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Cog Psy > Cog Psy Exam #3 (3/15/24) > Flashcards

Cog Psy Exam #3 (3/15/24) Flashcards

1
Q

knowledge representation: definitions

A

process - what the mind does (attention, encoding, retrieval)
product - consequences of processes (recall, comprehension, primed responses)

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2
Q

knowledge representation

A
  • what processes operate on
  • what products are derived from
  • ‘stand in for’ something else
  • capture important aspects of information not everything about them
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3
Q

knowledge representation: external vs internal representation

A

external
- subway map
- street signs

internal
- brain states: neural activity
- theoretical structures (mental images, conceptual nodes, schemas)

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4
Q

imagistic: mental imagery

A
  • direct, analogous to the thing you have a mental representation of
  • preserves visuospatial relations, maintains the same physical features
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5
Q

imagistic: mental rotation studies (Shepard & Metzler)

A
  • ask people to think about something and imagine turning it upside down in your head
  • takes people longer to rotate it upside down than to turn it to the side = shorter rotation

results: the amount of time taken to decide whether the objects are the same is a function of the amount of rotation required

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6
Q

imagistic: image scanning (Kosslyn - elephant/cat)

A
  • imagine an elephant, in the same scene imagine a cat
  • verifying question: does the cat have ears?
  • takes people longer th answer things about a cat next to elephant bc of size diff

results: faster to verify details that are larger in the overall image

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7
Q

imagistic: image scanning (Kosslyn - Island)

A
  • after memorizing map of made up island, people were asked to imagine mentally traveling on the map
  • people took longer to mentally travel for longer distances on the map
  • people maintain features of the actual physical environment
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8
Q

imagistic: relational-organizational hypothesis (Bower)

A
  • imagery improves memory when it affords associations btw stimuli
  • look at words and memorize them
  • give recognition test
  • in recall: when asked for
    - rote memorization = 30%
    - separate images = 47%
    - interacting images = 57%

results: people remember more by using imagistic representations

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9
Q

dual coding: memorize word pair study

A

words
- carrot/truck
- table/justice
- wisdom/flower
- integrity/socialism

Results: easier to make mental images for certain words (carrot vs socialism) and therefore pairs that are easier are easier to remember

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10
Q

dual code theory

A
  • two ways to represent concepts
  • sometimes things are imagistic and sometimes they are verbal
  • if you encode things in 2 diff formates you facilitate memory and are more likely to remember more
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11
Q

verbal representation

A
  • symbolic representation
  • words
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12
Q

abstract (propositional) representation

A
  • things we can’t define
  • coding in a computer or neuros firing
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13
Q

abstract representation: propositional (Anderson & Bower)

A
  • symbolic things that can’t be translated but conveys relationships
  • info is stored as ‘propositions’
  • relationship btw ideas
  • propositional representations are retrieved and image or verbal code is recreated
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14
Q

image vs proposition

A
  • analog: preserves perceptual features
  • relationship must be encoded in the representation
    • lamp is ON the table
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15
Q

spatial knowledge: mental models (Johnson-Laird)

A
  • running simulations of what might happen at the end of the movie
  • can infer info through a mental model
  • making judgements

study: cup in relation to knife situation

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16
Q

spatial knowledge: cognitive maps

A

specialized representations of physical environments

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17
Q

spatial knowledge: route knowledge

A

navigating through environment, series of landmarks

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18
Q

spatial knowledge: survey knowledge

A
  • bird’s eye view
  • can be learned through maps but takes a while
  • acquire with expensive experience
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19
Q

spatial knowledge: physical vs mental maps (Tversky)

A
  • conceptual knowledge can distort perceptual representations
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20
Q

spatial knowledge: map memorization study (Throndyke)

A
  • memorized maps w 4 made up cities
  • asked people to estimate distance btw cities

Results: if there were no intervening cities btw the 2 points they estimated shorter distances

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21
Q

embodied accounts - carpenter nail study

A
  • based on the way we interact with things
  • ppl read a sentence and then shown a picture and asked if it was an object in the sentence

Results: ppl were faster to say yes to the pictures in the same orientation as they wld be irl
- horizontal nails vs vertical bc that’s how it wld be hammered into a wall

