Simple models of human performance

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Simple models of human performance

• Predictive Evaluation with Hicks Law Fitts Law

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Agenda
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Two types of user modeling

• Stimulus-Response
• Hicks law
• Fitts law
• Cognitive human as interperter/predictor
  based on Model Human Processor (MHP)
• Key-stroke Level Model
• Low-level, simple
• GOMS (and similar) Models
• Higher-level (Goals, Operations, Methods,
  Selections)

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Hicks law

• Decision time to choose among n equally likely
  alternatives
• T Ic log2(n1)
• Ic 150 msec
• What might this be good for?

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One possible use

• Menu selection
• Which will be faster as way to choose from 64
  choices? Go figure
• Single menu of 64 items
• Two-level menu of 8 choices at each level
• Two-level menu of 4 and then 16 choices
• Two-level menu of 16 and then 4 choices
• Three-level menu of 4 choices at each level
• Binary menu with 6 levels

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Fitts Law

• Models movement times for a well-rehearsed
  selection (reaching) tasks in one dimension
• Basic idea movement time (MT) is proportional to
  Index of difficulty (ID) of a selection task
• MT increases as distance (A or D) to target
  increases
• MT decreases as size of target (W or S) increases

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Original Experiment

• 1-D

d
w
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Index of difficulty (ID)

• Measure difficulty of selection task
• ID log2(d/w 1.0)
• bits
• d distance between targets
• w target width

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Movement time (MT)
MT

• MT a b ID

Difficulty
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How MT is determined

• Empirical measurement establishes constants a and
  b
• Different for different devices and different
  ways the same device is used

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Extending it to 2-D

• What is w?
• Possible ws for 2-D
• smaller-of
• W (width of target along the approach vector)

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Applications

• When does it apply? When does it not?
• How used in interface design?

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Keystroke-Level Model (KLM)

• Decompose tasks into low-level elements
• Pressing mouse button, keystroke, pointing w/
  mouse
• Calculate prediction for total execution time
• Best for automated behavior

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Upcoming

• Friday Cognitive Models
• DFAB 12.2, 12.5 (skip 12.3, 12.4)
• Card, Moran, Newell article
• Monday Contextual Models
• Nardi article