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Simple Models of Human Performance
Predictive Evaluation with Hick’s Law, Fitt’s Law, Power Law of Practice
This material has been developed by Georgia Tech HCI faculty, and continues to evolve. Contributors include Gregory Abowd, Jim Foley, Diane Gromala, Elizabeth Mynatt, Jeff Pierce, Colin Potts, Chris Shaw, John Stasko, and Bruce Walker. Comments directed to foley@cc.gatech.edu are encouraged. Permission is granted to use with acknowledgement for non-profit purposes. Last revision: Jan 2014.
UI Design - Georgia Tech 2
Simple User Models
• Idea: If we can build a model of how a user works, then we can predict how s/he will interact with the interface § Predictive model à predictive evaluation
• No mock-ups or prototypes!
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Two Types of User Modeling
• Stimulus-Response § Hick’s law § Practice law § Fitt’s 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) – Not discussed here
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Power law of practice
• Tn = T1n-a § Tn to complete the nth trial is T1 on the first trial
times n to the power -a; a is about .4, between .2 and .6
§ Skilled behavior - Stimulus-Response and routine cognitive actions
– Typing speed improvement – Learning to use mouse – Pushing buttons in response to stimuli – NOT learning
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How can we use this law?
Discussion time.
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Uses for Power Law of Practice
• What did you think of?
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Uses for Power Law of Practice
• Use measured time T1 on trial 1 to predict whether time with practice will meet usability criteria, after a reasonable number of trials § How many trials are reasonable?
• Predict how many practices will be needed for user to meet usability criteria § Determine if usabiltiy criteria is realistic
• BUT what is the limitation on applicability?
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Hick’s law
• Decision time to choose among n equally likely alternatives § T = Ic log2(n+1)
§ Ic ~ 150 msec
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How can we use this law?
Discussion time
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Uses for Hick’s Law
• What did you think of? • 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
Uses for Hick’s Law
• Web page design § Minimize choices – especially on landing page § Keep it simple stupid (KISS)
• Bury low-probability choices in a sub-menu
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Open Close Save Save As ….
Movie Web Page Pictures
Open Close Save Save As Movie Save As Web Page Save as Pictures
What is the downside?
Twitter – Old and New
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Which is which?
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Fitts’ Law
• Models movement times for selection (reaching) tasks in one dimension
• Basic idea: Movement time for a selection task § Increases as distance to target increases § Decreases as size of target increases
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Original Experiment
• 1-D d w
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Components
• MT - Movement time
• k1 and k2 are experimental constants
MT = k1 + k2 *log2 (d/w + 1.0)
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Exact Equation • Run empirical tests to determine k1 and
k2 in MT = k1 + k2* ID • Will get different ones for different
input devices and device uses
MT
ID = log2(d/w = 1.0)
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How can we use this law?
Discussion time.
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Uses for Fitt’s Law
• What did you think of?
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Uses for Fitt’s Law
• Menu item size • Icon size • Scroll bar target size and placement
§ Up / down scroll arrows together or at top and bottom of scroll bar
• Pop-up menus faster than pull-down menus • Pie menus (pop-up) better than rectangular
§ menu items all start at menu center
§ wedge-shaped target areas become large
More implications
• Edges and corners of display easy to acquire - pointer remains at the screen edge regardless of how much further the mouse is moved (Mac OS Tool Bar)
• Top-of-screen menus (Mac OS) easier to acquire than top-of-window menus (Windows OS) – but may have to move further
• Pop-up menus opened faster than pull-downs - pop-up appears at current cursor position – no movement
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Compare Menu Item Sizes J
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End
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