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6
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Mouse Trackball Joystick Touchpad
Troughput Error rate
Trou
ghpu
t (bp
s)
Erro
r rat
e (%
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Image by MIT OpenCourseWare.
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© Mozilla. All rights reserved. © source unknown.
All rights reserved.
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© Microsoft. All rights reserved.
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© Microsoft. All rights reserved.
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© Microsoft. All rights reserved.
© The Eclipse Foundation. All rights reserved.
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© Interface Hall of Shame. All rights reserved.
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© Microsoft. All rights reserved.
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11
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30
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15
108
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2
2 3 4 5 6 8 10 15 20 30 40 50
Predicted execution time (sec)
Obse
rved
exe
cutio
n tim
e (s
ec)
Graphic EditorsMARK UP
DRAW SIL
Executive SubsystemsAll Subsystems
Text EditorsPOET SOS
DISPED
Image by MIT OpenCourseWare.
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High-level models of human-computer behavior
• Developing Theories in HCI– must explain and predict human behaviour in the human-computer system
– must work in a wide variety of task situations
– must work within broad spectrum of system designs and implementations
• Some low-level theories can be used to predict human performance– Fitts’ law: time to select an item with a pointing device
– Keystroke level model: sums up times for keystroking, pointing, homing, drawing, thinking and waiting
• General models that explain human behaviour with machines– Syntactic/semantic model (Shneiderman)
– Stages of interaction (Norman)
– all of psychology!
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Syntactic/semantic model of user knowledge
•A high level model of interaction, developed by Ben Shneiderman
Action ObjectAction Object
Task Computer
Semantic Syntactic
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1. Syntactic knowledge
•The rules or combinations of commands and signals
– seen as device-dependent details of how to use system
– examples:
• backspace key delete previous character
• tab move to next field in a form
• right mouse button context menu
• grep <word> <file> find word in a file
• control-shift-K search messages (thunderbird)
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Syntactic
1. Syntactic knowledge (continued)
User problems with syntactic knowledge
syntactic details differ between (and within!) systems
– little consistency –> arbitrary
hard to learn
easily forgotten
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Action Object
Computer
2. Semantic knowledge: Computer conceptsThe meaning behind computer concepts
People learn them by– meaningful learning – demonstrations– explanations of features– trial by error– models, analogies
relatively stable in memory– high level concepts– logical structure– cognitive model produced
usually transferable across computer systems– but not always
But: prefer to concentrate on task, not computer knowledge
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Action Object
Task
3. Semantic knowledge: task concepts
•The meaning behind the task concepts
– is independent of the computer– Similar mechanism to computer concepts
•Examples– how to write a business plan
• format concerns• stylistic concerns• paragraph structure, etc.
– creating a budget
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What Syntactic/Semantic Model reveals
•Mapping between the 3 items is key
– Task semantics to computer semantics to computer syntax• task semantics: write document• computer semantics: open a file, use editor, save it to disk• computer syntax: select menu items, key strokes for
formatting,...
– Bad mapping: using latex to write document• aside from task semantics, must also know semantics/syntax of:
– text editor– latex– Unix compiling and printing sequence (to typeset and print)
– Good mapping: trashcan to throw away files• must know mouse syntax of selecting and dragging• computer semantics almost analogous to task semantics
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Guideline from syntactic/semantic model•Reduce burden to task-oriented user of learning separate computer semantics and syntax
•computer semantics– Use metaphors– hide unnecessary information
•computer syntax– A little learning should go a long way...– As simple as possible and uniformly applicable– Generic commands– Syntax consistent between systems
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Four Stages of an Interaction
(a simplified version of Norman’s 7 stages)
1. Form intention
2. Select an action
3. Execute the action
4. Evaluate the outcome
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The four stages when performing a task
Physical activity
Execution
ActionSpecification
Intention
Goals
Evaluation
Interpretation
Perception
Mental activity
expectation
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Example task: improve document’s formattingintention-1
intention-2
intention-3
actionspecification
evaluate-1
evaluate-2
evaluate-3
interpretation
intention-4 evaluate-4
look better
block para
.pp->.sp
execution perception
getformatted
output
actionspecification
execution
interpretation
printer
perception
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Image by MIT OpenCourseWare.
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GoalsPhysicalSystem
gulf ofexecution
Gulf of Execution
•Do actions provided by system correspond to the intentions of the user?
•Gulf:– amount of effort exerted to transform intentions into selected and
executed actions•Good system:
– direct mappings between Intention and selections
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GoalsPhysicalSystem
gulf ofevaluation
Gulf of Evaluation
•Can feedback be interpreted in terms of intentions and expectations?
•Gulf:– amount of effort exerted to interpret feedback
•Good system:– feedback easily interpreted as task expectations
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Bridging the Gulfs
GoalsPhysicalSystem
execution bridgeintentions
action specificationsinterface
mechanism
evaluation bridge
interpretationsinterfacedisplay
evaluations