Shamsi T. Iqbal
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.
- Adamczyk, P.D. and B.P. Bailey. If Not Now When? The Effects of Interruptions at Different Moments within Task Execution. CHI, 2004, 271--278.]] Google Scholar
Digital Library
- Altmann, E.M. and J.G. Trafton. Task Interruption: Resumption Lag and the Role of Cues. CogSci, 2004.]]Google Scholar
- Bailey, B.P., P.D. Adamczyk, T.Y. Chang and N.A. Chilson. A Framework for Specifying and Monitoring User Tasks. Journal of Computers in Human Behavior, to appear, 2006.]]Google Scholar
- Bailey, B.P. and J.A. Konstan. On the Need for Attention Aware Systems: Measuring Effects of Interruption on Task Performance, Error Rate, and Affective State. Journal of Computers in Human Behavior, to appear, 2006.]]Google Scholar
- Card, S., T. Moran and A. Newell. The Psychology of Human-Computer Interaction. Lawrence Erlbaum Associates, Hillsdale, 1983.]] Google ScholarDigital Library
- Chung, P.H. and M.D. Byrne. Visual Cues to Reduce Errors in a Routine Procedural Task. CogSci, 2004.]]Google Scholar
- Cutrell, E., M. Czerwinski and E. Horvitz. Effects of Instant Messaging Interruptions on Computing Tasks. CHI, 2000, 99--100.]] Google ScholarDigital Library
- Czerwinski, M., E. Cutrell and E. Horvitz. Instant Messaging and Interruption: Influence of Task Type on Performance. Annual Conference of the Human Factors and Ergonomics Society of Australia (OZCHI) , 2000, 356--361.]]Google Scholar
- Czerwinski, M., E. Cutrell and E. Horvitz. Instant Messaging: Effects of Relevance and Timing. People and Computers XIV: Proceedings of HCI, 2000, 71--76.]]Google Scholar
- Czerwinski, M., E. Horvitz and S. Wilhite. A Diary Study of Task Switching and Interruptions. Proceedings of the ACM Conference on Human Factors in Computing Systems, 2004, 175--182.]] Google ScholarDigital Library
- Degani, A. and E. Wiener. Cockpit Checklists: Concepts, Design, and Use. Human Factors, 35 (2), 345--359, 1993.]]Google ScholarCross Ref
- Dragunov, A.N., T.G. Dietterich, K. Johnsrude, M. McLaughlin, L. Li and J.L. Herlocker. Tasktracer: A Desktop Environment to Support Multi-Tasking Knowledge Workers. Proc. IUI, 2005, 75--82.]] Google ScholarDigital Library
- Fogarty, J., S.E. Hudson and J. Lai. Examining the Robustness of Sensor-Based Statistical Models of Human Interruptibility. CHI, 2004, 207--214.]] Google ScholarDigital Library
- Fogarty, J., A.J. Ko, H.H. Aung, E. Golden, K.P. Tang and S.E. Hudson. Examining Task Engagement in Sensor-Based Statistical Models of Human Interruptibility. CHI, 2005, 331--340.]] Google ScholarDigital Library
- Horvitz, E. and J. Apacible. Learning and Reasoning About Interruption. ICMI, 2003, 20--27.]] Google ScholarDigital Library
- Horvitz, E., A. Jacobs and D. Hovel. Attention-Sensitive Alerting. Conference Proceedings on Uncertainty in Artificial Intelligence, 1999, 305--313.]]Google Scholar
- Horvitz, E., P. Koch and J. Apacible. Busybody: Creating and Fielding Personalized Models of the Cost of Interruption. CSCW, 2004, 507--510.]] Google ScholarDigital Library
- Hudson, J.M., J. Christensen, W.A. Kellogg and T. Erickson. ""I'd Be Overwhelmed, but It's Just One More Thing to Do"": Availability and Interruption in Research Management. CHI, 2002, 97--104.]] Google ScholarDigital Library
- Hudson, S.E., 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. CHI, 2003, 257--264.]] Google ScholarDigital Library
- Iqbal, S.T., P.D. Adamczyk, S. Zheng and B.P. Bailey. Towards an Index of Opportunity: Understanding Changes in Mental Workload During Task Execution. CHI, 2005, 311--320.]] Google ScholarDigital Library
- Iqbal, S.T. and B.P. Bailey. Investigating the Effectiveness of Mental Workload as a Predictor of Opportune Moments for Interruption. CHI, 2005, 1489--1492.]] Google ScholarDigital Library
- Jackson, T.W., R.J. Dawson and D. Wilson. The Cost of Email Interruption. Journal of Systems and Information Technology, 5 (1), 81--92, 2001.]]Google ScholarCross Ref
- John, B.E., K. Prevas, D.D. Salvucci and K. Koedinger. Predictive Human Performance Modeling Made Easy. CHI, 2004, 455--462.]] Google ScholarDigital Library
- Maglio, P. and C.S. Campbell. Tradeoffs in Displaying Peripheral Information. CHI, 2000, 241--248.]] Google ScholarDigital Library
