Interaction
James Slack
CPSC 533C
March 3, 2003
Introduction
• Visualization give us interfaces for complex
computer-based systems
• Interaction reduces cognitive load
• 3 classes of interlocking feedback loops
The 3 Feedback Loops
• Visual-Manual Control
• View Refinement and Navigation
• Problem Solving
Visual-Manual Control Loop
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•
•
•
Low level interaction
Visual control of hand position
Selection of objects on the screen
Reaction times
Choice Reaction Times
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•
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How fast can you choose something?
Visual signal: 130 msec response time
700 msec if signals aren’t expected
Reaction time proportional to logarithm of
the number of choices
• Speed-accuracy trade-off
2D Positioning and Selection
• How fast can you select something (from a
display, including positioning)?
• Selection time proportional to logarithm of
distance divided by target object width
(Fitts’ law)
• Fitts’ law can account for other time details
associated with HCI, like lag
Visual-Manual Feedback Loop
Detect start
signal
Judge distance
to target
no
In target?
Human processing
Effect hand
movement
yes
Next task
Machine processing
Update display
Measure hand position
Colin Ware, Information Visualization, Chapter 10, page 338
Skill Learning
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•
•
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Power law of practice
Applies to repeated tasks over time
Experience is a large factor in learning
Design interfaces should minimize learning
new tasks
• People can tolerate small changes
Vigilance
•
•
1.
2.
3.
4.
Principle: target detection, sparse targets
Is this boring? Vigilance is hard
Vigilance drops greatly over first hour
Fatigue large negative influence
Need to focus, no multitasking
Irrelevant signals reduce vigilance
Reminder
• Vigilance is hard
• Move visual signal into optimal spatial or
temporal range helps detection
• Make signals different from noise
• Use of colour, motion, texture to make
things stand out
View Refinement & Navigation
Loop
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•
•
•
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Exploration of extended, detailed spaces
Locomotion
Viewpoint control
Map orientation
Focus, context, scale
Rapid interaction with data
Navigation Control Loop
Spatial
data model
Working
memory
Visualization
of task
Computer
databases
Navigation
control
Cognitive
logical and
spatial model
Assess
progress
Long-term memory
Colin Ware, Information Visualization, Chapter 10, page 343
Locomotion
• Moving gives dimensionality to space
• Movement should correspond to real life
• Relative movement over time is more
important than smooth motion
• Low frame rate (~2 fps) ok, but lag is issue
Spatial Navigation Metaphors
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•
1.
2.
3.
4.
Movement is usually constrained to avoid
confusion (affordances)
4 main classes of movement metaphors:
World-in-hand
Eyeball-in-hand
Walking
Flying
World-in-hand
• Perception that the environment is moving,
observer is stationary
• Good: for discrete, relatively compact data
objects
• Bad: for long distances, extended terrains
• Used in: computer game “Black & White”
Eyeball-in-hand
• Camera (or eye) is manipulable
• Not the most effective method for viewpoint
control
• Good: ?
• Bad: occlusion, hard to get some views,
limited by user’s hand positions
Walking
• Walk around in virtual reality
• Movement in real world constrained (using
treadmills)
• Good: relevant to typical locomotion
• Bad: restricted affordances
Flying
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•
•
•
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Navigation as if in an airplane
Unconstrained movement
More flexible, usable than other interfaces
Good: relevant to typical locomotion
Bad: given real flight controls, users were
confused (users had to learn a new skill)
Reading Maps
• How to get from here to there (Siegel)
1. Declare key landmarks
2. Develop rules for connecting key
landmarks, things in between
3. Form cognitive spatial map for distances
between landmarks and relative position
Landmark rules
• In virtual environments (Vinson),
1. Should be enough landmarks visible at all
times
2. Landmarks should be visually distinct
3. Landmarks should be seen at every scale
4. Landmarks should be placed in areas of
interest
Map Orientation
• Track-up display orientation
– Up is always the correct way to go
– ‘Right’ is always ‘right’
• North-up display orientation
– North is up, use a compass
– ‘Right’ becomes ‘left’ if you go ‘down’
– Common frame of reference?
Visualizing with Maps
• Overview maps are important if the space is
large
• User location and direction should be noted
• Key landmark images should be provided
• Instructions other than the map should be
provided for navigation
Focus, Context, Scale
• Spatial Scale: understanding how changes
in scale relate
• Structural Scale: levels of detail give us an
appropriate amount of information
• Temporal Scale: time compression and data
samples from many different time ranges
Distortion
• Hide information that the user doesn’t need
to see by focusing attention where it’s
relevant
• Fish eye, table lens, hyperbolic tree browser
are good examples of distortion
Other Navigation Techniques
• Rapid zooming
• Elision techniques
– Hiding information until it is needed, give
appearance of data being far away, unimportant
• Multiple Windows
– One context each, but each window is linked
Rapid Interaction with Data
• Interaction should be fluid and dynamic
• Users have to relate cause and effect
• Users may want to customize how
visualization system displays their data
– Brushing: highlighting individual data elements
interactively (parallel coordinates)
Problem-Solving Loop
• Using visual representations of data to solve
problems
• Interactive cycle, use a conceptualization as
aid to finding solution
Problem-Solving Loop
Computer
based model
Visual-spatial
Refine and test
model
hypotheses through
visualization
Visualization
of task
Computer
databases
Navigation
control
Working
memory
Cognitive logical
verbal model
Long-term memory
network
Colin Ware, Information Visualization, Chapter 10, page 366
Human Memory
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1.
2.
3.
3 Types
Iconic
Working
Long-term
Iconic Memory
• Simple visual buffer holds retinal images
• Will quickly deteriorate if not read out
• The interface between computer display and
human processing system
Working Memory
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Limited in capacity
A ‘cache’ of sorts for human processor
Separate subsystems for different tasks
A general purpose working memory?
Long-term Memory
• Lifelong memory
• Includes: episodic memory, motor skills,
perceptual skills
• Estimated: 109 bits (~100 megabytes) stored
over 35 year period
• Ideas, thoughts get lost in concept network
• Misremembering events over time
Chunks & Concepts
• A chunk is a piece of information as a
mental representation
• Chunks are either specific or general; highlevel concepts are a result of experience
• Concepts formed from hypothesis testing
process, starting from an initial idea
Human Computer Similarities
• Both systems share common traits:
– Registers / Iconic Memory
– Caches / Working Memory
– Main Memory or storage / Long-term memory
• How is this possible?
– Known to be efficient using computers
Not Really the Same
• Digital information is much more detailed
• Digital information can be retained
indefinitely
• Human visual memory tends to dissipate
• Human storage isn’t thought of as atomic
elements but of chunks and concepts
Concept Maps, Mind Maps
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Links between concepts form cognitive aid
The SPIRE system (ThemeScapes)
Trajectory maps: an extrapolation of ideas
Unified Modeling Language (UML)
– Too cryptic, hard to understand relationships
Conclusion
• Similar structures exist in humans to
interact, navigate and problem solve
• Feedback loops are common structures that
reinforce positive behavior
• Visualization aids problem solving