CS260: Lecture 2

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CS260 Lecture 2

• John Canny
• Fall 2006

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Human Learning

• Why study human learning in HCI?

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Why Study Human Learning?

• A People learn to use new systems periodically
• A As people gain familiarity with systems, they
  evolve their use of them.
• A Learning science is one of the most-studied
  areas in social science, with effective success
  metrics.
• A Learning is not an isolated mental process,
  its part of most everyday knowledge work
  practices (micro-genesis).
• A To better understand adult, child and
  unschooled users.
• A Because formal education strongly shapes the
  way people think.

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Lev Vygotsky

• Vygotsky was an extraordinary scholarwho studied
  Law, and taught Literature, History of Art and
  Psychology by age 22.
• Vygotsky pursued a social perspective and took it
  very far, developing theories of knowledge,
  development, and education that were profoundly
  influential.

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Vygotsky in Education

• Vygotsky is (with Piaget) the leading education
  theorist of the early 20th century.
• Vygotskys social theory of learning
• Like Piaget he argued that children learn by
  constructing their own understanding of the world
  they experience.
• In contrast to Piaget, he insisted that the
  world experienced by children is a social,
  rather than a natural one. i.e. games, toys, and
  books are social constructions that embody social
  norms and expectations for the child.

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Vygotsky Genetic method

• Another of Vygotskys ideas is his genetic
  domains
• Onto-genesis Development by an individual
• Socio-historical Development of the society
• Phylo-genesis Development of the (human)
  species
• Micro-genesis Creation of ideas concept
  learning
• His social theory involves the interplay between
  1. and 2.
• Thus Vygotskys approach interleaves methods that
  would be regarded as both scientific and
  humanistic.

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Vygotskys Genetic Principle

• Vygotskys genetic principle has extraordinary
  implications.
• Among other things, it implies a socio-historical
  approach to understanding human behavior.
• This approach is still popular among researchers
  in Management and Cooperative Work.
• And much more

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Power laws

• One of the puzzling findings in human behavior is
  the presence of ubiquitous power law processes.
  A power law probability distribution has the
  form
• p(x)
  1/rank(x)a
• Where a is typically between 0 and 3 and is often
  very close to 1.
• Power laws are not natural from a statistical
  point of view. Something very special must be
  happening to cause them.

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Power laws

• Processes that exhibit power-law statistics
• The probabilities of words in the English
  language
• Word probabilities in any reasonably large corpus
• Number of links into a web site, click-thru of
  web sites
• Citations in academic journals
• Paths that users take walking through a house
• Products purchased from a vendor
• Size of cities, sizes of companies
• Stock market returns, trades, volumes
• Incomes of people many others
• One of the strongest nontrivial facts in
  social sciences

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Genetic processes and Power laws

• Power laws arise (and were first studied) in
  genetics. If there are k types we assume each
  type gives birth, mutates or dies with some
  probability.
• With a variety of choices of parameters, this
  process gives rise to power law distributions.
• For many choices of parameters,the power is 1.

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Genetic processes and Power laws

• While genetic processes may explain many power
  law phenomena, they can do more than that.
• Just as in classical genetics, a genetic process
  implies a phylogenic tree exists for the
  objects in a domain.
• We can guess the ancestry of an item from its
  current popularity, the popularity of its
  parent, and the separation time.
• This can help us understand the adoption and
  learning of activities.

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Learning and existing knowledge

• Learning is a process of (genetically) building
  new knowledge using existing knowledge.
• Knowledge is not acquired butconstructed out of
  existingmaterials.
• The process of applying existingknowledge in new
  settings is called Transfer.

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ZPD

• Learning is layered and incremental.
• In real societies, learners are helped by others.
• In fact learners have a zone of concepts they
  can acquire with help.
• This is the Zone of Proximal Development (ZPD).

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Back to learning..

• Example Who knows what this is?

100k
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Back to learning..

• Example

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Learning new applications

• Applications are designed to fit in ordinary
  users ZPD.
• In most cases, you cant assume that there is
  human available to help a user learn the new
  system.
• A tutorial help system can provide much of this
  support.

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Learning new applications

• People learn best by doing (constructing new
  knowledge).
• Using a system exposes a users conceptual models
  of how it works, and allows them to diagnose
  mistakes.
• A tutorial help system should be able to
  recognize and respond to common user
  misunderstandings.

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Learning and experience

• Learning is most effective when it connects with
  the learners real-world experiences.
• The knowledge that the learner already has form
  those experiences serves as a foundation for knew
  knowledge.

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Learning and transfer

• Transfer is certainly enhanced by similarity
  between the old and new contexts.
• What other factors should affect transfer?

