Psy 108: ch 8

  1. Semantic memory
    • Our org'd knowledge abt the world
    • vs. episodic memory (info abt events that happend to us)
    • knowledge/info
    • doesn't mention how we acquired that info
    • broad--includes encyclopedia, lang, & conceptual knowledge
    • influences most of our cog activities
    • categories & concepts = essential components
    • allows you to code objs you encounter
    • 4 approaches to semantic memory: feature comparison model, prototype approach, exemplar approach, & network models
    • elderly perform quite well on tests of semantic memory
    • concept-based knowledge unrelated to specific experiences
  2. Episodic memory
    • contians info abt events that happened to us
    • always implies a personal experience
    • emphasizes when, where, or how the event happened to you
    • vs. semantic memory
    • memory of autobiographical events (times, places, emotions, contextual knowledge) that can be explicitly stated
    • can be thought of as a "map" that ties together items in semantic memory
    • inform semantic knowledge & are relient upon semantic knowledge
    • "what," "when," "where"
    • memory structure that remembers events that are observed thru experience
  3. Category
    semantic memory

    • set of objs that belong together
    • ["fruit" rep's category of food items]--your cog system treats these objs as being equivalent
    • concept = our mental rep of a category; what defines that category
    • prototypes = ex's of a category
    • tend to have a structure based on family resemblance--members of a category share attributes w/other members of that category
    • no single attribute serves as necessary & sufficient criterion for membership in that category
    • ppl rely on representativeness when asked to judge category membership
    • (feature comparison model) defining features = something that's absolutely essential for that category [dog has to be mammal]
    • (prototype approach) prototype = most typical rep of a category
  4. Concept
    semantic memory

    • an essential component of semantic memory
    • our mental reps of a category--what defines that category
    • [concept of "fruit"--your mental rep of the objs in that category]
    • even tho objs arent identical you can combine together a wide variety of similar objs by using a single 1 word concept -> greatly reduces storage space b/c many objs can be stored w/same label
    • allow you to make numerous inferences when you encounter new ex's from a category which allow us to go beyond given info greatly expanding our knowledge
    • very few concepts we use in everyday life can be captured by a specific list of necessary defining features (prob w/feature comparison model)
    • no single attribute is shared by all ex's of a concept
    • can be unstable & variable--our notions abt ideal prototype can shift as context changes
    • (network model) each concept rep'd as a node
    • top-down processing emphasizes these
    • stored according to necessary characteristics--what is a mammal?
    • (PDP approach) concepts rep'd by pattern of activity thru set of nodes
  5. Feature comparison model
    Semantic memory

    • concepts are stored in memory according to a list of necessary features/characteristics; ppl use a decision process to make judgments abt these concepts
    • features: either defining or characteristic
    • sentence verification technique: 1 method to test
    • typicality effect
    • major prob: very few of the concepts we use in everyday life can be captured by a specific list of necessary defining features
    • another prob: assumption the indiv features are indpendent of 1 another
    • doesn't explain how members of categories are related to 1 another
    • emphasizes we ignore many details that make each item in a category unique--based on similarity btwn an item & list of features necessary for category membership
    • category membership is very clear-cut [all unmarried males must be "bachelors"]
    • disadvantage: ppl usu can't create list of necessary & sufficient features for a category
    • similar to obj recognition--need certain info to identify a concept/memory
    • identification of concepts involves comparison of attributes btwn a stimulus & semantic memory
    • evidence: longer reaction times for atypical concepts results from smaller overlap in attributes
  6. Defining features
    Feature comparison model

    • attributes necessary to the meaning of the item--something that's absolutely essential for that category [dog has to be mammal]
    • [a robin: it's living & has feathers & a red breast; "bachelor": male & unmarried]
    • vs. characteristic features
    • when ppl encounter an atypical item they need to compare the defining features for the item & its category (requires more time)
  7. Characteristic features
    Feature comparison model

    • attributes that are merely descriptive but not essential/necessar
    • [a robin: it flies, perches in trees, isn't domesticated, small; not all dogs & cats have tails]
  8. Sentence verification technique
    Feature comparison model

    • ppl see simple sentences & must consult their stored semantic knowledge to determine whether the sentences are true/false
    • ["A poodle is a dog"]
    • 1 of major tools used to explore feature comparison model
    • ppl usu highly accurate on this task so not useful to compare error rates across experimental conditions--measure reaction times instead
    • typicality effect: common finding in reearch using this technique
    • faster when item is more typical [quicker to answer "is a canary a bird?" vs. "is an ostrich a bird?" b/c share less features of a bird than a canary does]
    • problematic when applied to real life
  9. Typicality effect
    Feature comparison model

    • ppl reach decisions faster when an item is a typical member of a category (prototype) rather than unusual member (nonprototype)
    • faster to make judgments abt something that's more relevant to the category
    • common finding in sentence verification technique
    • [decide quickly a carrot is a veggie but pause b4 deciding if a rutabaga is]
  10. Prototype
    Prototype approach

