Chp.3: Understanding Users

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Chp.3 Understanding Users

• 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

• What is it? Cognition is what goes on in our
  heads thinking, reasoning, etc.
• thinking
• remembering
• learning
• daydreaming
• decision making
• seeing
• reading
• writing
• talking

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Chp.3.2 Cognition

• Two general modes
• experiential cogntion when we perceive, act, and
  react to events around us effectively and
  effortlessly (ideally how wed like to use
  interactive devices!!)
• reflective cognition involves thinking,
  comparing, decision-making (e.g., like when we
  learn to do something new)
• Specific processes
• attention
• perception and recognition
• memory
• learning
• reading, speaking, listening
• problem solving, planning, reasoning, decision
  making

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Chp.3.2 Cognition Attention

• Attention
• allows us to focus on information relevant to
  what were 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

• Perception how information is acquired from
  environment, I.e., senses
• sight, sound, touch, smell, taste
  (hmmsmell-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
• lthttp//members.aol.com/rcmoeur/signman.htmlgt
• 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

• 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 Millers magical number 7 or - 2
• interesting guideline, e.g., chunk information
  if possible,
• but dont 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

• 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 users
  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

• 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
  peoples reading, writing and listening skills
• 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

• 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
  dont 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

• 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

• 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

• Mental models do you have deep or shallow
  models of these systems
• 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, round-off 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

• Design guidelines
• make system internals visible or transparent
  to user (not literally, but rather give user idea
  of how things work)
• but dont make system too visible at the outset
  (e.g., Googles advanced search)
• can use training wheels
• provide useful feedback (so user knows whats
  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

• 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

• 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)