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22
Q

action compatibility effect (Kaschak & Glenberg)

A
  • move mouse to give a response, read sentence to see if it makes sense
    2 groups: forward or back to say yes
    sentence: you gave the friend the food

results: people are faster when moving forward with this sentence bc to give something you would hand it out

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23
Q

concepts and categories

A
  • how knowledge is stored in the mind: representation and organization
  • concept: knowledge one has about specific things in the word
  • types of categories
    • natural kinds
    • artifact
  • ad hoc: created ‘on the spot’ to suit a specific need
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24
Q

categorization accounts: function of rules

A
  • item belongs to a category if defining features are present
  • categories are at times related by family resemblance, not rules or def
  • some categories are malleable or fuzzy
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25
Q

spatial knowledge: prototype

A
  • the most typical and characteristic features
  • 1 good example
  • effects
    • statements about prototypes are verified rapidly
    • higher prototypciality means faster identification
    • ex. robin vs penguin bird
    • named first in free recall

cons
- typicality and context

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26
Q

categorization via exemplars

A
  • multiple examples
  • objects more similar to known exemplars will be categorized faster
  • instead of one best example, its several diff ones

pros
- no def, just instances
- objects more like exemplars, judged more quickly
cons
- how many exemplars do you have, which ones get used when
- storage demands

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27
Q

categorization via theories: hypotheses and reasoning

A
  • world knowledge shapes our understanding of concepts
  • relative importance of features
  • relations among features
    -purpose of category
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28
Q

categorization via theories: made up animal study (Rips)

A
  • made up animal with features: called Sorp
  • ask people what they would call the animal’s offspring
  • change the habitat and see if ppl would still call it the same thing

Results: people are slower to say that the offspring is the same bc the environment, using theory bc you are coming up with reasoning to explain why they are no longer called sorp

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29
Q

semantic network models: relations

A
  • property: specific property of a concept/node
  • Isa: ‘is an example of’, fits within larger concept/node
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30
Q

semantic network models: spreading activation

A
  • when you say something that relates to other nodes they get activated as well
  • weakens with length of link
  • more links = less activation per link
    • fan effect: not enough
      -energy to fully activate all the nodes
  • activation is not always good: noah vs moses story
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31
Q

semantic network models: spreading activation - story study (Mckoon and Ratcliff)

A
  • had people read a ‘story’ with interconnected relations
  • chain of events
  • ask if the story mentioned a series of words
  • see how long it takes to answer questions that relate to each other

Results: people take longer when the questions don’t relate to each other or it was not in the order given in the story

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32
Q

hierarchical network models: node theory (Collins and Quillian)

A
  • attached to each node is a set of features assoicated with it
  • at each level of the hierarchy, there are features of the thing that apply to all of the ones underneath
    • ex. fish - fins, swims, gills
      - shark - dangerous, gray
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33
Q

hierarchical network models: node theory - inheritance and cognitive economy

A

inheritance - each concept inherits property from higher concepts

cognitive economy - only have to represent property once in network and exceptions are added when necessary

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34
Q

hierarchical network models: node theory - levels

A

superordinate: animal

  • basic: bird, fish
    • first to be acquired by children
    • spontaneous naming
    • faster verification

subordinate: canary, shark, salmon

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35
Q

issues with hierarchical network models

A

can’t explain typical effects
- penguins and robins are at the same level in the hierarchy

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36
Q

defining language

A
  • a shared symbolic system for communication
  • a mental ‘code’ used for memory, thought, categorization etc
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37
Q

language as a defining characteristic for humans

A
  • productivity: we can produce whatever we want
  • arbitrariness: we decide what words mean
  • learnability: we can learn tons of language
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38
Q

linguistics

A
  • how languages are structured and how they change over time
  • language as an object: a thing that gets used, what are the rules, how do they change
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39
Q

psycholinguistics

A
  • how is language processed and represented in the mind
  • language as an activity
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40
Q

psycholinguistics: BF Skinner - behaviorisim

A
  • language is learned through shaping and experience
  • learned through observation
  • reinforce appropriate speech
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41
Q

psycholinguistics: Noam Chomsky - general thoughts

A
  • language is recursive/generative
  • infinite number of possible sentences
  • reinforcement is an insufficient mechanism for learning language
42
Q

