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Semantic Memory. General Conceptual KnowledgeLexical Knowledge (e.g.,
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1. General Knowledge Structure of Semantic Memory
Background
Feature Comparison Model
Prototype Approach
Exemplar Approach
Network Models
Schemas & Scripts
Background
Recall of Scripts
Schemas & Memory Selection
Schemas & Boundary Extension
Schemas & Memory Abstraction
Schemas & Memory Inferences
Schemas & Integration in Memory
Conclusions
2. Semantic Memory General Conceptual Knowledge
Lexical Knowledge (e.g., “apple” and )
Organized - (e.g., ‘pencil’ related to ‘pen’; think of ‘apple’ ----> ‘banana’
Categories and Concepts
Category - a class of objects that belong together (e.g., variety of objects: ‘fruits’ or ‘apple’)
Concept - mental representation of a category
3. Concepts allow us to make inferences when we encounter new instances (e.g. read ‘chair)
Natural concepts vs. Artifacts
Questions
Organization and Structure?
Storage?
Inferences?
Cognitive Economy?
Relatedness and Similarity?
4. Feature Comparison Models Concepts = list of features or attributes (e.g., Smith, Shoben, and Rips 1974)
Defining vs. Characteristic Features
Decision Process - 2 Stages
Stage 1 = global comparison
Stage 2 = compare defining features
Research
Typicality Effect
Category Size Effect (faster RTs for membership in small category) NOT explained
Other Problems
5. Feature Comparison Model
6. The Sentence Verification Technique For each of the items below, answer as quickly as possible either true or false.
A poodle is a dog.
A squirrel is an animal.
A flower is a rock.
A carrot is a vegetable.
A mango is a fruit.
A petunia is a tree.
A robin is a bird.
A rutabaga is a vegetable.
7. Comparison & Decision in Feature Comparison Model
8. Prototype Approach Classical View vs. Protoype
Rosch
Idealized version of category (example)
Graded membership - not all memebers
9. Bachelor = Unmarried, male But which of the following are really bachelors?
My 32-year old cousin, John, who works at a bank in Chicago
My 6 month old son Tim
An elderly Catholic Priest
10. Characteristics of Prototypes Prototypes are supplied as examples of a category.
Prototypes serve as reference points.
Prototypes are judged more quickly after priming.
Prototypes can substitute for a category name in a sentence.
Prototypes share common attributes in a family resemblance category.
No one attribute shared by all members
In / out phenomenon
11. Mervis, Catlin, & Rosch (1976) Group 1: generated examples for 8 different categories
Birds? … robin, sparrow …
Fruits?
Sports?
Etc.
Group 2: provided prototype ratings (low to high) for each example
e.g., sparrow 7 - high
penguin 2 - low
Strong correlation between frequency and rating
Typicality Effect
12. Demonstration 7.2: Prototypes as Reference Points
13. Lexical Decision Task
14. What Is a Priming Effect?
15. Prototype Priming Effect
16. Demo 7.3: Substituting Prototypes & Nonprototypes
17. Group 1: Prototype Ratings
e.g., vehicles: car, truck, tractor, sled
vegetable: carrots, beets, eggplant
clothing: shirt, sweater, vest
Group 2: List attributes possessed by each item:
e.g., car: wheels, steering wheel, doors, etc.
Score: What proportion of an item’s attributes were shared by other category member’s
Strong correlation between score and prototype rating.
18. Prototype Ratings for Words in Three Categories
19. Levels of Categorization 1 Superordinate Level
furniture, animals, tools
Basic Level
chair, cat, screwdriver
Subordinate Level
desk chair, persian cat, phillips screwdriver
20. Levels of Categorization 2 Superordinate level
Basic-level
Subordinate level
Basic-level names are used to identify objects
Members of basic-level categories have more attributes in common
Basic-level names produce the priming effect
Experts use subordinate categories differently
23. Exemplar Approach Store specific instances or examples (exemplars)
Decision process = comparison of new item to stored exemplars.
Comparison to prototype approach =
24. Picture of Dog
25. Exemplar Approach No abstraction - no summary representation.
Storage requirements.
May be more suitable for smaller categories.
Evidence from Social Psychology - stereotypes
Individual differences
Co-existence: prototypes and exemplars
Strategic differences
Explaining concept learning!
26. Network Models Semantic networks
(concepts and connections ----> nodes and links)
Collins & Loftus
Node = concept
Link = relation or connection
Spreading activation
Sentence verification ----> intersections
Explaining ‘Typicality Effect’
Anderson’s ACT* Theory
27. Example of a network structure
28. Portion of Semantic Net
29. Activation Spread
30. Hierarchical Network Structure
31. Levels Effect
32. Anderson ACT = Adaptive Control of Thought
Declarative vs. Procedural Knowledge
Propositional Networks
Proposition - the smallest unit of knowledge with a truth value
Proposition = node + link
Working Memory - active part of Long Term Memory
33. Susan gave a white cat to…
34. Propositional Network for Susan Gave
35. Partial Representation of a Cat in Memory
36. Schemas Larger cognitive units
Packages of interrelated units
Used to interpret, encode, understand, and remember new instances
Provide expectations about what should occur (top - down)
Default values / parts - filled in when schema activated
Sometimes - errors
37. “When Lisa was on her way back from the store with the balloon, she fell and the balloon floated away.”
40. Scripts Simple, well- structured sequence of events associated with a highly familiar activity
Schema vs. script
Recall of scripts
Different from conceptual categories (Barsalow & Sewell, 1985)
Script Identification - early vs. late (Trafimow and Wyer, 1993)
Appreciating the similarity of scripts
41. Trafimow & Wyer (1993) 4 different scripts
Photocopying a piece of paper
Cashing a check
Making tea
Taking the subway
Irrelevant details added (e.g., taking candy out of pocket)
Script - identification information presented first or last
Filler
Recall: of script - related events
23% vs. 10%
(script identified first) (script identified last)
42. Demo 7.5: Nature of Scripts
43. Picture of Room
44. Schemas and Memory Selection Remember best info consistent with schema or inconsistent
Brewer & Treyons (1981)
Rojahn & Pettigrew (1992)
Incidental vs. Intentional learning
45. Schemas and Boundary Extension
46. Schemas and Memory Abstraction Abstraction
Verbatim vs. Gist
Constructive Approach
Bransford & Franks (1971)
Holmes & Colleagues (1998)
Pragmatic Approach
Murphy & Shapiro (1994)
Attention Allocation / Control
C & P compatible
47. Demo 7.7: Contructive Memory
48. Constructive Memory: part 2
49. Murphy & Shapiro (1994)
50. Schemas and Inferences in Memory Bartlett (1932)
Ebb vs. Bartlett
Interaction of prior knowledge and experience and formation of new memories
“War of the Ghosts” story
Initial vs. Delayed Recall
Bransford, et al (1972)
Implications - e.g., advertising
51. Schemas and Integration in Memory Final process in memory formation
Result of selection, abstraction, and inference
Important!!
Integration and Delayed Recall
Integration and Limited Memory Capacity