- McCrickard, D.S., R. Catrambone, C.M. Chewar and J.T. Stasko. Establishing Tradeoffs That Leverage Attention for Utility: Empirically Evaluating Information Display in Notification Systems. IJHCS, 58 (5), 547--582, 2003.]] Google ScholarDigital Library
- McFarlane, D.C. Coordinating the Interruption of People in Human-Computer Interaction. Proceedings of the IFIP TC.13 International Conference on Human-Computer Interaction, 1999, 295--303.]]Google Scholar
- McFarlane, D.C. and K.A. Latorella. The Scope and Importance of Human Interruption in Hci Design. Human-Computer Interaction, 17 (1), 1--61, 2002.]]Google ScholarDigital Library
- Miyata, Y. and D.A. Norman. Psychological Issues in Support of Multiple Activities. In Norman, D.A. and Draper, S.W. (eds.) User Centered System Design: New Perspectives on Human-Computer Interaction, Lawrence Erlbaum Associates, Hillsdale, NJ, 1986, 265--284.]]Google Scholar
- Monk, C.A., D.A. Boehm-Davis and J.G. Trafton. The Attentional Costs of Interrupting Task Performance at Various Stages. HFES, 2002.]]Google ScholarCross Ref
- Navon, D. and D. Gopher. On the Economy of the Human Processing Systems. Psychological Review, 86, 254--255, 1979.]]Google ScholarCross Ref
- Newell, A. and P.S. Rosenbloom. Mechanisms of Skill Acquisition and the Law of Practice. In Anderson, J.R. ed. Cognitive Skills and Their Acquisition, Erlbaum, Hillsdale, NJ, 1981, 1--55.]]Google Scholar
- Ritter, F.E., G.D. Baxter, G. Jones and R.M. Young. Supporting Cognitive Models as Users. ACM Transactions on Computer-Human Interaction, 7 (2), 141--173, 2000.]] Google ScholarDigital Library
- Rubinstein, J.S., D.E. Meyer and J.E. Evans. Executive Control of Cognitive Processes in Task Switching. Journal of Experimental Psychology: Human Perception and Performance, 27 (4), 763--797, 2001.]]Google ScholarCross Ref
- Shneiderman, B. Designing the User Interface. Pearson Addison Wesley, Third Edition, 1997.]] Google ScholarDigital Library
- Tollinger, I., R.L. Lewis, M. McCurdy, P. Tollinger, A. Vera, A. Howes and L.J. Pelton. Supporting Efficient Development of Cognitive Models at Multiple Skill Levels: Exploring Recent Advancements in Constraint-Based Modeling. CHI, 2005, 411--420.]] Google ScholarDigital Library
- Trafton, J.G., E.M. Altmann, D.P. Brock and F.E. Mintz. Preparing to Resume an Interrupted Task: Effects of Prospective Goal Encoding and Retrospective Rehearsal. IJHCS, 58, 583--603, 2003.]] Google ScholarDigital Library
- Wickens, C.D. Multiple Resources and Performance Prediction. Theoretical Issues in Ergonomic Science, 3 (2), 159--177, 2002.]]Google ScholarCross Ref
- Zacks, J., B. Tversky and G. Iyer. Perceiving, Remembering, and Communicating Structure in Events. Journal of Experimental Psychology: General, 130 (1), 29--58, 2001.]]Google ScholarCross Ref
- Zijlstra, F.R.H., R.A. Roe, A.B. Leonora and I. Krediet. Temporal Factors in Mental Work: Effects of Interrupted Activities. Journal of Occupational and Organizational Psychology, 72, 163--185, 1999.]]Google ScholarCross Ref
Index Terms
- Leveraging characteristics of task structure to predict the cost of interruption
Recommendations
Understanding changes in mental workload during execution of goal-directed tasks and its application for interruption management
Notifications can have reduced interruption cost if delivered at moments of lower mental workload during task execution. Cognitive theorists have speculated that these moments occur at subtask boundaries. In this article, we empirically test this ...
Investigating the effectiveness of mental workload as a predictor of opportune moments for interruption
CHI EA '05: CHI '05 Extended Abstracts on Human Factors in Computing SystemsThis work investigates the use of workload-aligned task models for predicting opportune moments for interruption. From models for several tasks, we selected boundaries with the lowest (Best) and highest (Worst) mental workload. We compared effects of ...
If not now, when?: the effects of interruption at different moments within task execution
CHI '04: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsUser attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments ...
Comments