psycholinguistics: Noam Chomsky - why not just reinforcement

A
  • children produce novel sentences all the time
  • they do not receive negative feedback
  • errors are often systematic due to overregulation
    • I walked = I walked vs I go = I goed
  • children learn general rules not specific words
43
Q

psycholinguistics: Noam Chomsky - proposal

A
  • children are born with an innate language capacity: language acquisition device
  • ‘mental organization’ facilitates language learning in the environment
44
Q

psycholinguistics: Noam Chomsky - aspects of learning language

A
  • performance: what people actually say
  • competence: what people actually know
45
Q

psycholinguistics: Noam Chomsky - comprehension and production

A
  • comprehension: taking sounds and transforming them into ideas
  • production: taking an idea and making it into sounds
  • evidence: aphasia where language is disrupted and people have production or comprehension dysfunctions
46
Q

phonology

A

the sounds of language and the rules for combining them
phoneme: smallest unit of speech - total: 46
morpheme: smallest sounds associated with meaning

47
Q

speech perception

A
  • special to humans
  • machines can’t do it
  • speech environment is noisy but we can compensate
  • figure-ground problem: figure is what you want to listen to and ground is the surrounding noise
48
Q

coarticulation

A

there is no one-to-one correspondence btw acoustic input and the speech sounds we perceive
- the same letter can sound very different in different words
- each phoneme is not articulated individually

49
Q

segmentation problem

A

speech is continuous and not segmented
language is a steady stream, no breaks

50
Q

phonemic restoration effect (Warren and Warren)

A

shadowing: listen to speech and ask people to repeat it but they ablate the sound
- I knew that the *eel was on the orange/axle
- people repeat back peel or wheel depending on the last word they are given
- most people don’t catch the odd sounds

Results: context interacts with prior knowledge to help us percieve speech

51
Q

McGurk effect

A
  • ask people to listen to sounds and then look at a person saying a sound and guess what they are saying
  • sound output: [ba]
  • speaker’s lips/mouth: [ga]
  • listener’s perception [da]

Results: articulatory information influences perception

52
Q

semantics

A

study of linguistic meaning
- denotation: the definition
- connotation: additional nuances, not associated w the def but critical to understanding
- running late for class vs running in the Olympics

53
Q

how do we determine meaning

A
  • many words are ambiguous and can reflect polysemy = multiple possible meanings
54
Q

time course of meaning determinations

A

time course - when you hear a sound how long does it take to decide what it is/means

55
Q

context study (Swinney)

A
  • listened to paragraph stories
  • lexical decision task: word appears on screen as they are listening and ppl have to decide if word is real or not
  • timelock the word on the screen - sound to visual

probe point 1: “several bugs in the corner of his room”
- lexical task: spy/insect vs book/schnerp
results: faster for insect and spy than book

probe point 2: after the word “corner”
- lexical task: faster for insect < spy < book
results: ppl select relevant meaning

56
Q

syntax

A
  • arrangement of words and phrases into sentences according to grammar
  • in English word order is important
  • also for ambiguous concepts
    • “visiting relatives canbe a nuisance”
57
Q

transformations in grammar - Chomsky “Universal Grammar”

A
  • deep structure: abstract underlying representation of the idea of the sentence
  • surface structure: actual realization of the sentence
  • 1 surface structure, 2 deep structure
    • relatives coming to visit you vs you having to visit relatives
58
Q

syntactic parsing

A
  • grouping a sentence into grammatical frames to determine meaning
  • immediacy: parsing occurs as each word is encountered
  • as you read, you are slotting these things in your mind
  • online: in the moment
59
Q

reparsing

A

boggle: when you don’t completely understand the grammar of the sentence and have to go back
garden path sentences: don’t understand the grammatical structure so you have to go back and reread

60
Q

syntax: first approach

A
  • claim: parsing is based on grammar not meaning
  • one alternative meaning is considered at a time
  • very fast process
  • assume simplest structure based on input
61
Q

semantic influences on parsing

A
  • syntax and semantics work together
  • need semantics to understand the sentences
62
Q

speech acts

A
  • speech is typically produced for a reason, to ‘perform’ some act
  • direct speech act: “open the window”
  • indirect speech act: “can you open the window? or “it sure is hot in here”
  • people speak in diff ways depending on who they are speaking with
63
Q

rules of communication: cooperative principle (Grice)

