Presentation is loading. Please wait.

Presentation is loading. Please wait.

General Knowledge Structure of Semantic Memory Structure of Semantic Memory –Background –Feature Comparison Model –Prototype Approach –Exemplar Approach.

Similar presentations


Presentation on theme: "General Knowledge Structure of Semantic Memory Structure of Semantic Memory –Background –Feature Comparison Model –Prototype Approach –Exemplar Approach."— Presentation transcript:

1 General Knowledge Structure of Semantic Memory Structure of Semantic Memory –Background –Feature Comparison Model –Prototype Approach –Exemplar Approach –Network Models Schemas & Scripts 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 General Conceptual Knowledge Lexical Knowledge (e.g., “apple” and ) Lexical Knowledge (e.g., “apple” and ) Organized - (e.g., ‘pencil’ related to ‘pen’; think of ‘apple’ ----> ‘banana’ Organized - (e.g., ‘pencil’ related to ‘pen’; think of ‘apple’ ----> ‘banana’ Categories and Concepts 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) Concepts allow us to make inferences when we encounter new instances (e.g. read ‘chair) Natural concepts vs. Artifacts Natural concepts vs. Artifacts Questions 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) Concepts = list of features or attributes (e.g., Smith, Shoben, and Rips 1974) Defining vs. Characteristic Features Defining vs. Characteristic Features Decision Process - 2 Stages Decision Process - 2 Stages –Stage 1 = global comparison –Stage 2 = compare defining features Research Research –Typicality Effect –Category Size Effect (faster RTs for membership in small category) NOT explained Other Problems 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. 1. A poodle is a dog. 2. A squirrel is an animal. 3. A flower is a rock. 4. A carrot is a vegetable. 5. A mango is a fruit. 6. A petunia is a tree. 7. A robin is a bird. 8. A rutabaga is a vegetable.

7 Comparison & Decision in Feature Comparison Model

8 Prototype Approach Classical View vs. Protoype Classical View vs. Protoype Rosch Rosch Idealized version of category (example) Idealized version of category (example) Graded membership - not all memebers Graded membership - not all memebers

9 Bachelor = Unmarried, male But which of the following are really bachelors? 1.My 32-year old cousin, John, who works at a bank in Chicago 2.My 6 month old son Tim 3.An elderly Catholic Priest

10 Characteristics of Prototypes 1. Prototypes are supplied as examples of a category. 2. Prototypes serve as reference points. 3. Prototypes are judged more quickly after priming. 4. Prototypes can substitute for a category name in a sentence. 5. Prototypes share common attributes in a family resemblance category. No one attribute shared by all membersNo one attribute shared by all members In / out phenomenonIn / out phenomenon

11 Mervis, Catlin, & Rosch (1976) Group 1: generated examples for 8 different categories 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 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 Strong correlation between frequency and rating Typicality Effect Typicality Effect

12 Demonstration 7.2: Prototypes as Reference Points

13 Lexical Decision Task apple table tadjld mountain pudor 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:

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

15 Robin Penguin Robin 480 ms. Penguin 660 ms. Bird 550 ms.670 ms. 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 vegetable: carrots, beets, eggplant clothing: shirt, sweater, vest 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 Superordinate Level –furniture, animals, tools Basic Level Basic Level –chair, cat, screwdriver Subordinate Level Subordinate Level –desk chair, persian cat, phillips screwdriver

20 Levels of Categorization 2 Superordinate level Basic-level Subordinate level 1. Basic-level names are used to identify objects 2. Members of basic-level categories have more attributes in common 3. Basic-level names produce the priming effect 4. Experts use subordinate categories differently

21 Carrot Vegetable Same / Different Priming EffectNo Priming Effect

22

23 Exemplar Approach Store specific instances or examples (exemplars) Store specific instances or examples (exemplars) Decision process = comparison of new item to stored exemplars. Decision process = comparison of new item to stored exemplars. Comparison to prototype approach = Comparison to prototype approach = Stored Representation Prototype ApproachExemplar 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. No abstraction - no summary representation. Storage requirements. Storage requirements. May be more suitable for smaller categories. May be more suitable for smaller categories. Evidence from Social Psychology - stereotypes Evidence from Social Psychology - stereotypes Individual differences Individual differences Co-existence: prototypes and exemplars Co-existence: prototypes and exemplars Strategic differences Strategic differences Explaining concept learning! Explaining concept learning!

