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Chp.3: Understanding Users
Spring 2003
• Considering (modeling) how “humans work”
– want to see what humans are good and bad at and use this
knowledge to inform interaction design to both extend human
capabilities and compensate their weaknesses
– often done by modeling human processes and offering guidelines
for design
• Apply knowledge from physical world/activities to
digital domain
• Use conceptual frameworks for cognition
– mental models
– information processing
– external cognition
• Informing design: principles and guidelines
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Chp.3.1: Cognition
Spring 2003
• What is it? Cognition is what goes on in our heads:
thinking, reasoning, etc.:
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thinking
remembering
learning
daydreaming
decision making
seeing
reading
writing
talking
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Chp.3.2: Cognition
Spring 2003
• Two general modes:
– experiential cogntion: when we perceive, act, and react to
events around us effectively and effortlessly (ideally how
we’d like to use interactive devices!!)
– reflective cognition: involves thinking, comparing, decisionmaking (e.g., like when we learn to do something new)
• Specific processes:
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attention
perception and recognition
memory
learning
reading, speaking, listening
problem solving, planning, reasoning, decision making
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Chp.3.2: Cognition: Attention
Spring 2003
• Attention:
– allows us to focus on information relevant to what we’re
doing
– involves auditory and visual senses (i.e., visual attention,
auditory attention)
– can be thought of as a filter, e.g., when listening to
cacophonic noise you can attend to one audio stream
• Attentional process is aided by:
– maintaining goals (e.g., searching for something specific)
– accessing clearly presented information (particularly
relevant for visual design of interfaces)
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Chp.3.2: Cognition: Perception
Spring 2003
• Perception: how information is acquired from environment, I.e.,
senses:
– sight, sound, touch, smell, taste (hmm…smell-o-vision?)
• W.r.t. interaction design, want to present information that is
readily perceived
– e.g., well structured, organized, highlighted, etc.
– icons and other signage should be easily understood (e.g.,
consider US and universal road signs), see for example:
– <http://members.aol.com/rcmoeur/signman.html>
• General design principle:
– represent information in a way which facilitates perception and
recognition of its underlying meaning
– good example: google
– bad example: poor icons (see p.78)
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Chp.3.2: Cognition: Memory
Spring 2003
• Memory: involves recalling knowledge that enables us to act
appropriately
• Impossible to remember everything we see, hear, taste, smell,
or touch: information gets filtered (e.g., via attention)
– note: smell is strongly linked to memory, think how: (a) certain
smells are easily recalled, e.g., pine forest, “new car smell”, skunk,
(b) how certain smells trigger memory, e.g., certain foods may
remind you of certain places, events,…
• George Miller’s magical number 7 + or - 2
– interesting guideline, e.g., “chunk” information if possible,
– but don’t take this too literally (see box on p.82)
• Compare and contrast recall and recognition
– recognition is often easier/faster
– interesting example: when trying to remember URLs (p.83) automatic sentence completion seems like a pretty helpful tool…
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Chp.3.2: Cognition: Learning
Spring 2003
• Learning: in our context, consider
– learning how to use computer-based application
– using computer-based app to learn some concept
• People prefer to “learn by doing”
– hence direct manipulation interfaces and tutorials are good
tools
• Learning also to an extent relies on user’s underlying
mental model of given device / user app (see below)
• Guidelines:
– encourage exploration
– dynamically link representations and abstractions that need
to be learned
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Chp.3.2: Cognition: reading, speaking, listening
Spring 2003
• Reading, speaking, listening are three forms of language
processing
• Meaning of written or spoken text can be similar, but
perception may be different, e.g.,
– no intonation in written text
– written text can be re-read, annotated, etc.
• Many applications developed capitalizing on people’s reading,
writing and listening skills:
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interactive books (ebooks?)
speech-recognition systems
speech-synthesis systems
natural language recognition systems (Ask Jeeves)
various I/O devices facilitating Universal Access (fertile research
area)
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Chp.3.2: cognition: problem-solving, reasoning,
decision-making
Spring 2003
• Problem-solving, reasoning, decision-making are all
examples of reflective cognition (as opposed to…?)
• Reflective cognition is the slower, more difficult form
of the two, idea of interaction design is to aid this
process, e.g., via externalizing cognition:
– to reduce memory load (paper TO DO lists or electronic TO
DO lists on PDAs, e.g., shopping lists)
– to offload computation (e.g., calculators so you don’t have to
compute everything in your head)
– to allow modification of representations to reflect their
changing status, e.g.,
• annotating: crossing off TO DO items
• cognitive tracing: restructuring info such as desk files into piles
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Chp.3.3: Applying physical world knowledge
Spring 2003
• Helpful strategy for interaction design is to:
– understand various cognitive processes users engage when
coping with demands of everyday life
– emulate this interaction in the digtial world
• Examples:
– post-it notes
– electronic TO DO lists (and other things like calendars)
– “pile” metaphor (piles of files): let users organize electronic
files in a manner similar to how they would organize papers
on their real desks (in piles of stuff)
– similar to piles: the visual representation of “paper” in email
mailbox - signifies new or old mail waiting to be processed
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Chp.3.4: Conceptual frameworks
Spring 2003
• Applying theories and conceptual frameworks to
interaction design:
– mental models
– information processing
– external cognition (mentioned previously):
• reducing memory load
• offloading computation
• allow modification of representations
• Mental models: users’ developed knowledge of:
– how to use a system
– how a system works
• Examples: “deep” and “shallow” mental models
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Chp.3.4.1: Mental models
Spring 2003
• Mental models: do you have “deep” or “shallow”
models of these systems:
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fridge (recall visibility and affordance picture)
car and car engine
scanner (e.g., when used as a photocopier)
elevator (why do people press button twice??)
television
programming:
• C/C++ memory management
• system-level processes, e.g., numerical representations, roundoff errors, floating point equality (would you use the following:
if((float) x == 0.0) ? why or why not?)
– other computer applications (e.g., Shake vs. Final Cut Pro)
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Chp.3.4.1: Mental models
Spring 2003
• Design guidelines:
– make system internals “visible” or “transparent” to user (not
literally, but rather give user idea of how things work)
– but don’t make system too visible at the outset (e.g.,
Google’s advanced search)
– can use “training wheels”
– provide useful feedback (so user knows what’s happening)
– provide clear and easy-to-follow instructions
– on-line help, tutorials
– context-sensitive guidance for users
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Chp.3.4.2: Information processing
Spring 2003
• Information processing: another approach to conceptualizing
how the mind works:
– the mind as a reservoir (sponge??)
– telephone network (e.g., switches and interconnections)
– digital computer (e.g., with CPU, memory, etc.)
• Why bother?
– to better understand how mind works
– to be able to make predictions about human performance (e.g.,
GOMS model)
• Problem with this approach:
– often restricted to modeling mental activities happening exclusively
inside the head
– does not take into account environment (e.g., interaction with
others, or with other tools, e.g., books, documents, devices)
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Chp.3.5: Informing design: from theory to
practice
Spring 2003
• Theories, models, conceptual frameworks provide
abstractions for thinking about phenomena
• In this chapter, we looked at abstractions of humans
and human (cognitive) processes
• Example: GOMS (Goals, Operators, Methods,
Selection rules):
– describes how user performs computer-based tasks
– model has been transformed into keystroke level method that
allows quantitative predictions on the amount of time needed for
certain methods (e.g., so many keystrokes to complete task)
• Research from cognitive psychology can be applied
to interaction design (but use care to avoid
oversimplification and misapplication)
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