Part of Test 3 (My Study Guide) Flashcards
1
Q
Language: What is it?
A
- No easy definition is likely to distinguish complex communication systems from “true language” to all researchers’ satisfaction
- A shared system of symbols and rules that allows us to communicate
2
Q
Language Universals
A
-A simple definition is difficult, but we can identify features that are universal to human language
- Features:
- Semanticity
- Arbitrary
- Flexibility
- Naming
- Displacement
- Productivity/Generativity
3
Q
Semanticity
A
- Language conveys a meaning
- Ex: coughing alone doesn’t express your flu as well as you saying, “I have the flu.”
4
Q
Arbitrary
A
- There’s no inherent connection between the symbols and their referents (words and meaning)
- Ex: of “yes” - the word “yes” doesn’t say anything about what it means; the way it looks doesn’t say anything about what it means
5
Q
Flexibility
A
- Since connections between words and referents are arbitrary, we can change them
- Ex: Slang changed the meaning of some words in particular contexts (bad, sick, wicked, minute, truthiness)
- Ex: Shakespeare made up a lot of words
6
Q
Naming
A
- We name everything…if it doesn’t have a name, we make one up
- Ex: In an unfamiliar environment: “The blue thingy…” “That little doohickey there…”
7
Q
Displacement
A
- We communicate about things that are not present and may or may not happen. We project into the future and the past.
- Ex: Well, if I have to work tonight, then tomorrow night I can do homework, and then if I get all that done I can go on a road trip this weekend. Unless they don’t feel like it; then maybe we can…
8
Q
Productivity/Generativity
A
- We produce/generate novel ways of saying things rather than repeating the same sequences over and over
- Ex: “Oh, my God. There’s a snake! There’s a snake over there!” “A snake it on the ground.”
9
Q
Levels of Language - Grammar
A
-The complete set of rules that will generate acceptable utterances, but not illegal utterances
- Thought to operate on several levels:
- Phonology
- Lexical
- Syntax
- Conceptual
- Belief
- Read about 4 and 5 in book!
- Belief
10
Q
Phonology and Phonemes
A
-Phonology: a language’s sounds and rules for combining sounds
- Phonemes: smallest segment of sound in a given language
- Ex: /a/ - “table”; /ae/ - “sat”; /b/ - “ball”; /k/ - “snake”’ /d/ - “door”; /E/ - “me”
- Phoneme boundaries: boundaries by which we identify phonemes
- Ex: English: Princess and pituitary: “p” sounds the same, even though there are physical differences
- Ex: Spanish: No difference between “s” and “z” – Ice and eyes sound the same for native spanish speakers
11
Q
Levels of Language - Lexical Level
A
-Lexical level: words and their meanings
- Morphemes: smallest linguistic unit that has semantic meaning to it; if can’t break down into smaller units
- Ex: stop
- Ex: Unstoppable: 3 morphemes
- Un – 2 phonemes /u/, /n/– NOT
- Stop – 4 phonemes /s/,/t/,/o/, /p/– HALT
- Able – 3 phonemes: /ae/, /b/, /l/– ABILITY
- Polysemy: multiple meanings (activating semantic network and deactivating the irrelevant stuff)
- We resolve the meaning through context:
- Step 1: Activate all meanings at a low level
- Step 2: Deactivate irrelevant meanings based on context
-Ex: “She drove into the bank.”
12
Q
Levels of Language - Syntax
A
-Syntax: the structure of a sentence; how to put words in a sequence so they’re meaningful
- Planning how to say something
- -Given new strategy: we construct sentences based in part on the accessibility of the meaning; gonna say easy stuff first because more accessible in semantic network
- Why? We start speaking once the 1st part has been planned but before the end has been planned
- More complex syntactical structures require more planning
-Ex: “I want a donut.” vs. “It would be pleasant, if not downright enjoyable, to eat a donut in the not so distant future, and I will take advantage of the opportunity to do so should it arise.”
