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Representation and Retrieval

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Representation and Retrieval. Reviewing the framework. Information ... Jennifer Lopez. Steve Whitaker. Hillary Clinton. Sam Mudd. Condolesa Rice. Jim Sherman ... – PowerPoint PPT presentation

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Title: Representation and Retrieval


1
Representation and Retrieval
  • Reviewing the framework
  • Information processing sequence
  • Encoding entering information into cognitive
    system
  • Attention
  • Interpretation
  • Elaboration going beyond the information
  • Evaluation and judgment
  • Inference
  • Attribution
  • Representation storing new knowledge
  • Retrieval using stored knowledge
  • Response

2
Representation and Retrieval
  • So far focus on how information is processed
  • Some (but not all) stimulus info encoded
    selective attention
  • Interpreted
  • Elaborated in various ways evaluation,
    inference, attribution

3
Representation and Retrieval
  • Information then stored in memory. But
  • Stimulus info has been transformed. Therefore --
  • Mental representation of it may differ from
    actual input. But
  • That representation is basis for later retrieval
    and response
  • So -- Use of information is based on retrieval

4
Representation and Retrieval
5
Representation and Retrieval
  • Model does a good job of specifying
  • How information is represented in memory (and
    why)
  • How information is retrieved from memory

6
Representation and Retrieval
  • Representation, retrieval, and judgment the use
    of heuristics
  • Information represented in memory -- used for
    many purposes, e.g., judgments decisions.
  • Do you think Ryan is a smart guy?
  • Candidate Smith is he a conservative?
  • How many times have we been told the economy is
    sound?
  • How are these judgments made?

7
Representation and Retrieval
  • Do you think Ryan is a smart guy?
  • Judgment formed on-line (stored in memory) or
    memory-based (on retrieval of relevant info from
    memory)
  • Candidate Smith is he a conservative?
  • Image (prototype) of what a conservative is.
    How well does Mr. Smith match prototype?
    Pro-choice, but anti-gun control, pro-business,
    but anti-tax cuts, etc.
  • How many times the economy is sound?
  • To provide accurate answer, recall all instances
    from memory
  • Problem to be accurate, judgment process can
    take a lot of work (time, energy).
  • Solution short cuts heuristics. Tversky
    Kahneman (1974 Rdng. 10).

8
Representation and Retrieval
  • Heuristic
  • a rule of thumb applied to available
    information
  • allows making judgments with little processing
    effort
  • yields judgments that are in most cases
    reasonably accurate.
  • However --
  • rule of thumb is not thorough, logical
    analysis therefore --
  • can produce systematic errors and biases.

9
Representation and Retrieval
  • Why base judgments on error-prone process?
  • All information needed to make logical judgment
    may not be available
  • Person has limited capacities and resources
  • Decisions need to be made quickly
  • Though subject to error, heuristics usually
    produce judgments that are sufficiently accurate

10
Representation and Retrieval
  • Judgment heuristics
  • Representativeness
  • Assigning single elements (e.g., persons) to
    larger categories (e.g., groups), estimating
    probability
  • Availability
  • Making frequency and probability judgments

11
Representation and Retrieval
  • Representativeness heuristic categorization
    based on resemblance of exemplar to category
    (prototype).
  • If A is highly representative of B, the
    probability that A originates from B is judged to
    be high.
  • Bob is quiet and shy, reads a lot, and is
    concerned with detail and orderliness. Is Bob a
    farmer or a librarian?
  • Is Candidate Smith a conservative?
  • The heuristic makes sense category members
    usually do resemble prototype of category. Hence
    useful and often accurate.

12
Representation and Retrieval
  • Problems sources of error (see Tversky
    Kahneman reading)
  • Insensitivity to base rates. Example -- exemplar
    resembles one category, but other category more
    likely. Base rates vs. representativeness.
  • Conjunction fallacy.
  • Linda is 31 years old, single, outspoken, and
    very bright. She majored in philosophy. As a
    student she was deeply concerned with issues of
    discrimination and social justice, and also
    participated in anti-nuclear demonstrations.
  • What is probability that today
  • Linda is a bank teller.
  • Linda is a bank teller and a feminist.

13
Representation and Retrieval
  • Insensitivity to chance.
  • the hot hand in basketball
  • Ignoring regression to the mean.
  • the Sports Illustrated jinx.
  • Some names..

