final exam weeks 7 and 8 Flashcards

(51 cards)

1
Q

problem definiton

A

gap between a present state and a goal state

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2
Q

dominant approaches to problems = ?

A

information processing approach and gestalt approach

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3
Q

information processing approach

A

Involves search for solution using “mean-end analysis” and creating subgoals
- associated with non insight problems

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4
Q

gestalt approach

A

Problem solving is a process involving restructuring the problem (monk example) → once reconstructed, problem may be easy
- associated with insight problems

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5
Q

restructuring

A

process of changing a problem’s representation

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6
Q

fixation

A

people’s tendency to focus on a specific characteristic of the problem that keeps them from arriving at a solution

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7
Q

non-insight problem

A

apply very linear process to solve (math problem; algebra solve for x)

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8
Q

insight problem

A

aha moment - requires a shift in perspective and view the problem in a novel way to achieve solution
(monk problem)

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9
Q

functional fixedness

A

effect that occurs when the ideas a person has about an object’s function inhibit the person’s ability to use the object for a different function

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10
Q

affordness

A

uses of objects are partly what defines them

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11
Q

mental set

A

a preconceived notion about how to approach a problem, determined by previous knowledge/experience

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12
Q

operators

A

in problem solving, permissible moves that can be made toward a problem’s solution

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13
Q

intermediate state

A

the various conditions that exist along the pathways between the initial and goal states

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14
Q

problem space

A

initial state, goal state, and all possible states for a particular problem

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15
Q

means end analysis

A

seeks to reduce the difference between the initial and goal states. This is achieved by creating subgoals, intermediate states that are closer to the goal

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16
Q

analogy

A

making a comparison in order to show a similarity between two different things

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17
Q

source problem

A

a problem or story that is similar to the target problem and provides information that can lead to a solution to the target

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18
Q

surface features

A

specific elements that make up a problem

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19
Q

analogical paradox

A

people find it difficult to apply analogies in lab settings, but routinely use them in real-world ones

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20
Q

experise : pros

A
  • more organized knowledge
  • solve problems faster
  • better snap judgements
  • > likely to notice deep features of a problem
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21
Q

expertise : cons

A
  • no better than movies when given problems outside their field
  • less likely to be open to new ways of look at problems
22
Q

deductive reasoning

A
  • top down
    making a conclusion based on generally accepted statements or facts
23
Q

in deductive reasoning, if premises are correct….

A

conclusion will be correct and will always follow from premises

24
Q

inductive reasoning

A

making an inference based on observations

25
bayesian inference
making predictions based on previous experience
26
heuristics
a ‘rule of thumb’ that provides a best guess solution to a problem
27
avaliability heuristic
Events that are more easily remembered are judged as being more probable than events that are not e.g cows vs sharks; which is more dangerous
28
illusory correlations
correlation that appears to exist between two events, when in reality, there is no correlation or its is weaker than it is assumed to be
29
stereotype
a oversimplified generalization about a group of people that often focuses on negative characteristics
30
Representativeness heuristic
The probability of an event A comes from class B can be determined by how well A resembles the properties of class B
31
base rate fallacy
tendency to disregard the information on base rates in favour of descriptive information
32
confirmation bias
tendency to look for information that confirms our beliefs and overlooks information that is against it
33
myside bias
people generate and test hypothesis in a way that is biased towards their own opinions and attitudes
34
expected utility theory
assumes people are rational, and will (if they have relevant information) make decisions that result in maximum expected utility (in most desirable outcome given the goals) - e.g jelly bean example
35
prospect theory
our decisions reflect values we assign to gains and losses; instead of values we assign to outcomes (influenced by emotions)
36
risk aversion
tendency to avoid taking risks because we magnify the anticipated negative effects of a possible loss
37
risk seeking strategy
we attempt to mitigate hte effects of a potential loss by taking a risk
38
sadder but wiser hypothesis
suggest that being in a sad mood may positively improve decision making by making it more careful and deliberate and less influenced by biases
39
peoples are more likely to engage in ___ ___ behavior when choices are presented as gains
risk avoiding
40
people are more likely to engage in ____ _____ behavior when choices are presented as losses
risk taking
41
when we make a decision, we compare it to what?
context and other decisions
42
framing
decisions are influenced by how the choices are stated
43
status quo bias
tendency to do nothing when faced with making a decision
44
opt in / opt out procedure
choosing for/ against a course of action - people tend not to override the default choice made for them
45
syllogism
series of 3 statements: two premises followed by a conclusion
46
validity
quality of a syllogism whose conclusion following logically from its premises
47
belief bias
tendency to think a syllogism is valid if its conclusion is believable or that its invalid if the conclusion is not believable
48
mental model
a specific situation that is represented in a person’s mind
49
conditional syllogism
two premises and a conclusion (if..then)
50
falsificiation principle
reasoning principle that to test a rule, it's necessary to look for situations that would falsify the rule
51
evolutionary perspective on cognition
idea that many properties of our minds can be traced to the evolutionary principles of natural selection