26 Network Models Semantic networks Semantic networks –(concepts and connections ----> nodes and links) Collins & Loftus Collins & Loftus –Node = concept Link = relation or connection Link = relation or connection –Spreading activation Sentence verification ----> intersections Sentence verification ----> intersections Explaining ‘Typicality Effect’ Explaining ‘Typicality Effect’ Anderson’s ACT* Theory 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 ACT = Adaptive Control of Thought Declarative vs. Procedural Knowledge Declarative vs. Procedural Knowledge Propositional Networks Propositional Networks Proposition - the smallest unit of knowledge with a truth value Proposition - the smallest unit of knowledge with a truth value Proposition = node + link Proposition = node + link Working Memory - active part of Long Term Memory Working Memory - active part of Long Term Memory

33 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. Susan gave a white cat to…

34 Propositional Network for Susan Gave

35 Partial Representation of a Cat in Memory

36 Schemas 1. Larger cognitive units 2. Packages of interrelated units 3. Used to interpret, encode, understand, and remember new instances 4. Provide expectations about what should occur (top - down) 5. Default values / parts - filled in when schema activated 6. Sometimes - errors

37 “When Lisa was on her way back from the store with the balloon, she fell and the balloon floated away.”

38

39

40 Scripts Simple, well- structured sequence of events associated with a highly familiar activity Simple, well- structured sequence of events associated with a highly familiar activity Schema vs. script Schema vs. script Recall of scripts Recall of scripts –Different from conceptual categories (Barsalow & Sewell, 1985) –Script Identification - early vs. late (Trafimow and Wyer, 1993) Appreciating the similarity of scripts Appreciating the similarity of scripts

41 Trafimow & Wyer (1993) 4 different scripts 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) Irrelevant details added (e.g., taking candy out of pocket) Script - identification information presented first or last Script - identification information presented first or last Filler Filler Recall: of script - related events 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 Remember best info consistent with schema or inconsistent Brewer & Treyons (1981) Brewer & Treyons (1981) Rojahn & Pettigrew (1992) Rojahn & Pettigrew (1992) Incidental vs. Intentional learning Incidental vs. Intentional learning

45 Schemas and Boundary Extension

46 Schemas and Memory Abstraction Abstraction Abstraction Verbatim vs. Gist Verbatim vs. Gist Constructive Approach Constructive Approach –Bransford & Franks (1971) –Holmes & Colleagues (1998) Pragmatic Approach Pragmatic Approach –Murphy & Shapiro (1994) –Attention Allocation / Control C & P compatible 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) Bartlett (1932) Ebb vs. Bartlett Ebb vs. Bartlett Interaction of prior knowledge and experience and formation of new memories Interaction of prior knowledge and experience and formation of new memories “War of the Ghosts” story “War of the Ghosts” story Initial vs. Delayed Recall Initial vs. Delayed Recall Bransford, et al (1972) Bransford, et al (1972) Implications - e.g., advertising Implications - e.g., advertising

51 Schemas and Integration in Memory Final process in memory formation Final process in memory formation Result of selection, abstraction, and inference Result of selection, abstraction, and inference Important!! Important!! Integration and Delayed Recall Integration and Delayed Recall Integration and Limited Memory Capacity Integration and Limited Memory Capacity


Download ppt "General Knowledge Structure of Semantic Memory Structure of Semantic Memory –Background –Feature Comparison Model –Prototype Approach –Exemplar Approach."

Similar presentations


Ads by Google