13
Q
Comprehension
A
-Additional processes that are involved in understanding real-world samples of language and text
- Comprehension as a structure-building framework
- Like building a house out of legos
-1. Lay the foundation form the initial representations, capture meaning
- Mapping additional concept meanings and inferences get added; starting to make inferences
- Ex: She was glad that snow made people….?
- Mapping additional concept meanings and inferences get added; starting to make inferences
- Shifting to a new structure encounter change cues that require new structures
- Ex: the check that she’d get from….?
- Shifting to a new structure encounter change cues that require new structures
- She drove into the bank to get some money.
- She was glad that the snow made people stay at home, so there wasn’t much traffic.
- The check she’d get from the insurance company for the accident would help her pay off her credit card bill.
14
Q
Comprehension - Mental Structure
A
-A mental representation of the situation conveyed by language; mental representation of what you’re reading
15
Q
Comprehension - Situation Models
A
-A mental simulation of the world described by a text – includes prior semantic and episodic knowledge
- Ex:
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- The door swung open at once. A tall, black-haired witch in emerald-green robes stood there. She had a very stern face and Harry’s first thought was that this was not someone to cross.
- ‘The firs’-years, Professor McGonagall,’ said Hagrid.
- ‘Thank you, Hagrid. I will take them from here.’
- Bridging inference: make a connection between concepts that may or may not be explicitly stated
- Ex:
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- THE DOOR swung open at once. A tall, black-haired witch in emerald-green robes stood there. She had a very stern face and Harry’s first thought was that this was not someone to cross.
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- [IT] swung open at once. A tall, black-haired witch in emerald-green robes stood there. She had a very stern face and Harry’s first thought was that this was not someone to cross.
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- Authorized vs. Unauthorized inferences
- Authorized: Inference that speaker/author intends for you to make
- Unauthorized: Inference that speaker/author did NOT intend for you to make
- Ex of authorized: Hagrid raised a gigantic fist and knocked three times on the castle door. The door swung open at once. A tall, black-haired witch in emerald-green robes stood there. SHE had a very stern face and Harry’s first thought was that this was not someone to cross.
- Ex of unauthorized: “You look nice today.” “So I looked bad yesterday?”
16
Q
Comprehension (Wrapped Up)
A
- Mental structures → mental representations, structure building (basic building blocks)
- Situation models → simulations, using mental structures, drawing on prior knowledge, allows you to make inferences
17
Q
Language and the Brain
A
- Includes:
- Broca’s Area: Involved in speech planning and programming
- Arcuate Fasciculus: Axons that connect Broca’s and Wernicke’s areas – communication between the regions
- Wernicke’s Area: Involved in language understanding; come up with meaning
- Aphasia: language impairment; type depends on…?
18
Q
Types of Aphasia
A
- Broca’s Aphasia
- Wernicke’s Aphasia
19
Q
Broca’s Aphasia
A
- Brain Area Affected: lateral frontal lobe
- Spontaneous Speech: Nonfluent
- Comprehension (if what they’re saying makes sense or not): Good
- Repetition: Poor
- Naming: Poor
- May be able to read, but writing often difficult
- Usually aware of the problem
20
Q
Wernicke’s Aphasia
A
- Brain Area Affected: lateral temporal lobe
- Spontaneous Speech: Fluent
- Comprehension: Poor
- Repetition: Poor
- Naming: Poor
- Reading and writing usually impaired
- Usually unaware of the problem
21
Q
How we make decisions?
A
- Heuristics (ex: when playing blackjack: greater than 15? No more cards)
- Algorithms
22
Q
Heuristic
A
- A rule of thumb; a shortcut
- More automatic
- Ex: Playing blackjack
23
Q
Algorithm
A
- A rule or procedure that will provide a correct answer
- More controlled
24
Q
Common Heuristics
A
- Frequency/Probability Judgements
- The availability heuristic
- The representative heuristic
- Gambler’s fallacy
- Base rate neglect
- Sample size (law of large numbers)
- Blame Judgements
- Counterfactual thinking
25
Frequency Judgment
-A judgement about which of a set of choices happens most often
26
Availability Heuristic
-We make a decision based on the ease with which the relevant information comes to mind (how quickly it comes to mind)
- Ex:
- Are there more words that start with “r” or more words with “r” in the 3rd position?
