Studied by 8 people
three determinants of high-level cognition
working memory and problem complexity
time
long term memory
algorithm
rule that generates the solution of a problem
heuristic
rule of thumb
insight
sudden appearance of the solution to a problem
four stage decomposition
preparation
incubation
insight
verification
sudden flash of illumination
ill defined problems are solved by
incrementally
well defined problems are solved
problem
occurs where there is an obstacle between present state and goal state
states and operators
problems are composed of
problem space
the set of all the problem states
creative problem solving
study of incubation and insight
explicit implicit interaction theory
integrative theory of creative problem solving made up of knowledge interaction and knowledge integration
deduction
inference that draws a conclusion about a specific event on the basis of a general concept
induction
an inference that builds a general explanation about something based on a subset of observations
normative models
theories about how people should think
descriptive models
theories about how people normally think
categorical logic
a normative model for reasoning about propositions using and, or, if, if and only if, & not
universal negative
No A are B
universal affirmative
all A are B
particular negative
some A is not B
particular positive
some A is B
belief bias
the natural tendency to judge a conclusion valid based on how believable it is
conditional reasoning
inferences that us "if-then" statements
confirmation bias
seek evidence that confirms ones hypothesis while ignoring evidence that would prove it false
availability heuristic
estimation of the probability of an event is judged by how easy it is to retrieve it from memory
representativeness heuristic
the probability of an event A is evaluated by the degree to which A resembles event B
anchor
an arbitrary value that participants are asked to consider before making a numerical estimate
anchoring effect
numeric estimates tend to remain close to the anchor
classical approach
require necessary and sufficient attributes
principle of family resemblance
use of characteristic features for categorization
catergories
pointers to knowledge
semantic network view of concepts
classical view without restrictive assumptions
classical view
all or none mentality- no levels
prototype view
average of all members of a category, making one common object
typicality effect
prototypical objects are processed preferentially, named more rapidly, more affected by a priming stimulus
exemplar view
categories are represented by the sets of all previously encountered exemplars, there is no summary representation
similarity based approach
some categories can be learned fast (square) and others require a rule (bachelor)
Note 
Flashcard (29)