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CS 544 Human Abilities

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Acknowledgement: Some of the material in these lectures is based on material ... Movement time prediction in human-computer interfaces. ( Reprinted in BGBG 483-493) ... – PowerPoint PPT presentation

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Title: CS 544 Human Abilities


1
CS 544Human Abilities
  • Human Motor Capabilities

Acknowledgement Some of the material in these
lectures is based on material prepared for
similar courses by Saul Greenberg (University of
Calgary), Ravin Balakrishnan (University of
Toronto), James Landay (University of California
at Berkeley), monica schraefel (University of
Toronto), and Colin Ware (University of New
Hampshire). Used with the permission of the
respective original authors.
2
Example Pointing Device Evaluation
  • Real task interacting with GUIs
  • pointing is fundamental
  • Experimental task target acquisition
  • abstract, elementary, essential

3
Fitts Law (Paul Fitts, 1954)
Task difficulty is analogous to information -
execution interpreted as human rate of
information processing
4
MT (secs)








different way to calculate IP










b slope IP 1/b












a
ID (bits) log2(D/W 1)
5
50 years of data
Reference MacKenzie, I. Fitts Law as a research
and design tool in human computer interaction.
Human Computer Interaction, 1992, Vol. 7, pp.
91-139
6
What does Fitts law really model?
Target Width
Target Width
Velocity
(c)
(a)
(b)
Distance
7
Power law of Practice
  • task time on nth trial follows a power law
  • Tn T1 n-a, where a .4 (empirically
    determined)
  • i.e., you get faster the more times you do it!
  • applies to skilled behavior (sensory motor)
  • does not apply to knowledge acquisition or quality

8
Hicks law
  • Reaction time T a blog2(n1)
  • Where n is the number of choices
  • a, b empirically determined constants
  • log2(n1) represents amount of information
    processed by human operator (in Bits)
  • Example a telephone switch panel consisting of
    10 buttons, any one of which may light up,
    prompting the operator to press the lit button.
  • Unequal probabilities

9
Using these laws to predict performance
  • Which will be faster on average?
  • pie menu (bigger targets less distance)?

10
Beyond pointing Trajectory based tasks
11
From targets to tunnels
  • 2 goals passing
  • 3 goals passing
  • N1 goals passing
  • ? goals passing

12
Steering Law (Accot, 1997)Beyond Fitts Law
Models for trajectory based HCI
tasks.Proceedings of ACM CHI 1997 Conference
13
Some results (from Accot, 1997)
14
Readings
  • MacKenzie, I. S. (1992). Movement time prediction
    in human-computer interfaces. (Reprinted in BGBG
    483-493).
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