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1 Survey on Boredom as Indicator of Work Underload Measure NICIE Lab Seminar 2004.03.15 (Mon) Chang Hoon Ha.

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Presentation on theme: "1 Survey on Boredom as Indicator of Work Underload Measure NICIE Lab Seminar 2004.03.15 (Mon) Chang Hoon Ha."— Presentation transcript:

1 1 Survey on Boredom as Indicator of Work Underload Measure NICIE Lab Seminar 2004.03.15 (Mon) Chang Hoon Ha

2 2 Contents  Background  Introduction  Work Underload Measure  Summary and Further Studies

3 3 Background  Human error causation paradigms; What causes human errors? [3]  Engineering error paradigm Focuses on the technical aspects of a system Includes the design of MMI and issues around plant automation  Individual error paradigm Considers both motivational and personality issues as well as accident proneness of individuals  Cognitive error paradigm Focuses on the psychological or information processing causes of human errors Covers both skill and decision-making errors Considers the capabilities and limitations of the individual human information processing system  Organizational error paradigm Focuses on management decision-making, safety management and issues such as safety culture, participation, competence, control and communication

4 4 Background  Designing the man ‘out of the loop’ through automation is often considered as a proposal for reducing risk. However, automation may not always remove human error and indeed may create new sources of human reliability. [3]  One of the outcomes of increased automation is that the operator will have less to do.  “Automation may accompany the performance deterioration in underload conditions” – Byrne and Parasuraman [1]  “The overall performance will decrease with task underloading” – Yerkes-Dodson Law [2]  “ The operator’s role is changed to one of the supervisory monitoring of an automated system, but with reduced information about the system itself (humans are generally poor at monitoring tasks that require extended periods of vigilance)” – Bainbridge [3]

5 5 Introduction  Definitions of boredom  “An unpleasant, transient affective state in which the individual feels a pervasive lack of interest in and difficulty concentrating on the current activity and feels that it takes conscious effort to maintain or return attention to that activity” – Fisher (1998) [4]  “A state in which the organism was underloaded not overloaded” – Welford (1965)  Characteristics of boredom  “The essential behavioral component of boredom is the struggle to maintain attention”  “Almost the opposite of the totally focused attentional state called “flow”, that is, there is complete involvement in the task and no awareness of any distractions” – Csikszentmihalyi (1975) [4]

6 6 Introduction  Subjective experience of boredom in the view of interaction between human and task [7]  Cognitive components Arising from the operator’s perception of the demands which are imposed by the task/operational environment Meaningless and lacking challenge Requiring limited activity Repetitive and constraining  Affective components Arising from the operator’s interpretation of the imposed demands Feelings of monotony Frustration Subjective variety Distraction Daydreaming Dissatisfaction and satisfaction Lack of interest fatigue

7 7 Work Underload Measure (I)  C. D. Braby, D. Harris and H. C. Muir’s Experiment (1993) - Using subjective data and physiological data [7]  Subjects: 16 male with a mean of 24.7 years  Flight instrument monitoring task  To investigate the relationship between physiological and subjective indices of work underload  30 Subjective states are given in the right table. The number of subjects who responded ‘Yes’ to each of subjective states is presented StateFrequencyStateFrequency Stretched1Absorbed0 Tired2Alert1 Annoyed0Bored9 Active0Unsatisfied2 Frustration4Free from concentration 3 Satisfied1Busy0 Concentrating0Stimulated1 Inactive1Disinterested8 Quite tired2Anxious2 Easily distracted 3Relaxed3 Very bored0Free to think of other things 3 Irritated0Sleepy0 In control0Daydreaming0 Pressured1Unchallenged2 Interest2Fatigue1

8 8 Work Underload Measure (I)  Measured data  Subjective data Cognitive arousal Five-point Likert Scale: Rating of ‘1’ indicated minimum alertness and 5 maximum alertness Mental effort Bedford workload scale Subjective underload 30 subjective underload states  Physiological data Heart rate (HR) and Heart rate variability (HRV) data  In this experiment, the subjective experience of work underload was described primarily in terms of those cognitive and affective states associated with boredom.  Significant decrease in autonomic arousal measured as HR and HRV is accompanied by a significant increase in the number of work underload states experienced.

