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Flashcards in Semantic memory Deck (64)
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1

What is a 'concept'?

A mental representation of a category/class of objects

2

Which theories demonstrate how adults represent concepts?

1. Classical Defining Feature theory
2. Feature Comparison model
3. Prototype model

3

According to Classical Defining Feature theory, what is a 'concept' defined by?

Represented in memory & defined by a set of features

4

What are defining features of a CHAIR? Why are they important? Can a chair have additional features?

Defining features = inanimate, used for sitting on, has a seat

Chair must have these defining features - they are central to the representation of our understanding of the object

A chair can have additional features (e.g. made of wood)

5

Features are 'primitives'. What does this mean?

They can't be broken down into smaller units

Equally important

6

All examples of a concept are equally representative of that concept. True/false?

True - all instances of a concept are equally representative of that concept

7

How are concepts organised in memory?

Concepts are organised in a hierarchy of superordinate & subordinate categories

8

What type of categories (superordinate/subordinate) inherit defining features?

Defining features of the SUPERORDINATE are inherited by the SUBORDINATE

9

What were Collins & Quillian's (1969) key claims?

- knowledge is organised hierarchically in a semantic network
- the network has NODES (concepts) with CONNECTIONS (relationships) between each one
- there are 2 types of connection = ISA (is a member of) & FEATURE (is a defining feature of)

10

What happens when a node in the semantic network is activated?

Activation spreads through connections to other related nodes

11

What is the key argument of Classical Defining Feature theory? What does it mean?

Cognitive economy

E.g. since most birds 'can fly', this feature is attached to the general category of 'birds' (highest possible level) rather than to every individual bird node

Minimises processing effort & resources

12

What happens in memory when we make a judgement between 2 concepts?

When we make a judgement between 2 concepts, they become activated in semantic memory & spread out among the connections

At some point they will intersect, which will suggest a possible relationship
This will trigger a decision stage to verify the relation

13

What does spreading activation in the network allow us to do?

Make predictions - the time it takes to access info in the network depends on the distance that is 'travelled'

We can test our predictions to assess the validity of this account to semantic memory

14

What types of sentence verification tasks can we use to test Collins & Quillian's (1969) predictions?

1. Instance category task
2. Instance feature task

15

What is involved in an instance category task (type of sentence verification task)?

Pps are asked
"Which leads to the quickest answer?"

a) Is a canary a canary?
b) Is a canary a bird?
c) Is a canary an animal?

16

How many levels in the hierarchy are involved in each question of the instance category task?

a) Is a canary a canary?
b) Is a canary a bird?
c) Is a canary an animal?

a) Is a canary a canary? - 0 levels in the hierarchy
b) Is a canary a bird? - 1 level
c) Is a canary an animal? - 2 levels

17

To which question do pps respond fastest to in an instance category task?

Pps say "yes" faster to a) than b), & faster to b) than c)

a) Is a canary a canary?
b) Is a canary a bird?
c) Is a canary an animal?

18

What is involved in an instance feature task (type of sentence verification task)?

a) Is a canary a canary?
b) Is a canary a bird?
c) Is a canary an animal?

Pps are asked
"Which leads to the quickest answer?"

a) Does a canary breathe?
b) Is a canary yellow?
c) Can a canary fly?

19

How many levels in the hierarchy are involved in each question of the instance feature task?

a) Does a canary breathe?
b) Is a canary yellow?
c) Can a canary fly?

a) Does a canary breathe? - 0 levels
b) Is a canary yellow? - 1 level
c) Can a canary fly? - 2 levels

20

To which question do pps respond fastest to in an instance category task?

a) Does a canary breathe?
b) Is a canary yellow?
c) Can a canary fly?

Pps say "yes" faster to a) than b), & faster to b) than c)

a) Does a canary breathe?
b) Is a canary yellow?
c) Can a canary fly?

21

Spreading activation explains what type of priming?

Semantic priming

22

What is semantic priming?

We respond faster to an item when we have already seen an item that is semantically related to it

23

Pps were shown word pairs & asked if both words were real.

Types of pairs they were shown = related real words vs. unrelated real words vs. nonsense words

Who did this study & what did they find?

Meyer & Schvaneveldt (1971)

Found that pps responded faster when the words were related real words

24

Collin & Quillian (1969) said that Classical Defining Feature theory have a number of exceptions. Give an example about ostriches being birds.

Ostriches can’t fly - they can have a separate feature that is linked to a particular object/etc.

25

What is a problem with Classical Defining Feature theory, according to Conrad (1972)?

Not all features are equal - some are more closely associated with a concept than others

e.g. robins have a red breast vs. robins lay blue eggs

26

What is a problem with Classical Defining Feature theory, according to Rosch (1973)?

Not all instances are equal - some are more typical than others

e.g. a robin is a more typical bird than an ostrich; an ostrich isn't captured by the defining feature of a bird (flying)

27

What is the typicality effect?

We respond faster to typical instances of a concept than atypical

28

Smith et al. (1974) found that pps were faster to verify OSTRICH-BIRD or OSTRICH-ANIMAL?

Pps were feaster to verify OSTRICH-ANIMAL

When thinking about the hierarchy, OSTRICH should be closer to associate with BIRD than ANIMAL

29

Name some limitations of Classical Defining Feature theory.

X not all features are equal
X not all instances are equal

X it can be hard to find a set of features that defines membership & excludes non-members

X differences between categories should be clear-cut (i.e have the defining feature or not) but they aren't

30

In Classical Defining Feature theory, are categorical boundaries clearly defined or fuzzy?

Boundaries between categories are fuzzy

People agree with others & consistent across sessions about typical & unrelated instances

People don't agree about atypical instances