A
  • assume that speakers are always cooperative
  • be relevant, truthful, conscise, clear
  • when ppl violate it we try to understand why
  • hold even with violation of maxims
    • even when someone violates the maxims you are still interpreting why they are doing it (rec letter example)
64
Q

prosody

A

tone of the way people say things
- flat affect: when someone speaks in monotone

65
Q

reading

A
  • eye tracking during reading
  • fixation time increases for difficult words
  • pupillometic changes: pupils dilate for confusing words
  • saccades (eye movements) decrease when something is more confusing
66
Q

Sapir-Whort Hypothesis - linguistic determinism

A

strong version: linguistic determinism: the language you speak determines the way you think
weak version - linguistic relativity: the language you speak can influence how you think

67
Q

problem solving: definition

A
  • any goal-directed activity is a form of problem-solving
  • includes planning and commonsense reasoning
68
Q

ways to study problem solving

A
  • observation = puzzle room or escape room
  • introspection = having people talk out loud as they are solving the problem
  • product and process considerations
69
Q

studying problem solving: Sultan the chimp (Kohler)

A
  • put the chimp in a cage and would set up problems for it to solve and observe
  • ex. boxes around the cage with a banana hanging from the top of the cage
  • sultan would throw the boxes until one accidentally landed on the other and then he would realize that he could stake them to get the banana
70
Q

Kohler: insight

A
  • moment where you figured something out
  • the point at which the relationships between elements in a problem facilitate the development of a solution
71
Q

measuring problem-solving

A
  • speed and accuracy
  • think-aloud/talk-aloud protocols valid measures
  • how to account for background knowledge
  • evaluating or controlling the setting or context of the problem
72
Q

elements of problems: formal approach to problem solving (Newell & Simon)

A
  • problem space: all the possible steps and possibilities for a problem
  • goal state: end goal
  • initial state: beginning of the problem
  • intermediate steps: subgoals btw beginning and end
  • operators: tools and methods to reduce current and goal state
  • production systems: rules for solving problems
73
Q

elements of problems: visualization

A

initial state with subsequent subgoals until the end state has been achieved

74
Q

elements of problems: Sultan example

A
  • problem space: wants banana, needs to reach banana
  • goal state: eat banana
  • initial state: sees banana out of reach
  • intermediate steps: staking crates, sticks, jumping
  • operators: stick, boxes, movement, cage
  • production system: physical limitations and affordance of the environment
75
Q

strategies and methods for problem solving: heuristics

A
  • rule of thump you apply bc its easy and usually gives you the right answer
  • common sense
  • fast, easy
  • not always the correct solution
76
Q

strategies and methods for problem solving: algorithmic

A
  • using data to make an assessment
  • systematic
  • slow, laborious,
  • guaranteed solution
77
Q

brute force search

A
  • every possibility, usually for small problem spaces
  • exhaustive, systematic search through the problem space

advantage: easy to apply
disadvantage: combinatorial explosion
- most problems are too big
- number of states in problem space increases dramatically with some increases in the attributes of the problem

78
Q

difference reduction

A
  • to solve problem, you try to reduce the differences btw your current state and the goal state

disadvantage: hill climbing
- by trying to reduce the diff but not actually getting any closer to the solution
- can move towards subgoal that actually puts you further away from the intended goal state

79
Q

means-end analysis

A
  • compare current state with goal state and choose subgoals to reduce diff

disadvantage: doesn’t work if subgoals cannot be indentified

80
Q

working backwards vs working forward

A
  • thinking about the goal state and moving backward
81
Q

analogies

A
  • structural similarity btw situations or events
  • problem spaces that relate to each other
82
Q

what can go wrong in problem-solving

A
  • failure to understand the problem
  • failure to see connections
  • hill climbing
  • distraction by irrelevant info
83
Q

what can go wrong during problem-solving: functional fixedness

A
  • expectations about how to use a given object
  • experience can hinder insight
  • requires ‘cognitive restructuring”
  • Bunker candle problem
84
Q