9 9 Work Underload Measure (II)  Mark S. Young and Neville A. Stanton’s experiment (2002) [8]  To investigate the potential differences in attention and workload among drivers under different conditions of automation such as adaptive cruise control (ACC) or active steering (AS)  Introducing the concept of malleable attentional resource pools ; Most applied research on attention has implicitly assumed that the size of resource is fixed. But, this paper says this limit may change in the relatively short term, depending on task circumstances.  Southampton Driving Simulator (SDS) with ACC and AS was used  30 participants (17 men, 13 women) had a mean age of 25.3 years (SD=6.53) and full UK driving licenses for 6.9 years (SD=5.92)  Four levels of automation; Manual, ACC, AS, ACC+AS

10 10 Work Underload Measure (II)  Measured data  Primary task data 4 evaluative performance variables Number of lane excursions Speed instability Time spent out of lane Headway instability  Secondary task data To make a judgment as to whether the figures (presented in the lower left corner of the screen) were the same or different and used to measure spare mental capacity Variable Number of correct responses  Attention ratio data: the test for MART (Malleable Attentional Resource Theory) Amount of attentional gaze directed at secondary task

11 11 Work Underload Measure (II)  Results indicate that automation does have a significant effect on driver mental workload.  The data on attentional gaze provided a convincing indication that the size of attention resource pools can shrink directly inline with reductions in mental workload. [[Results]]

12 12 Approaches of Work Underload Measure  Performance-based measure  Is there relationship existed between work output and subjective feelings of boredom? “YES” --- Boredom was accompanied by changes in work and that, especially toward the end of the day, workers tended to talk, become restless, work more slowly, and become more variable in their output. [5] Primary task Secondary task  Subjective measure C. D. Braby’s 30 subjective states [7] C. D. Fisher’s 22 items [4] Farmer and Sundberg’s Boredom Proneness Scale (BPS); 28 item  Physiological measure  McDowall and Wells (1927) Attempt to link the development of boredom to inadequate reflex circulatory adjustments to the boring task Propose that normal vascular responses to a task are dependent on adequate interest in that task  Heart rate (HR) and heart rate variability (HRV) data derived from Electrocardiogram signal (ECG) [7]  Attentional gaze

13 13 Boredom alleviation  General strategies in the cockpit [5]  Activity-based strategy Focuses on alternation of automated monitoring with manual activity Pilots performed best in conditions under which they had some control over the automated system  Sensory-based strategy Sensory stimulation is used; “wake up” sensory systems such as viewing bright light, breathing fresh air, splashing cold water on one’s face, or aromatherapy  Rest-based strategy  Biofeedback techniques Using EEG (ElectroEncephaloGram), the assessment of the pilot’s cognitive state can be monitored and alarms offered when changes in awareness have fallen below acceptable levels.

14 14 Summary and Further Studies  Humans are prone to fatigue and boredom if they are engaged in routine or monotonous tasks.  With automation, humans have switched from being operators of equipment to being a monitoring role.  Some experimental results on work underload measure  Introducing MART saying that attentional capacity can change size in response to changes in task demands  Find out the relationship between eye movement and boredom  Work underload measure in VDU-based simulator representative of advanced MCR by using physiological method such as eye movement  Study about real-time workload estimating methodology using psychophysiological measures

15 15 References  [1] “Psychophysiology and adaptive automation”; Evan A. Bryne, Raja Parasuraman; Biological Psychology, 42, 249-268; 1996  [2] “Mental workload; Its theory and measure”; Neville Moray; Plenum press. New York and London; 1977; p 249  [3] “Human factors in safety-critical systems”; Felix Redmill and Jane Rajan; Butterworth Heinemann; 1997; chap 2.3  [4] “Effects of external and internal interruptions on boredom at work: two studies”; Cynthia D. Fisher; Journal of Organizational Behavior, 19, 503-522; 1998  [5] “Boredom: A Review”; Richard P. Smith; Human Factors, 23(3), 329-340; 1981  [6] “Monitoring Automated Displays: Effects of and Solutions for Boredom”; Christina M. Frederick-Recascino; 2001 IEEE, 5.D.3  [7] “A psychophysiological approach to the assessment of work underload”; C. D. Braby, D. Harris and H. C. Muir; Ergonomics, 1993, vol. 36, no. 9, 1035- 1042  [8] “ Malleable Attentional Resources Theory: A new Explanation for the Effects of Mental Underload on Performance”; Mark S. Young and Neville A. Stanton; Human Factors, 2002, vol. 44, no. 3, pp. 365-375


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