- Are there more deaths from tornadoes or asthma?
- The government has $1 billion to put toward one project. Should it be put toward more protection from terrorism or better infrastructure (e.g., roads and bridges)?
- Remember X times you were assertive. How assertive are you?
27
Representative Heuristic
-Judging the probability of something based on how much it resembles its population or the process that produced it
- Ex: For the next 6 babies born in the US, which of the following sequences is most likely?
- BBBBBB(doesn’t represent population) GGGBBB (too orderly) GBBGBG (random and does represent well!)
- All are equally likely
28
The Gambler’s Fallacy
- The FALSE belief that random processes (coin flips, roulette wheels, etc.) are sensitive to prior outcomes
- Ex: You watch a fair coin come up heads 5 times in a row. If you bet $10 on the next coin toss, do you bet heads or tails?
29
Base Rate Neglect
-Failure to take the baseline probabilities of events into consideration
- Ex: Steve is shy and withdrawn, usually helpful, but with little interest in people. Meek and tidy, he loves order and structure and has a passion for detail. Is Steve a librarian or a farmer?
- US Demographics: about 3.2 million farmers, and about 178,000 librarians, so farmer more likely, but people think librarian
30
Insensitivity to Sample Size
-Belief that small and large samples should be equally representative of the parent population
- Ex: At one hospital, about 20 babies are born each day. At another hospital, about 50 babies are born each day. For one year, the hospitals recorded the number of days when 60% or more of the babies born were female. Which hospital do you think had more days like that?
- Small hospital has more days like this
31
The Law of Large Numbers
- The larger the sample size, the more representative the sample will be!
- At one hospital, about 20 babies are born each day. At another hospital, about 50 babies are born each day. For one year, the hospitals recorded the number of days when 60% or more of the babies born were female. Which hospital do you think had more days like that?
32
Counterfactuals
- Imagining how outcomes might have been different (simulation), contradicting the facts
- ”If only…” or “What if…” kind of thinking; like second-guessing yourself
- Ex: Imagine that Paul normally leaves work at 5:30 and drives directly home. One day, Paul feels restless at work and leaves early to see a movie. Paul is broadsided by a driver who violated a stop sign and receives serious injuries.
- Downhill change: altering the unusual aspect of a story and substituting a normal event
- Ex: Unusual event: leaving too early; normal event: have him stay at work
- Why mostly downhill changes?
- Easily imagined (availability heuristic)
- They seem more plausible
- We tend to attribute cause to the unusual event
33
Goldiner et al. (2003) Blaming the Victim - When are counterfactuals typically triggered? Is this something we do on purpose? Why put ourselves through this? What effects do they have?
- When are counterfactuals typically triggered?
- Unexpected and bad events
- Is this something we do on purpose? Why put ourselves through this?
- It’s spontaneous and probably automatic
- What effects do they have?
- Can alter ideas of what the cause was and where blame lies
34
Goldiner et al. (2003) Blaming the Victim - Hypothesis
- Cognitive load will reduce the ability to discount counterfactuals when assigning blame
- There may be differences between WMC groups
- WMC might interact with cognitive load
35
Goldiner et al. (2003) Blaming the Victim - Method
- IV: type of story
- GV: working capacity (high-span or low-span)
- DV: compensation, victim blame, company blame
- *Focus on “load during judgement”
36
Goldiner et al. (2003) Blaming the Victim - Results
- Compensation:
- Everybody awarded more money in control story BUT:
- low-spans had significant difference between the two stories; high-spans did not have significant difference
- Blame to victim:
- Low-spans more likely to blame victim than high-spans
37
Goldiner et al. (2003) Blaming the Victim - Conclusions
- Blame more likely for counterfactual triggering stories.
- Victim blaming was worse under load, if load occurred during judgment.
- Load only affected blaming in low-span subjects.