14
  • Jennifer Lopez
  • Steve Whitaker
  • Hillary Clinton
  • Sam Mudd
  • Condolesa Rice
  • Jim Sherman
  • John Levine
  • Serena Williams
  • Bruce Stuckel
  • Eleanor Roosevelt
  • Oprah Winfrey
  • Bob Hall
  • Garry Demarest
  • Laura Bush
  • Jeff McMillan

15
Representation and Retrieval
  • Availability heuristic judging frequency of
    occurrence based on ease of retrieving instances.
  • Which occurs more frequently
  • Robins or owls?
  • Fords or Mercedes?
  • Baseball players or soccer players?
  • The heuristic makes sense. Instances in large
    classes are usually recalled more easily than
    instances in small classes.
  • But -- Availability is the inverse if instances
    can be recalled easily, there must be a lot of
    them.

16
Representation and Retrieval
  • Of the names you saw, were there more females or
    more males?
  • Females?
  • Males?
  • Problems sources of error ease of retrieval
    can be due to factors other than actual
    frequency. Anything that makes instances more
    accessible in memory will influence judgments.

17
Representation and Retrieval
  • What factors influence ease of retrieval?
  • Familiarity
  • Famous and not-so-famous names. Females on list
    all famous. Males not famous.
  • Recency
  • Salience, vividness
  • Egocentric bias

18
Representation and Retrieval
  • Egocentric bias in retrieval of instances (Ross
    Sicoly, 1979 Rdng. 12).
  • Married couples, each person indicates extent of
    their responsibility for each of 20 activities
    making breakfast, cleaning dishes, grocery
    shopping, cleaning house, planning joint
    activities, etc.
  • Results add two values from partners, greater
    than total possible.
  • Why? Self-relevant inputs are more available for
    retrieval from memory.

19
Representation and Retrieval
  • Separating amount of recall from ease of
    retrieval.
  • The problem availability heuristic relies on
    ease of retrieving instances. But in many
    cases there is more recall (famous names). Is
    overestimation due to recalling more or recalling
    a few more easily?

20
Representation and Retrieval
  • Strategy for solving (Schwarz et al., 1991 Rdng.
    11).
  • Describe 6 (12) situations in which you behaved
    assertively (unassertively).
  • Rate how assertive you are.
  • no. recalled assertive unassertive
  • 6 6.3 5.2
  • 12 5.2 6.2

21
Representation and Retrieval
  • Retrieval -- Different routes to retrieval
  • Information in memory -- retrieved for judgments,
    decisions, etc. How will information be
    retrieved? Have already seen a few ways.
  • Free recall retrieving items of acquired
    information
  • Frequency estimates
  • Trait ratings

22
Representation and Retrieval
  • Two well-known effects in the literature
  • Better recall of expectancy-inconsistent items
    (e.g., Srull, 1981 Rdng. 23).
  • Proportion Recalled
  • Congruent .400
  • Incongruent .470
  • Irrelevant .278
  • Overestimation of frequency of expectancy-consiste
    nt items (e.g., Hamilton Rose, 1980).
  • Traits Stereotypic of
  • Occupation Accts Doctors Salesmen
  • Accountants 2.67 1.99
    2.25
  • Doctors 2.21 2.66 2.41
  • Salesmen 1.94 2.12 2.94

23
Representation and Retrieval
  • How can we explain both of these effects??
  • The effects occur under different conditions
  • Different retrieval processes for different tasks
  • Return to the associative network model.

24
Representation and Retrieval
25
Representation and Retrieval
  • The TRAP Model (Twofold Retrieval from
    Associative Pathways) (Garcia-Marques Hamilton,
    1996).
  • Assumes same encoding and representation as
    network model.
  • One more assumption pathways connecting person
    node to --
  • consistent items -- strong (easily accessible)
  • inconsistent items -- weak (less accessible)

26
Representation and Retrieval
  • Major proposal of TRAP Model Two strategies for
    retrieval
  • Exhaustive retrieval. Example recall.
  • Heuristic retrieval. Example frequency
    estimates.
  • What are differences between two retrieval
    strategies?

27
Representation and Retrieval
  • Exhaustive Retrieval Heuristic Retrieval
  • Example free recall Example frequency
    estimates
  • Thorough search Selective search,
    focused on specific type of
    information
  • Retrieve anything and Uses availability
    to gauge everything, in any order
    frequency or amount of
  • information
  • Resource-consuming Less systematic, less
    demanding
  • Output retrieval of specific Output summary
    estimate
  • items

28
Representation and Retrieval
  • Implication of TRAP Model
  • Recall and frequency estimation rely on different
    retrieval strategies
  • So could use both strategies to retrieve info
    from same representation
  • If so in same study, could we show
  • (a) better recall of incongruent items
  • and
  • (b) overestimation of congruent items?

