Introduction to Work and Organizational Psychology

Gerhard Ohrband8th lectureWorkload and Task Allocation

Course structure

Part I Introduction1 Managing diversity2 History and context for Work and Organizational

Psychology / Roles and methods

Part IIPeople at work3 Job Analysis and Design4 Personal Selection5 Training

Course structure

6 Performance Appraisal: Assessing and Developing Performance and Potential

7 Job Stress and Health

Part IIIHuman Factors at Work8 Workload and Task Allocation9 Work Environments and Performance10 The Design and Use of Work Technology11 Safety at Work

Course structure

Part IVOrganizations at Work12 Leadership and management13 Work motivation14 Teams: the challenges of cooperative work15 Organizational development (OD)

Part III – Human Factors at work8 Workload and Task Allocation

Outline:1. What is workload?2. Why assess workload?3. Requirements for effective workload

assessment4. Workload assessment techniques5. The application of workload assessment

techniques6. Automation and task allocation

1. What is workload?

performance problems associated with tasks high in explicit demand (i.e., the overload or cognitive strain scenario)

exploring/modelling errors at lower levels of the task demand spectrum

Physical vs. mental workload Focus on mental workload Examples: air traffic controllers, pilots,

process control operators and medical staff Primary tasks: cognitive processes which

require memory, attention, perception and communication skills rather than extensive physical demands

Definition (Kramer, 1991): Mental workload can be conceptualized as the costs that human operators incur in performing tasks

Industries traditionally defined ashigh risk

Defence Road transportation Railways Aerospace Process control Power generation

Workload and error The complexity of the relationship between workload,

task performance and task load can be illustrated with reference to the debate in which a number ofinvestigators have aimed to provide an answer to the question “How much workload is too much?” (e.g., de Waard, 1996; Meijman and O’Hanlon, 1984;Teigen, 1994).

To answer this question, investigators have found it useful todivide the Yerkes-Dodson inverted U function into 6 task performance-related regions as shown in Figure 8.

Task performance and workload as a function of demand

Single resource models

Kahneman’s capacity of attention

Performance Resource Function (PRF)

Multiple resource models the human information processing system is a multiple

channel processor(e.g., it has multiple structures)

each processor, or group of processors, has its own internal capacity.

In MRT approaches, mental resources are often seen as analogous to fuel that is consumed by various activities, or as a tank of liquid to be divided among several competing tasks (Wickens, 1984).

In stressful conditions, or multitasking situations, the amount of resource may become depleted and give rise to interference effects. One important feature of this view is the idea that the impact ofchanges in task demand on mental resources may not be purely quantitative, but may also be qualitative as well, (i.e., structural).

Sources of mental resource relative to information processing stage

Diagrammatic representation of Wickens Multiple Resource Theory

Composite models relatively new type of cognitive modelling activity that aims

to use elements of the single channel hypothesis and resource theory to account for workload effects in human performance.

These composite models are usually represented in the form of computer programs that are applied to tasks and used to predict various aspects of human performance.

The ability of these models to reproduce workload effects has frequently been mentioned as a justification for their development – although the extent to which they have managed to do this has been a matter of some debate.

Perhaps the most frequently mentioned composite model in the workload literature has been the Executive-Process Interactive Control (EPIC) model developed by Kieras and Meyer, 1997

2. Why assess workload? Solve practical problems in the workplace Effects of workload on performance, well-being, health

and safety Design complex task environments that do not place

disproportionate demands on the human operator 1. Safety critical systems such as air traffic control

and aircraft cockpit design 2. Aid evaluation of the effects of automation or the

introduction of new technology and other changes in the nature of work on individual well-being and health

3. Assessment of individual operators (selection or training)

Acute vs. chronic effects of workload

3. Requirements for effective workload assessment

Sensitivity Diagnosticity Intrusiveness Validity Reliability Acceptability Applicability Generality

4. Workload assessment techniques Subjective/self-report measures: Cooper-Harper scale (Cooper and Harper, 1969) NASA task load index (TLX) (Hart and

Staveland, 1988) Subjective workload assessment technique

(SWAT) (Reid and Nygren, 1988) Instantaneous self-assessment technique (ISA) Situation awareness rating scale (SART)