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Transfer and understanding

• Transfer depends on thorough learning in the
  first situation (learning with understanding).
• The more thorough the understanding in the first
  situation, the more easily knowledge will
  transfer.

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Understanding

• By understanding we mean that a person has a
  mental model of why a thing behaves as it does.
• This model allows the person to predict how the
  thing behaves in other situations, and to
  explain their reasons for that conclusion.

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Transfer and Generality

• Generality of existing knowledge has the learner
  already seen it applied in several contexts?

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Transfer and Motivation

• Motivation is the new knowledge useful or
  valuable?
• Motivation encourages the user to visualize use
  of the new knowledge, and to try it out in new
  situations.
• Students are usually motivated when the
  knowledge can be applied to everyday situations.

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Transfer and Abstraction

• Is the existing knowledge abstract or specific?
• Abstract knowledge is packaged for portability.
  Its built with virtual objects and rules that can
  model many real situations.
• E.g. clipart

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Summary

• Factors affecting transfer
• Real-world experience
• Degree of Understanding (the earlier concept)
• Generality of the earlier knowledge
• Motivation
• Abstraction

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Metacognition

• Metacognition is the learners conscious
  awareness of their learning process.

Metacognitionhelps transfer
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Metacognition

• Strong learners carefully manage their learning.
• For instance, strong learners reading a textbook
  will pause regularly, check understanding, and go
  back to difficult passages.
• Weak learners tend toplough through theentire
  text, then realize they dontunderstand and
  startagain.

Have I learnedthis yet?
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Metacognition

• Another very good strategy is to predict the next
  main point in an argument before you read it
• What would a user interview be like?
• What techniques will improve learning?
• Then when you see thereal answer, the
  newknowledge will tie withreal experience
  theexperience you just had.

Let me guess whats comingnext..
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Structuring Learning

• A similar strategy is very effective for
  teaching.
• Ask students to work on a problem first, trying
  out their own approaches.
• Then provide an explanation (a set of principles
  to explain the problems behavior).

Reading, lecture
Problem, lecture
Problem work only
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Structuring Learning

• Again this gives students some rich and immediate
  experience with the problem.
• When the explanation is given, students can
  relate the new information with the experience
  they just had.

Reading, lecture
Problem, lecture
Problem work only
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• Break

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Piaget Stages of learning

• Piaget observed very systematic progression of
  knowledge in young children through stages
• Sensori-motor (acting, observing, remembering)
• Semiotic or symbolic (naming things)
• Concrete operations (relationships,
  transformations)
• Propositional or formal thought

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Sensori-motor stage (lt 2 years)

• Conditioned behaviors, and first hand-eye
  coordination.
• Grasping, manipulating things.
• Some indirect manipulation.
• Object persistence.

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Semiotic stage (gt1.5 years)

• Children continue to play with missing objects,
  and may use gesture to invoke them.
• This soon turns to imaginary play.
• Drawing.
• Speech naming first the things that are
  present.
• Then referring to things thatare not present,
  and to the past and future.

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Concrete thought (2-7,7-11 years)

• Concrete thought a system of (real) objects,
  relationships, and operations on them.
• Children understand things by being able to
  relate them to similar things, and to predict the
  consequences of their actions.
• They can plan and act to achieve a desired
  outcome.

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Concrete thought

• But early concrete thought is still tied to
  direct experience it is not de-centered.
• E.g. children in this stage can navigate through
  their neighborhood, changing their route if
  needed.
• i.e. they can mentally model and predict the
  results of their actions.
• But they cannot indicate that route abstractly,
  say on a map.

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Concrete thought

• Concrete thought includes rich spatial and
  temporal relationships.
• Visual design is a concrete process.

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Formal thought (11 years)

• Objects and operations no longer need to relate
  to the world. Things dont need to be true or
  consistent. Thinking is a game.
• Operations are more abstract, and often
  complementary e.g. joining-separating.
• Children learn a number of principles, like
  reversibility, proportion, chance.

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Formal thought caveats

• Researchers have found that the transition to
  formal thought is not as reliable as Piaget had
  thought.
• Many features of this stage are missing in
  children who do not attend school.
• This stage corresponds with the transition from
  learning from experience (pre-school), to
  learning from texts (school).

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Aside Design for Developing Regions

• Users in developing regions often have limited
  formal schooling. This leads to systematic
  challenges
• Users are not comfortable with formal objects
  such as a red square, i.e. they do not treat
  objects as sets of attributes, but as concrete
  things.
• Graphic (picture representations) are OK, but
  should not be too abstract.
• Users favor representations of people doing
  actions.
• Users expect consistency and realism.

