D. Hovel, and K. Rommelse, “ The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users,” Proc. of the 14th Conf. on Uncertainty in Artificial Intelligence, Madison, WI, pp. 256-265, 1998.
  19. [19] P. Vorburger, A. Bernstein, and A. Zurfluh, “Interruptability Prediction Using Motion Detection,” 1st Int.Workshop on Managing Context Information in Mobile and Pervasive Environments MCMP-05, 2011.
  20. [20] M. Haller, C. Richter, P. Brandl, S. Gross, G. Schossleitner, A. Schrempf, H. Nii, M. Sugimoto, and M. Inami, “Finding the Right Way for Interrupting People Improving Their Sitting Posture,” Human-Computer Interaction INTERACT, Vol.6947, pp. 1-17, 2011.
  21. [21] S. T. Iqbal and B. P. Bailey, “Leveraging Characteristics of Task Structure to Predict the Cost of Interruption,” Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 741-750, 2006.
  22. [22] J. Zacks, B. Travesky, and G. Iyer, “Perceiving, Remembering, and Communicating Structure in Events,” J. of Experimental Psychology: General, Vol.130, No.1, pp. 29-58, 2001.
  23. [23] D. C. McFarlane, “The Scope and Importance of Human Interruption in Human Computer Interaction Design,” Human Computer Interaction, Vol.17, 2002.
  24. [24] D. C. McFarlane, “Interruption of People in Human-Computer Interaction: A General Unifying Definition of Human Interruption and Taxonomy,” Naval Research Laboratory (NRL/FR/5510979870), Washington DC, 1997.
  25. [25] G. Mark, V. M. Gonzalez, and J. Harris, “No Task Left Behind, Examining the Nature of Fragmented Work,” Proc. of the SIGCHI Conference on Human Factors in Computing Systems, pp.321-330, 2005.
  26. [26] D. C. McFarlane, “Coordinating the Interruption of People in Human Computer Interaction,” Human-Computer Interaction INTERACT, IFIP TC.13-1, pp. 95-303, 2002.
  27. [27] D. C. McFarlane, “Comparison of Four Primary Methods for Coordinating the Interruption of People in Human-Computer Interaction,” Human-Computer Interaction, Vol.17, pp. 63-139, 2002.

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