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Knowing. Semantic memory. Semantic Memory. Memory of the general knowledge of the world While episodic memory is personal – events that happened to you – semantic memory is more general – information that everyone can learn about the world. Two basic questions asked.

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knowing

Knowing

Semantic memory

semantic memory
Semantic Memory
  • Memory of the general knowledge of the world
  • While episodic memory is personal – events that happened to you – semantic memory is more general – information that everyone can learn about the world
two basic questions asked
Two basic questions asked
  • 1. What is the structure and content of semantic memory?
    • Current perspective is that semantic memory is a network of nodes each representing a basic concept and nodes are linked together
  • 2. How do we access the information in semantic memory?
    • Accessing or retrieving information from the network involves spreading activation
semantic memory models
Semantic memory models
  • Quillen and Collins network model
  • Smith’s feature comparison model
collin and quillian model
Collin and Quillian Model
  • A network model – interrelated concepts or nodes are organized into an interconnected network – these connections can be direct or indirect
  • Memory is the activation of a node which can spread to other nodes activating other memories
  • Two forms of connections or propositions:
    • Category membership “is a”
    • Property statements “has”
smith s feature overlap model
Smith’s feature overlap model
  • Showed significant problems of the Quillen and Collins model
  • Used lists of characteristics instead of a network
  • Concepts are defined by a list of features. These features are stored in a redundant manner
  • The decision of whether one concept is an example of an another depends upon the level of overlap
smith s feature overlap model11
Smith’s feature overlap model
  • Feature comparison
    • Where features of two concepts overlap a great deal or very little, the decision is made quickly
    • If some features overlap and others do not, then a stage 2 comparison has to be made and the decision is slower
empirical tests of semantic memory models
Empirical Tests of Semantic Memory Models
  • Sentence Verification Task: Simple sentences are presented for the subjects’ yes/no decisions.
  • Most early tests of semantic memory models adopted the sentence verification task.
challenges to collin and quillian model
Challenges to Collin and Quillian Model
  • Support for Collin and Quillian was cognitive economy – only nonredundant facts stored in memory. Conrad (1972) found that high frequency properties were stored in a redundant fashion
challenges to collin and quillian model15
Challenges to Collin and Quillian Model
  • Conrad (1972) found that high frequency properties were more highly associated with the concepts and are verified faster than low frequency properties – not shown in network model
challenges to collin and quillian model17
Challenges to Collin and Quillian Model
  • Typicality: The degree to which items are viewed as typical, central members of a category.
  • Typicality Effect: Typical members of a category can be judged more rapidly than atypical members.
semantic relatedness
Semantic Relatedness
  • Semantic Relatedness Effect: Concepts that are more highly interrelated can be retrieved and judged true more rapidly than those with a lower degree of relatedness.
  • Resulted in a third revision of the model which required a 3-dimensional model
knowing21

Knowing

Categorization, classification, and prototypes

knowledge
Knowledge
  • Knowledge is the acquisition of concepts and categories – your mental representations that contain information about objects, events, etc.
categorization
Categorization
  • Concepts usually involve the creation of categories
  • Categories – grouping things into groups based upon similar characteristics
  • Categories help organize information so that you do not have learn about every new thing you expereince
concepts and categories
Concepts and Categories
  • Two basic questions:
    • What is the nature of concepts?
    • How do we form concepts and categories?
  • Three approaches to these questions, classical, prototype, and exemplar
classical approach aristotle
Classical Approach - Aristotle
  • Categories have defining features – semantic features that are necessary and sufficient to define the category
    • Necessary – features have to be present for inclusion
    • Sufficient – if these features are present no other features are necessary for inclusion
  • Problem – most members of a category do not have the same defining features
prototypes
Prototypes
  • A prototype of the category is developed
  • The prototype has the semantic features that are most typical of the members of the category
  • New objects compared to different prototypes of different categories, and are included in category with the most similar prototype
  • Members of a category that are less similar to the prototype require longer to verify their inclusion
prototypes cont
Prototypes (cont)
  • Nonmembers of a category can be seen as members if they are similar to the prototype and the differences are not known
  • When asked to name members of a category, those members most like the prototype are named first
  • Priming most effected by prototypes
exemplars
Exemplars
  • Identification of examples or exemplars of the category
  • New objects are compared to to other objects you have seen in the past – your exemplars
  • Advantage of the use of exemplars – it uses actual examples not just a constructed prototype – atypical members can be exemplars of a category
prototypes and exemplars
Prototypes and Exemplars
  • Evidence supports both models of categorization
  • One possibility is that we use prototypes in large categories and exemplars in defining smaller categories
feature comparison theory of determining category membership
Feature comparison theory of determining category membership
  • This model focuses on the strategy used to decide whether an exemplar (i.e. a canary) is a member of a larger category (i.e. bird)
  • This strategy consists of two rules:
    • If the feature associated with the exemplar (canary has feathers) is found to be associated with the larger category (birds have feathers), it provides positive proof the exemplar is a member of the larger category
    • If the feature is not associated with the category (bats have fur), they are not members of the category (a bat is not a bird)
support for feature comparison model
Support for Feature comparison model
  • Consistent with typicality effects – typical exemplars have extensive overlap of features; atypical exemplars have less overlap and require more time to determine their membership
  • Consistent with the false relatedness effect- subjects respond faster when the exemplar is unrelated to the category than when it is somewhat related
  • Also consistent with levels effects
level effects
Level effects
  • Categories are organized in a hierarchy – one category is part of a larger category which is part of an even larger category
  • Superordinate category – largest and most abstract – animal
  • Subordinate category – smallest and least level of abstraction – a canary
  • Base level category – in the middle and at an intermediate level of abstraction - bird
base level categories
Base level categories
  • Most useful and most likely to come to mind and tend to be the most important
  • Children develop base categories before superordinate or subordinate categories
  • When asked to identify pictures, people more likely to give base level category
category levels
Category levels
  • When asked for common attributes of superordinate category, people give very few (vehicle)
  • When asked about attributes of base level categories, many more given (car)
  • When asked about attributes of base level categories, not many more than those given at the base level are added (SUV)
  • Movement from a superordinate category to a base level category results in a great increase in information, but movement to a subordinate category adds very little information
base level thinking
Base level thinking
  • Humans prefer to think a the base level of categorization because it provides the most useful information for predicting membership in a category
  • Superordinate members of a category maybe very different with few similarities – fruit
  • Base level share many common features – apples
  • Subordinate categories are more informative , but are poor discriminators – McIntosh apples share many features of other apples
  • Subordinate level thinking most important in areas of expertise. Choosing wine for dinner
knowing36

Knowing

Connectionism

importance of context
Importance of context
  • Context can act as a prime to understanding correct meaning
    • I saw a man eating fish.
    • Visiting relatives can be boring
  • Context can activate the meaning meant to be conveyed
  • By understanding the context of a communication, you can understand and remember the material better
connectionist model of semantic memory
Connectionist model of semantic memory
  • Involves a network of interconnected nodes each node connected with specific information
  • The connections between nodes vary in strength – referred to as connection weights
  • Nodes that are more strongly connected have greater connection weights
  • Learning involves strengthening the connection by increasing connection weights