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Formal thought (7 years)

• Side-effects of abstract representations
• Context disappears things are just true or
  false everywhere.
• Rules are very powerful, and both the rules and
  the reasoning must be accurate, or false
  conclusions will be drawn.
• Detail must be discarded or the rules may
  conflict.

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Thought styles

• Designers and other visually-oriented people
  usually favor concrete thought
  context-dependent, rich representations.
• Technologists and mathematically-oriented people
  favor formal thought context independent,
  sparse representations, rich consequences.

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A mismatch

• Many interface researchers (technologists) tried
  to build UI design tools using abstract interface
  specs (UIMSes)
• the designer specifies rules about the interface
  and the system finds a solution satisfying
  them.
• Real designers hated this idea. They lost control
  over spatial relationships and overall layout
  which was lost in the rules.

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Macro and micro-Piaget

• Piagetian stages are often evident in learners
  acquisition of particular concepts.
• i.e. the learners first experience is
  sensori-motor if I do X, then Y happens.
• They develop a language for naming the
  operations, objects, groups of objects etc.
• They acquire concrete understanding of the
  systems operation I can change state X to Y
  using operation Z.
• Finally, they may develop a formal understanding
  of how the system works (as explicit rules).

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Piagets progression

• The Piagetian progression can be a good model for
  the progression in learning new concepts, like
  how to use a computer program.
• Look for a Sensori-motor ? Symbolic ? Concrete ?
  Abstract progression in your own learning, and in
  your users.

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Inquiry cycles

• Inquiry-based learning makes students
  meta-cognitive strategy explicit.
• It also treats learning as a kind of scientific
  research.

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Inquiry cycles

• Question a new problem for the learner
• Hypothesis Learner proposes a solution or a way
  to understand the problem better
• Investigate Learner figures a way to try out the
  hypothesis (often an experiment)

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Inquiry cycles

• Analyze understand the results of the
  investigation.
• Model Construct a model or principle for whats
  going on.
• Evaluate Evaluate the model, the hypothesis,
  everything that came before.

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Inquiry cycles

• See http//thinkertools.soe.berkeley.edu
• Thinkertools uses software agents to personify
  the different stages in inquiry cycles.
• The agents help scaffold the child through the
  cycle.

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Scaffolding

• Refers to the process of shaping the learners
  experience while learning, by creating a
  scaffold to guide their actions.
• Generally, the teacher begins by doing most or
  all of the task.
• The task is repeated, with the learner doing more
  and more of it.
• Eventually, the learner does the entire task
  themselves the scaffold is removed.

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Scaffolding and ZPD

• Scaffolding produces a steady progression through
  the learners ZPD (Zone of Proximal Development)

ZPD
Inaccessibletasks
Solo tasks
Scaffolded learning
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Scaffolds and Tools

• First-generation learning tools were electronic
  flashcards
• System flashes a new item on the screen
• User has to enter the right input (typing,
  multiple choice etc.)
• System learns users weaknesses, and focuses its
  examples on those weak cases.
• Quite effective for low-level learning (e.g.
  Morse code).

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2nd Generation Scaffolds

• Allow exploration of a knowledge domain
• Caclulators, spreadsheets, graphing programs,
  probes etc.
• Modeling/Simulation (e.g. Interactive Physics)
• Matlab packages

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MicroWorlds

• An idea promoted by Seymour Papert (creator of
  Logo).
• A Microworld is a simplified model of the
  physical world, which emphasizes certain physical
  principles and omits other detail.
• E.g. 2D geometry (turtle geometry).

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MicroWorlds

• Microworlds encourage less structured exploration
  by learners.
• The idea is that the learners discoveries will
  be driven more by their own goals, leading to
  better learning.
• The structure of the Microworld should ensure
  that they make the right inferences.

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Feedback, Reflection, Revision

• One of the most important principles in
  learner-centered design is Early Feedback
• The learner should be given feedback as soon as
  possible as they form new concepts.
• This can take the form of a multiple-choice
  question so the answers can be given
  immediately.

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Feedback, Reflection, Revision

• Reflection tools encourage meta-cognition.
• Thinkertools which we mentioned earlier
  encourages learners to follow an inquiry cycle.

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Feedback, Reflection, Revision

• Small-group discussion is another way to
  encourage reflection.
• Discussion makes each learner reflect on their
  understanding to explain to others, and to
  interpret others explanations.
• Systems that do this CSILE (Vanderbilt)

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Feedback, Reflection, Revision

• Peer instruction (Mazur) is a pattern that
  encourages all these steps
• Students are given a multi-choice question
• They write down an individual answer
• The class votes their answer
• Students discuss in small groups, then answer
  again.
• Another vote is taken
• The instructor explains the right answer.