(Taylor, 1989) Situation awareness global assessment

technique (SAGAT) (Endsley, 1995)

NASA Task Load Index (TLX)

NASA-TLX Scoring example

Subjective Workload Assessment Technique - SWAT

Time Based Task Loading Models

Performance measures Primary task measures Secondary task measures

Primary task: the task or system function whose workload is to be measured

Secondary task: one task that is performed concurrently with a primary task to investigate the workload associated with the latter

Physiological Measures cardiac function brain function respiration eyeblinks pupil dilation urine blood saliva (hormonal and immunological

changes)

5. The application of workload assessment techniquesSummary of the capability of different broad categories of workload assessment techniques to satisfy different requirements for use

Intrusiveness Sensitivity Diagnosticity Applicability Acceptability

Subjective Measures

Post-task measures

Generally not intrusive

Good but may depend on length of task

Generally difficult to use diagnostically

Minimal equipment requirements

Very good

Instantaneous measures

Potentially intrusive

Good Provides only a global measure

Some equipment required

good

Performance measures

Primary task Not intrusive Reasonable but difficulties in interpreting variation

Poor Depends on task complexity and variability

Should be acceptable to operator

Secondary task Potential for intrusion

Good Very good May require training and extra equipment

Additional demands may be distracting

Intrusiveness Sensitivity Diagnosticity Applicability Acceptability

Physiological measures

EEG measures Not usually a problem

Good Varies according to specific measure but reasonably good

Extensive equipment and analysis requirements

Some potential problems

ECG measures Not intrusive Good Not fully established

Extensive equipment and analysis requirements

Not generally found to be problematical

6. Automation and task allocation advancements in computer technology

Wickens (1992): three reasons for automation

1. Situations which may be hazardous or dangerous to humans or which humans cannot perform (diving operations, handling of toxic materials)

2. Tasks with high levels of workload for the human operator (autopilots)

3. Overcome human limitations, e.g. in memory or attention (radar advance warning systems)

Dangers of automation Thoughtless design which may simply require the

operator to perform those functions or tasks that have been unable to be automated

Difficulties:1. Automation may induce feelings of loss of control and

situation awareness when the human is operating “out of the loop”

2. Risk of deskilling the operator in highly automated systems

3. Automation does not always lead to improved performance and levels of operator workload

Unscheduled manual interventions (Hockey and Maule, 1995)

operators overriding automated systems in order to assume control of production or other processes at times when the system is scheduled to be under automatic control

Why?1. desire for control2. motivation to improve the speed and quality

of production3. low trust in the automated system

Selection of the appropriate type and degree of automation

Goal: achieving desirable levels of safety and effectiveness

Question: Which tasks should be allocated to the operator and which to be automated part of the system?

Task allocation/function allocation Traditional approaches: Fitt’s list (1951,

Kantowitz and Sorkin, 1987) Think about it: Where are machines and

where are humans more effective?

Answer: Machines: performing mathematical and

computational operations, integrating information and dealing with predictable events reliably

Human operators: making decisions, inductive reasoning, more flexible, particularly when unexpected events occur and possess experience of previous events

Dynamic task allocation (DTA) Def.: flexible allocation of tasks or

functions between the operator and the system in human-machine systems; sometimes referred to as adaptive control

some or all of the task elements have the potential to be carried out by either the operator or the system itself

control of task allocation: explicit and implicit allocation

explicit: operator control, implicit: computer control of task allocation

Advantages of DTA1. Workload of operators will be maintained at a relatively

constant level2. Resources of the systems (both human and computer)

will be used more fully3. More acceptances by the operators than static

automation4. Enhancement of situation awareness and prevention of

decay of manual control and problem-solving skills which may be required in breakdown or emergency situations

5. Enhancement of the operator’s ability to diagnose failures and errors made by the computer

Discussion Points

1. What are the different workload assessment techniques?

2. Explain the hazards of automation.3. Discuss the objectives of workload

assessment.

Literature Hockey, G.R.J. and Maule, A.J. (1995).

Unscheduled manual interventions in automated process control. Ergonomics, 38, 2504-24.

Kramer, A.F. (1991). Physiological metrics of mental workload: a review of recent progress. In D.L. Damos (ed.), Multiple-Task Performance. London: Taylor and Francis