what can go wrong during problem-solving: set effects

A
  • expectations about how to solve a particular problem
  • water jug problem
85
Q

what can go wrong during problem-solving: failure to transfer

A
  • finding similarities and links to an earlier problem
  • the tumor problem (Gick and Holyoak)
  • need someone to connect problems for you in order to solve them
86
Q

reasoning and decision-making: defs

A

reasoning - drawing conclusions based on principles and/or evidence

judgment/decision making - evaluating and selecting among alternatives

87
Q

normative method

A

how people should reason
getting many opinions/evidence/info

88
Q

descriptive reasoning

A

what people actually do

89
Q

logical reasoning

A
  • logic = set of rules you apply to study the world
90
Q

syllogistic reasoning

A
  • formal procedure that ensures accuracy if rules of logic are followed (like math proofs)
  • validity in syllogistic reasoning is determined by form, not content
91
Q

belief bias

A
  • if syllogism’s conclusion is true or agrees with a person’s belief, then the syllogism is likely to be judged as valid

ex. “republicans have larger brains” - “Ash is republican” - “Ash has a larger brain”
- people who are not republicans tend to say that it’s not believable
- what people want or expect or culturally believe should be true intrudes upon their reasoning

92
Q

Wason card selection task

A
  • 4 cards: each card has a letter on one side and a number on the other
    Cards: A 2 X 3
  • task: what are the fewest cards you could turn over to determine if there is a vowel on one side, there is an even $ on the other?
  • Flip A first: confirmation bias
  • Second flip should be 3 because it ensures there is not a vowel on the other side
  • 2 doesn’t matter because not all even number have to have vowels
  • X doesn’t matter because rule doesn’t say anything about consonants

Results:
- only 25% flip 3
- 60% choose 2
- 15 % choose X

93
Q

falsification

A
  • to test a rule it is necessary to find situations that disconfirm the rule
94
Q

real-world Wason task (Griggs & Cox)

A
  • if a person is drinking beer, then the person must be over 21
    • Cards: Abe - beer, Betty - 22, Chuck - coke, Diane - 17
  • task: how do you determine whether law is being broken?
  • flip the one drinking beer and the one who is 17
  • context helps, people do well when the task is more real-world oriented
95
Q

expected value

A
  • what leads people to make decisions
  • A: 50% chance of winning $50
  • B: 25% chance of winning $110
  • economists would calculate expected value, always choose B because it has higher chances
96
Q

subjective utility

A
  • imagine its lunchtime, wallet is empty, and you are very hungry
  • A: 85% chance of winning $8
  • B: 25% chance of winning $28
  • expected value is higher for B but people choose A because they want to eat
  • most of us choose a lower expected value, bc subjective utility of the outcome is much higher
97
Q

framing effects

A
  • reasoning is influenced by whether a problem is framed in terms of gains or losses
  • if frame emphasizes gains people are risk-averse
  • if frame emphasizes losses, people are risk-takers
98
Q

pandemic/vaccine study (Kahneman & Tversky)

A
  • calculating subjective probabilities is difficult
  • people use approximations to simplify problems
  • these approximations help but can result in errors
99
Q

representativeness heuristic

A
  • people often choose things that look like what they expect
  • when flipping a coin people are more likely to choose the pattern that looks more random
  • people expect some level of randomness but tend to underestimate random sequences
100
Q

representativeness heuristic: gambler’s fallacy

A
  • many people believe a 6 is due if it hasn’t been rolled in a while
  • but each roll is independent of previous rolls
  • people ignore basic mathematical truths by relying on heuristic reasoning
101
Q

availability heuristic

A
  • the “ease” with which we generate examples from memory influences expectations for events
  • “ease” is not perfectly correlated with objective frequency
  • if you can easily remember something you often think its true
102
Q

anchoring and adjustment

A
  • how frequent is “blank”
  • depends on how you ask the question and on your starting point for evaluating the answer
  • to make decision we establish anchor to initiate a starting point even if the anchor is not relevant
  • ex. what percentage of African countries are in the UN
    • giant wheel in the room and ppl pick the number the wheel was on
    • if it was on a smaller number they would make smaller guesses

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