Introducing User-Centered Systems Design - Foundations for Designing User-Centered Systems - page 18

Table 1.4 Example usability issues arising from the behavioral level
Car interfaces—questions of legibility of characters, avoidance of glare in bright sunlight,
avoiding parallax problems with different heights of drivers, and making sure that the dials are
not obscured by the steering wheel
Making knobs and levers tactually discriminable to enable them to be used without looking to
check whether the correct control is being used (e.g., putting a wheel on the landing gear lever
in a plane)
Problem of ascertaining the physical actions of how something is used, to see whether it can be
made quicker/safer/more productive, and so on
Looking at simple errors (slips of action) that are made, to see how they can be mitigated or
prevented
Table 1.5 The original Fitts ( 1951 ) list
Humans appear to surpass present-day (i.e., 1951) machines with respect to:
• Ability to detect small amounts of visual or acoustic energy
• Ability to perceive patterns of light or sound
• Ability to improvise and use flexible procedures
• Ability to store very large amounts of information for long periods and to recall relevant facts at
the appropriate time
• Ability to reason inductively
• Ability to exercise judgment
Present-day machines appear to surpass humans with respect to:
• Ability to respond quickly to control signals, and to apply great force smoothly and precisely
• Ability to perform repetitive, routine tasks
• Ability to store information briefly and then to erase it completely
• Ability to reason deductively, including computational ability
• Ability to handle highly complex operations, that is, to do many different things at once
1.4.2 Behavioral Aspects
When we discuss the behavioral aspects of the user, we refer to the basic behaviors
users can produce. The behavioral level builds on the anthropometric level as the
physical aspects of the body are used to produce simple behaviors. Table 1.4
provides several examples, drawing on a wide range of application areas.
Behavioral analysis has supported and led to the creation of checklists of those
tasks best performed by humans and those best performed by machines. Table 1.5
shows an example of such a list, where human and machine tasks could be
assigned on the basis of better fit. Such lists have been critiqued for being too static
(Sheridan 1992 ), but the exercise of making such lists, updated according to
technological innovations and changes in human expectations and abilities through
training, can be useful. An excellent example of the evolution of the way we think
about task allocation is the recent success of IBM's Watson system. Historically,