COM 3210, Week 6

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COM 3210, Week 6

• Making sense from prior experience

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Topics

• Types of reasoning that users engage in
• Learning theories
• Learning models
• Conclusions for interface design

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1. Reasoning

• Two types of reasoning
• Based on analogies
• Based on metaphors

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Analogy and Metaphor

• An analogy provides an explicit, isomorphic
  mapping between objects of two domains
• A metaphor is a looser connection that draws on
  similarities, but also includes dissimilarities.

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Examples

• Killing a tumor is like a generals army
  attacking a fortress surrounded by mines
• Your PCs operating systems works like a desktop
• whether something is an analogy or a metaphor
  also depends on the scope of the comparison

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Computing metaphors

• No chance for real analogies in computing
• computing metaphors use real world objects in a
  computing environment
• they provide an intuitive understanding of the
  computing object and initiate a process of active
  learning
• computer metaphors are indispensable as
  overarching design strategies, but choose
  carefully

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The desktop metaphor

• Pictures of trash can Macintosh

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The desktop metaphor

• The use of the trash can to eject a disk was
  present form the very beginning of the Macintosh
  interface. The original Mac had not hard
  disk. Because most users typically would
  switch back and forth between several diskettes
  during a session, it was deemed appropriate for
  the Mac to keep a memory image of the list of
  files of the various disks, regardless whether or
  not the diskette was actually inserted in the
  drive. Often, during the course of a session,
  the user would finish using a particular
  diskette, To reclaim vluable space, the now
  unwanted list of files represented by the
  grayed-out icon could be thrown away by dragging
  it into the trash Tom Erickson, Apple

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2. Learning Theories

• Major groups
• behaviorist theories
• constructivist theories

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Behaviorist theories

• Learning as changes of observable external
  behavior
• Stimulus - response, selective reinforcement
• habits
• Prominent Behaviorist Skinner
• Learning as a reactive process

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Constructivist theories

• Learning as constructing meaning in ones mind
• building of conceptual structures through
  reflection and abstraction
• not directly observable
• requires self regulation
• learning as an active process
• Piaget, Gestalt

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Constructivist approaches

• Perception
• Organization
• Decision making
• Problem solving
• Attention
• Memory

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3. Some practical learning models

• concept formation
• learning by exploration
• learning by explanation
• learning by imitation
• learning by chunking
• proceduralization

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Concept formation

• Common response to a class of stimuli
• discrimination of distinctive features of objects
• conjunctive Car - 4 wheels and engine
• disjunctive meazels - one or several of the
  following symptoms
• relational rectangle - four sided object with
  the two opposite sides of the same length

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Concept formation

• Users acquire new concepts and refine them
• e.g. Children learn about dogs and cats
• first concept animals have four legs (humans
  have two)
• refinement birds are animals and have only two
  legs.

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Concept formation

• What kind of concept does a computer user need to
  learn?
• How can designers support concept formation

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Learning by experimentation

• Learning as an active process
• exploration and experimentation Learning by
  doing
• experiential learning theory (Gibbs 1988)

Concrete experience
Reflective observation
Active experimentation
Abstract conceptualization
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Learning by experimentation

• How can designers facilitate this kind of
  learning?
• Restricted functionality at first
• training wheels
• feedback
• safety nets
• undo

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Explanation-based learning

• general ideas and supporting facts such that the
  learning can see the relationship between them
• e.g. lectures
• mental models
• What are sources of explanation for computer
  users?
• What makes a good explanation?

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Minimalist instruction

• people rather learn by experimentation than by
  explanation
• explanation i.e. instruction should support that
• instruction should be as little as possible, but
  as much as necessary

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Minimalist instruction

• Focus on real world activities of the task domain
• Choose an action oriented approach (how to do
  things)
• emphasize error recognition and recovery
• eliminate repetitions, summaries, reviews, and
  exercises

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Learning by imitation

• Piaget three types of human adaptation
• Play assimilating objects to predetermined
  activities regardless of the objects attributes,
  e.g. using chair as horse
• Simple Imitation change behavior to be something
  else, e.g. using mams lipstick, but also dance
  lessons

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Intelligent Adaptation

• Assimilating aspects of the environment to the
  cognitive structure and
• accommodating cognitive structures to the
  environment
• guided by structures and resulting in changed
  structures
• e.g. apprenticeship (crafts), pilot-training,
  nurse training, learning to drive a car

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Immitation and intelligent adaptation

• Learning to do things skills
• can start as imitation and may move on to
  intelligent adaptation
• How can this be exploited in interface design?
• How can a designer support this type of learning?

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Learning by chunking

• Forming general rules from specific instances
• declarative chunking e.g. grouping digits of a
  phone number.
• Procedural chunking grouping several actions
  into a new action, e.g. drag and drop

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Proceduralization

• From declarative to procedural knowledge
• from facts to how-to-do knowledge
• from knowing everything about typewriters to
  learning how to type
• from knowing everything about windows to learning
  how to use it
• Consistency is important, but can be harmful or
  annoying

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Exercise answer the following questions

• What is the tree that grows from an acorn?
• What is the black cover garment that one wraps
  around one self?
• What sound does a frog make?
• knock knock stories are a kind of
• Whats the term to say youve got no money?
• Whats the clear part of an egg?

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Habit intrusion

• Users tend to behave in habitual ways
• even if it is not appropriate
• How can designers incorporate habitual behaviour?

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4. Design principles for learnability (Dix)

• Predictability - help users predict future
  actions
• Synthesizability - help user asses effects of
  past action
• Familiarity - help users to apply past knowledge
• Generalizeability - help users to extend
  knowledge
• Consistency - similar behavior in similar
  situations

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Summary week 6

• Reasoning by analogy and by metaphor
• Models of learning
• concept formation
• experimentation
• explanation
• imitation and intelligent adaptation
• chunking
• proceduralization

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Further reading

• Preece, J. et al. (1994) Human Computer
  Interaction
• Eberts, R. (1994) User Interface Design
• Dix et al. (1998) Human Computer Interaction
• Carroll, J. (1990) The Nurnberg Funnel MIT Press
• Carroll, J. (1998) Minimalism Beyond the
  Nurnberg Funnel MIT Press
• Huthicns, E. (1995) Cognition in the Wild. MIT
  Press
• Gibbs, G. (1988) Learning by Doing