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General Knowledge Structure of Semantic Memory Schemas & Scripts

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1 General Knowledge Structure of Semantic Memory Schemas & Scripts
Background Feature Comparison Model Prototype Approach Exemplar Approach Network Models Schemas & Scripts 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 Natural concepts vs. Artifacts
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 high penguin low Strong correlation between frequency and rating Typicality Effect

12 Demonstration 7.2: Prototypes as Reference Points

13 Lexical Decision Task The following items: Decide whether each item is a word (‘yes’) or not a word (‘no’). Respond by pressing the ‘yes’ button or the ‘no’ button: apple table tadjld mountain pudor

14 What Is a Priming Effect?
Lexical Decision Task doctor doctor Y/N 400 ms hospital doctor Y/N 450 ms automobile Y/N 450 ms

15 Prototype Priming Effect
Robin Penguin 550 ms. 670 ms. Bird Bird Robin 480 ms. Penguin 660 ms.

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

21 Carrot Vegetable Same / Different Same / Different Priming Effect No Priming Effect


23 Exemplar Approach Store specific instances or examples (exemplars)
Decision process = comparison of new item to stored exemplars. Comparison to prototype approach = Stored Representation Prototype Approach Exemplar Typical or idealized representation Stored representation = Specific members / instances Absence of features -- (characteristic vs. defining)

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 Does a robin breathe?

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…
Susan gave a white cat to Maria, who is the president of the club. 1. Susan gave a cat to Maria. 2. The cat was white. 3. Maria is the president of the club.

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
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

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