Detecting system failures from durations and binary cues

Durations are often used to judge the status of an invisible process. However, the apparent duration of an interval depends on the actual duration and on other variables, such as the workload during the interval and the person's expectations. An experiment dealt with the use of durations as an information source on the state of an invisible process and the effects of expectations and workload on decisions regarding the process. Eighty-nine participants observed a computerized simulation of a process which could be either intact or faulty, with intact processes ending on average sooner than faulty ones, and they had to indicate whether or not the process is intact and to estimate its duration. A binary cue with either intermediate or no validity indicated whether the process was supposedly intact or not, generating expectations about the duration of the process. Perceived durations and the decisions about the intactness of a process depended on the actual process duration, as well as on the expectations generated by the binary cue. In addition, task workload affected time estimates, but it had no effect on participants' tendency to adhere to cue recommendations or their ability to distinguish between intact and faulty processes. Results show that users' duration-based decisions about the status of a computerized process are affected by internal and external cues. While users can use durations as an information source, they should, whenever possible, be accompanied by additional indicators, lowering the inherent uncertainty in the duration estimation process.

[1]  D Shinar,et al.  Duration estimates and users' preferences in human-computer interaction. , 1996, Ergonomics.

[2]  M. Boltz,et al.  Time estimation and expectancies , 1993, Memory & cognition.

[3]  S. Breznitz Cry Wolf: The Psychology of False Alarms , 1984 .

[4]  Joachim Meyer,et al.  Use of Warnings in an Attentionally Demanding Detection Task , 2001, Hum. Factors.

[5]  Greg C. Elvers,et al.  The Effects of Correlation and Response Bias in Alerted Monitor Displays , 1997, Hum. Factors.

[6]  Kathleen L. Mosier,et al.  Does automation bias decision-making? , 1999, Int. J. Hum. Comput. Stud..

[7]  Scott W. Brown Attentional resources in timing: Interference effects in concurrent temporal and nontemporal working memory tasks , 1997, Perception & psychophysics.

[8]  M. Boltz,et al.  The role of learning in remembered duration , 1998, Memory & cognition.

[9]  M. R. Jones,et al.  Dynamic attending and responses to time. , 1989, Psychological review.

[10]  R. D. Ray,et al.  Trends in Ergonomics/Human Factors II , 1985 .

[11]  Joachim Meyer,et al.  Conceptual Issues in the Study of Dynamic Hazard Warnings , 2004, Hum. Factors.

[12]  Robert D. Sorkin,et al.  FORUM: Why are people turning off our alarms? , 1988 .

[13]  Joachim Meyer,et al.  Displaying a boundary in graphic and symbolic "wait" displays: Duration estimates and users' preferences , 1995, Int. J. Hum. Comput. Interact..

[14]  Joachim Meyer,et al.  Effects of Warning Validity and Proximity on Responses to Warnings , 2001, Hum. Factors.

[15]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .

[16]  Neil A. Macmillan,et al.  Detection theory: A user's guide, 2nd ed. , 2005 .

[17]  Graham A. Murrell,et al.  Combination of evidence in a probabilistic visual search and detection task , 1977 .

[18]  Dan Zakay,et al.  Chapter 10 Subjective Time and Attentional Resource Allocation: An Integrated Model of Time Estimation , 1989 .

[19]  P. Hancock,et al.  How cognitive load affects duration judgments: A meta-analytic review. , 2010, Acta psychologica.

[20]  Joachim Meyer,et al.  Task structure and the apparent duration of hierarchical search , 2001, Int. J. Hum. Comput. Stud..

[21]  Florian Schaefer,et al.  The Effect of System Response Times on Temporal Predictability of Work Flow in Human-Computer Interaction , 1990 .

[22]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[23]  S. W. Brown,et al.  Time perception and attention: The effects of prospective versus retrospective paradigms and task demands on perceived duration , 1985, Perception & psychophysics.

[24]  John Anderson,et al.  An integrated theory of prospective time interval estimation: the role of cognition, attention, and learning. , 2007, Psychological review.