2Semantic Memory General Conceptual Knowledge Lexical Knowledge (e.g., “apple” and )Organized - (e.g., ‘pencil’ related to ‘pen’; think of ‘apple’ ----> ‘banana’Categories and ConceptsCategory - a class of objects that belong together (e.g., variety of objects: ‘fruits’ or ‘apple’)Concept - mental representation of a category
3Natural concepts vs. Artifacts Concepts allow us to make inferences when we encounter new instances (e.g. read ‘chair)Natural concepts vs. ArtifactsQuestionsOrganization and Structure?Storage?Inferences?Cognitive Economy?Relatedness and Similarity?
4Feature Comparison Models Concepts = list of features or attributes (e.g., Smith, Shoben, and Rips 1974)Defining vs. Characteristic FeaturesDecision Process - 2 StagesStage 1 = global comparisonStage 2 = compare defining featuresResearchTypicality EffectCategory Size Effect (faster RTs for membership in small category) NOT explainedOther Problems
6The 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.
7Comparison & Decision in Feature Comparison Model
8Prototype Approach Classical View vs. Protoype Rosch Idealized version of category (example)Graded membership - not all memebers
9Bachelor = Unmarried, male But which of the following are really bachelors?My 32-year old cousin, John, who works at a bank in ChicagoMy 6 month old son TimAn elderly Catholic Priest
10Characteristics 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 membersIn / out phenomenon
11Mervis, Catlin, & Rosch (1976) Group 1: generated examples for 8 different categoriesBirds? … robin, sparrow …Fruits?Sports?Etc.Group 2: provided prototype ratings (low to high) for each examplee.g., sparrow highpenguin lowStrong correlation between frequency and ratingTypicality Effect
12Demonstration 7.2: Prototypes as Reference Points
13Lexical Decision TaskThe 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:appletabletadjldmountainpudor
14What Is a Priming Effect? Lexical Decision TaskdoctordoctorY/N400 mshospitaldoctorY/N450 msautomobileY/N450 ms
17Group 1: Prototype Ratings e.g., vehicles: car, truck, tractor, sledvegetable: carrots, beets, eggplantclothing: shirt, sweater, vestGroup 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’sStrong correlation between score and prototype rating.
19Levels of Categorization 1 Superordinate Levelfurniture, animals, toolsBasic Levelchair, cat, screwdriverSubordinate Leveldesk chair, persian cat, phillips screwdriver
20Levels of Categorization 2 Superordinate levelBasic-levelSubordinate levelBasic-level names are used to identify objectsMembers of basic-level categories have more attributes in commonBasic-level names produce the priming effectExperts use subordinate categories differently
23Exemplar Approach Store specific instances or examples (exemplars) Decision process = comparison of new item to stored exemplars.Comparison to prototype approach =Stored RepresentationPrototype ApproachExemplarTypical or idealizedrepresentationStored representation =Specific members / instancesAbsence of features -- (characteristic vs. defining)
25Exemplar Approach No abstraction - no summary representation. Storage requirements.May be more suitable for smaller categories.Evidence from Social Psychology - stereotypesIndividual differencesCo-existence: prototypes and exemplarsStrategic differencesExplaining concept learning!
26Network Models Semantic networks (concepts and connections ----> nodes and links)Collins & LoftusNode = conceptLink = relation or connectionSpreading activationSentence verification ----> intersectionsExplaining ‘Typicality Effect’Anderson’s ACT* Theory
32Anderson ACT = Adaptive Control of Thought Declarative vs. Procedural KnowledgePropositional NetworksProposition - the smallest unit of knowledge with a truth valueProposition = node + linkWorking Memory - active part of Long Term Memory
33Susan 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.
36Schemas Larger cognitive units Packages of interrelated units Used to interpret, encode, understand, and remember new instancesProvide expectations about what should occur (top - down)Default values / parts - filled in when schema activatedSometimes - errors
37“When Lisa was on her way back from the store with the balloon, she fell and the balloon floated away.”
40ScriptsSimple, well- structured sequence of events associated with a highly familiar activitySchema vs. scriptRecall of scriptsDifferent from conceptual categories (Barsalow & Sewell, 1985)Script Identification - early vs. late (Trafimow and Wyer, 1993)Appreciating the similarity of scripts
41Trafimow & Wyer (1993) 4 different scripts Photocopying a piece of paperCashing a checkMaking teaTaking the subwayIrrelevant details added (e.g., taking candy out of pocket)Script - identification information presented first or lastFillerRecall: of script - related events23% vs. 10%(script identified first) (script identified last)
50Schemas and Inferences in Memory Bartlett (1932)Ebb vs. BartlettInteraction of prior knowledge and experience and formation of new memories“War of the Ghosts” storyInitial vs. Delayed RecallBransford, et al (1972)Implications - e.g., advertising
51Schemas and Integration in Memory Final process in memory formationResult of selection, abstraction, and inferenceImportant!!Integration and Delayed RecallIntegration and Limited Memory Capacity