- *The chances that people can discount counterfactual thinking depends on availability of mental resources.
38
Conditional Reasoning
- Determining whether evidence supports, refutes, or is irrelevant to an if-then statement
- Logice doesn’t equal common sense
- Ex: Rule: If P then Q
- Evidence: red light
- Conclusion: stop
- Concrete terms can sometimes hurt and sometimes help
- Ex: of Rule: If you are hunger, then you eat
39
Confirmation Bias
-Confirmation Bias: the tendency to look for and notice information that confirms a conclusion, belief, or hypothesis
40
Problem Solving
-Transforming one situation into another to meet a goal
- Ex: Three men want to cross a river. They find a boat, but it is too small for all of them. The boat can only hold 200 lbs, but Mr. Large weighs 200 lbs, Mr. Medium weighs 120 lbs, and Mr. Small weighs 80 lbs. How can they all get across in the least number of trips?
- 1. Mr. Medium & Mr. Small cross the river
- 2. Mr. Small goes back to the other side
- 3. Mr. Large crosses the river
- 4. Mr. Medium takes the boat back to the other side to get Mr. Small
- 5. Mr. Medium & Mr. Small cross the river
41
Problem Space
- Initial, intermediate, and end state of the problem
- Ex: of three men and one boat (small number of intermediate states of the problem space) vs. the DONALD + GERALD = ROBERT (Huge number of intermediate states of the problem space!) (if receive hint that D = 5, what happens?)
42
Operators
- The legal operations or moves that can be performed
- Ex of Legal: the way the problem is actually solved
- Ex of Illegal: Mr. Large hangs on side of boat
43
Goal
- The solution to the problem
- Types: well-defined and ill-defined
- Well defined: Complete specification of the initial state (the problem) and the end state (the goal), permissible operators, etc
- Ex: Get keys out of car any way necessary, except breaking window
- Ill-defined: The initial states, the goal state, and/or the operators may all be vague.
- Ex: Finding a job
44
Problem Solving Characteristics
- Goal-directedness
| - Sequence of steps
45
Goal directedness
- There is a definite purpose you are trying to achieve
- Ex: Figure out how to work less - good example (NOT “live a better life” - too vague)
- Problem solving characteristic
46
Sequence of Steps
-There has to be a series of things to be done in order to qualify as problem solving
- Ex: Multiplication problems are NOT just a retrieval from memory; other problems (like 14 x 12) require various steps
- 3 x 4 is just a retrieval from memory and doesn’t require various steps
-Problem solving characteristic
47
Problem Solving Obstacles
- Functional fixedness
- Solving anagrams? Ex: in class, one half got “ape” other half got “pea” (because one group received animals, others received foods; solution due to particular mental set)
- Negative Set, set effects, mental set
- Confirmation bias
- Using analogies
48
Functional Fixedness
- Tendency to see only the usual uses of objects in a problem
- Problem-solving obstacle
49
Negative Set, Set Effects, Mental Set
- A predisposition to think of a problem in a certain way, leading to fixation on one strategy
- Ex: guy with two strings to tie
- Problem-solving obstacle
50
Confirmation Bias (Again)
-Tendency to look for info that confirms our hypothesis and to overlook info that argues against it
-Ex: These numbers conform to a simple rule. Discover the rule by generating your own set of numbers. Example set: 2, 4, 6
Answer: any 3 numbers in increasing magnitude
-Problem-solving obstacle
51
Using Analogies
-Analogy: a relationship between two similar concepts, situations, or problems
```
-Ex: DOCTOR : HOSPITAL ::
(A) sports fan : stadium
(B) cow : farm
(C) professor : college
(D) criminal : jail
(E) food : grocery store
```
-Analogies are ways of restructuring the problem so that it’s parallel to another problem using the solution of one problem to solve another
- Ex: A patient has an inoperable tumor. There are certain rays that will destroy this tumor if their intensity is great enough. But at this intensity, the rays will also destroy the healthy tissue surrounding the tumor. How can the tumor be destroyed without damaging the healthy surrounding tissue?
