Concepts and General Knowledge

Question 1

Concept

Answer 1

Building blocks of knowledge. Knowing what an object is. Discussed in terms of “probably”

Question 2

Prototypes

Answer 2

Specify the centre of the category. May be an ideal or the average of all category members that have been encountered. Wide range of empirical evidence (sentence verification, rating tasks), however prototypes vary between individuals.

Question 3

Graded Membership

Answer 3

Objects closer to the ideal are “better” members of that category.

Question 4

Exemplars

Answer 4

Drawing on specific knowledge about category members (examples). Empirical evidence to support this.

Question 5

Family Resemblance

Answer 5

There are features that are common to each category, but no member is likely to have all the features (like a family).

Question 6

Categorising Concepts

Answer 6

Basic - not too specific or too general (apple)
Subordinate - more specific (Jazz apple)
Superordinate - more general (fruit)

Question 7

Categorising by Resemblance

Answer 7

Prototypes and exemplars are heuristics. We use both methods. Prototypes offer a quick summary, exemplars provide information and detail. We switch between the two methods depending on the situation and prior knowledge.

Question 8

Limitations of Categorising by Resemblance

Answer 8

Category judgements can be made by things other that what is typical.
People reason differently about natural and manufactured objects
Understanding of the category guides judgement about membership.

Question 9

Typicality

Answer 9

Degree to which an object, situation or event is typical.

Question 10

Heuristics

Answer 10

A strategy (cognitive shortcut) that is reasonably efficient and works most of the time at the cost of reduced accuracy.

Question 11

Concepts-as-Theory

Answer 11

Understanding concepts requires networks of beliefs about concepts (function, appearance etc) that we can use to make inferences about new cases and integrate new information. Explains differences in natural/manufactured reasoning, however, people may make assumptions based on theories that are incorrect.

Question 12

Knowledge Networks

Answer 12

Knowledge is represented in vast networks of connections. Connections contain information about the relationships between concepts. Allows generalisation of information and deliberate unlearning, however can lead to errors as nodes are closely linked.

Question 13

Local Representations

Answer 13

Each node represents a single idea.

Question 14

Connectionist Networks

Answer 14

Ideas are represented by a pattern of activation and involves parallel distributed processing.