29
Representation and Retrieval
  • Empirical test (Garcia-Marques Hamilton, 1996)
  • Task form impressions of two persons.
  • Method
  • different occupations, opposite stereotypes
    (expectancies) cab driver (unambitious, fun),
    computer programmer (ambitious, boring)
  • read 36 behaviors, 18 about each person (6
    congruent, 6 incongruent, 6 neutral per person)
  • Recall behaviors
  • Estimate of behaviors for each trait

30
Representation and Retrieval
  • Results
  • Recall no. items recalled
  • congruent 3.67
  • incongruent 4.72
  • irrelevant 3.33
  • Frequency estimates
  • mean estimate
  • congruent 16.61
  • incongruent 13.49

31
Representation and Retrieval
  • Conclusion two retrieval strategies exhaustive
    heuristic -- can produce
  • divergent outcomes
  • based on same information
  • on immediately successive tasks

32
Representation and Retrieval
  • Next study (Garcia-Marques, Hamilton, Maddox,
    2002)
  • Same basic methodology, with some manipulations
    -- intervene to alter exhaustive retrieval
  • Cognitive load at encoding
  • Cognitive load at retrieval
  • Free recall vs. focused recall
  • Dependent measure recall

33
Representation and Retrieval
  • Mean Recall
  • No Load Load Encoding Load
    Retrieval
  • Cong Inc Cong
    Inc Cong Inc
  • Free Recall 4.00 5.05
  • Focused Recall

34
Representation and Retrieval
  • Mean Recall
  • No Load Load Encoding Load
    Retrieval
  • Cong Inc Con Inc
    Cong Inc
  • Free Recall 4.00 5.05 4.55 4.10
    4.70 4.10
  • Focused Recall

35
Representation and Retrieval
  • Mean Recall
  • No Load Load Encoding Load
    Retrieval
  • Cong Inc Con
    Inc Cong Inc
  • Free Recall 4.00 5.05 4.55
    4.10 4.70 4.10
  • Focused Recall 4.68 4.32 4.53 3.76
    5.17 3.83

36
Representation and Retrieval
  • Summary of findings
  • Cognitive load during either encoding or
    retrieval changes outcome (for different reasons)
  • Focused recall changes outcome
  • Note -- focused recall makes free recall
    (exhaustive) resemble the heuristic retrieval
    process

37
Representation and Retrieval
  • Remembering that vacation
  • Collaborative recall retrieval as a social
    process (Garrido, 2007)
  • Procedure
  • 3 persons per session
  • Task form impression
  • Expectancy John, computer programmer,
    intelligent, wise, quick thinker
  • 30 behaviors
  • Recall
  • Collaborative groups
  • Nominal groups

38
  • Results --

39
Representation and Retrieval
  • Collaborative retrieval lower recall why?
  • Relationship between encoding retrieval
  • Items represented in memory
  • Representation implies retrieval routes
  • Normal recall -- retrieval follows those routes
  • Collaborative recall
  • Each person has idiosyncratic representation,
    retrieval routes
  • Other person may recall item not implied by
    retrieval plan disruptive inhibits recall
  • Consequence lower recall in collaborative

40
Representation and Retrieval
41
Representation and Retrieval
  • But not the whole story
  • Transactive memory (Wegner, Erber, Raymond,
    1991)
  • Shared memory schemes within couple,
  • Each member has special knowledge
  • Both members know who knows what
  • I dont need to remember stuff you know
  • Together, better memory
  • Should occur only in established couples

42
Representation and Retrieval
  • Method
  • Natural impromptu couples
  • Task memorize items from 7 categories
  • Assignment of expertise or not (3 categories to
    one partner, 4 to other)
  • Dyadic memory task

43
Representation and Retrieval
  • Results

44
Representation and Retrieval
  • Results
  • No assignment natural impromptu
  • Assigned expertise impromptu natural
  • Why??
  • No assignment pre-existing structures in
    natural couples provides advantage
  • Assigned expertise
  • interference of assigned structure with
    pre-existing structure
  • in natural, but not impromptu, couples
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