- Only about 10% of participants solved this problem.
- Two other groups of subjects read a story about a general capturing a fortress first.
- Having this previous story helped solve problem above: A general wanted to capture a fortress. He needed a lot of soldiers to do this, but all the roads leading to the fortress were planted with mines. Small groups of soldiers could travel the roads safely, but not large groups. How could the general move all the soldiers he needed toward the fortress? The general decided to divide his army into small groups and send each one down a different road. When he gave the signal, all groups marched toward the fortress where they converged and attacked successfully
-Problem-solving obstacle
52
Insight
-A restructuring of the problem that results in the “aha!” experience; doesn’t require calculations; sudden realization of the solution
- Ex: Connect all 9 dots with 4 straight lines without lifting your pencil from the page.
- People are not very good at predicting their ability to solve insight problems
53
Incubation
-A period of time during which attention is turned away from the problem
- Time away from a problem may
- Relieve fatigue and frustration
- Relieve functional fixedness
- Help people escape negative mental sets (stop thinking about certain solution that doesn’t work)
- Release from irrelevant thoughts (putting things in concrete terms may give you irrelevant thoughts)
54
How are the arbitrary and flexible universals of language related to each other?
- Words and sounds don’t have any inherent connection to its meaning
- Ex: “Yes.”
55
What are 2 of the levels of grammar?
- Conceptual belief
| - Syntax
56
What are morphemes?
- Part of lexical level; smallest linguistic unit of meaning
| - Ex: “unable” = “un” and “able”
57
What is a situation model?
-Mental simulation of a world described in text
58
What is an unauthorized inference?
-An inference somebody makes that another didn’t intent
59
Cumulative question: What is the Pandemonium Model a model of? And what type of model is it?
- Model of pattern recognition
| - Bottom-up or feature detection model
60
What are heuristics and algorithms?
- Heuristics: rules of thumb; mental shortcut
| - Algorithms: more controlled and/or effortful process (ex: of blackjack)
61
What is the availability heuristic?
-Make decision based on how easily information comes to mind
62
What’s the gambler’s fallacy?
-Prior odds don’t influence what’s going to happen next
63
What’s insensitivity to sample size?
-Idea that a small sample and big sample are equally representative samples
64
Cumulative: Name one type of memory that declines with age and one that doesn’t.
- Declines: episodic
| - Doesn’t decline: semantic
65
Cumulative: What is iconic memory?
-Storage buffer for incoming visual stimuli; lasts up to about 1 second
66
Cumulative: What did the paper on stereotypes and memory show?
-If attention is divided or have high cognitive load, more likely to rely on stereotypes (because it’s like a shortcut)
67
What are the three examples of the representativeness heuristic?
- Gambler’s fallacy
- Insensitivity to sample size
- Base rate neglect
68
How did the counterfactual thinking paper examine the relationship between cognitive resources and victim blaming?
-Putting them under load at different times, and other times weren’t under load, and compared results
69
What did they find?
-When people under load while making decision, that’s when people most blame victim (low-spans especially)
70
What is conditional reasoning?
-Determining whether evidence is relevant, irrelevant, or refutes
71
What is confirmation bias?
-Looking at things that will will just confirm your own beliefs
72
Cumulative: What’s are the three basic assumptions of cognitive psychology?
-Mental processes exist, animals are active information processors, those processes can be measured
73
Cumulative: What is transfer appropriate processing?
-The way you study reflects how you will do test
74
Cumulative: Why is decay a bad theory of forgetting?
-Because time doesn’t cause anything
75
Cumulative: What is bottom up processing?
-Putting features together; going from features to patterns
76
Cumulative: What’s an example of deep processing in an educational setting?
-Times table example: 3 x 3 - think of three groups of three apples
77
Cumulative: What’s the difference between serial and parallel processing?
-Serial processing can’t overlap; parallel can overlap
78
Cumulative: What’s an example of an information processing model?
-Modal model
79
Cumulative: What’s the major analogy that information processing uses to understand cognition?
-Computer analogy as its basis