    • the item that's most typical & representative of a category; more readily available in memory, rehearsed more often
    • sometimes the prototype of a category may not even exist
    • an abstract, idealized ex
    • have a special, privileged status w/in a category & differ from nonprototypical members in several ways
    • supplied as ex's of a category--ppl judge some items to be better ex's of a concept than other items
    • if someone asks you to name a member of a category, you'll prob name a prototype
    • typicality effect: ppl judge prototypes (typical items) faster than nonprototypes
    • ppl supply prototypes more often as ex's & make quicker judgments abt category membership when assessing prototypes
    • judged more quickly after semantic priming
    • share attributes in a family resemblance category
    • not the same as a basic-level category--it's the best ex of a category
    • our notions abt the ideal prototype can shift as context changes
    • experts construct these in a diff fashion--choose diff & more prototypes than novices
    • [prototype of a dog would be an idealized rep of a dog, w/avg size for a dog & avg other features--not necessarily like any particular dog you've ever seen (vs. exemplar approach)]
    • tends to have most attributes in common w/other items in the category [prototypical dog = golden retreiver]
  11. Prototype approach
    Semantic memory

    • Emphasizes we ignore many details that make each item in a category unique
    • Doesn't explain how members of categories are related to 1 another
    • Based on similarity btwn an item & idealized obj that reps the category
    • You decide whether an item belongs to a category by comparing that item w/a prototype--if the item is similar to the prototype you include it in the category
    • [You conclude a robin is a bird b/c it matches your ideal prototype for a bird]
    • Members of a category differ in their prototypicality (graded structure)
    • Vs. feature comparison model: it'd argue not all members of "bachelor" category are created = & cousin is more prototypical than nephew/priest
    • Advantages: it can account for our ability to form concepts for grps that are loosely structured; can be applied to social rel's as well as inanimate objs & nonsocial categories
    • Probs: we often store specific info abt indiv ex's of a category--needs to include mechanism for this; doesn't account for experts
    • (Exemplar approach) both say we make decisions abt category membership by comparing new item against some stored rep of the category--if similarity is strong enough we conclude this new item belongs to the category
    • May be more suitable when considering a category that has numerous members
    • Can be abstract--doesn't have to be something you're familiar with/have experienced
    • Instead of going down a checklist you compare 1 to the other
  12. Prototypicality
    • The Prototype Approach
    • Degree to which members of a category are prototypical
    • [A robin & sparrow are very prototypical birds but ostriches & penguins are nonprototypes]
    • [Tomato = nonprototypical fruit; elevator = nonprototypical vehicle]
  13. Graded structure
    • Prototype approach
    • Categories tend to have this
    • Beginning w/most representative/prototypical members & continuing on thru the category's nonprototypical members
    • Shows all members of categories are not created equal
    • Ppl tend to have an order of how typical things are ["bird": parrot b4 ostrich]
  14. Semantic priming effect
    • Ppl respond faster to an item if it was preceded by an item w/similar meaning
    • [You'd make judgments abt apples more quickly if you'd just seen the word fruit than if you'd seen the word giraffe]
    • Helps cog psychologists understand important info abt how we retrieve info from memory
    • Priming facilitates responses to prototypes more than to nonprototypes
    • Basic-level names are more likely to produce this effect
    • If you have a task where you're filling in a word in a sentence ["Joe caught some ____ when he was hunting today"] & showed Bambi b4, the word "deer" is primed to put into that sentence
  15. Family resemblance
    • No single attribute is shared by all ex's of a concept, but each ex has at least 1 attribute in common w/some other ex of the concept
    • Most prototypical item usu has largest # attributes in common w/other items in category
    • [Hairless dog may not have hair but has other things similar to other dogs even tho that 1 feature is diff]
    • Doesn't mean all items w/in a concept have to be defined by 1 universal feature--but certain things will be common throughout the category
    • Characteristics will be diff but won't change category membership
  16. Superordinate-level categories
    Prototype approach

    • Higher-level/more general categories; broad classification
    • ["Furniture," "animal," "tool"]
    • Produced slower than basic-level
    • Activates prefrontal cortex (processes lang & associative memory)
    • Too general for semantic priming
  17. Basic-level categories
    Prototype approach

    • Moderately specific--category that's neither too general/specific
    • ["Chair," "dog," "screwdriver"]
    • Not the same as prototype
    • Seem to have special status--more useful than superordinate or subordinate levels; used more often
    • Used to identify objs--gives enough info w/o being overly detailed
    • Ppl produce these names faster than superordinate/subordinate names
    • More likely to produce semantic priming effect
    • Novices prefer these terms (vs. experts)
  18. Subordinate-level categories
    Prototype approach

    • Lower-level/more specific categories
    • ["Desk chair," "collie," "Phillips screwdriver"]
    • Produced slower than basic-level--when ppl see these terms they freq remember basic-level version later
    • Activates part of parietal region of brain (shift visual attention)
    • Experts prefer terms even more specific than these
  19. Expertise
    • Shows consistently exceptional performance on representative tasks in a particular area
    • Deliberately challenge themseleves & practics tasks in their specific area
    • Must have practiced for at least 10yrs in their area to qualify as an expert
    • Construct prototypes in a diff fashion--diff level of categorization (vs. novices)--very specific terms (even more specific than subordinate)
    • [Someone really into cars has more prototypes for cars than someone who doesn't know much abt them]
    • Concentrate study time on more challenging material
    • Have top-down processes that allow them to perform well on many diff components of prob solving in their area of expertise
    • Memory skills tend to be very specific [expert chess players--memory for various chess positions]
    • More likely to use means-ends heuristic effectively when they encounter a novel prob in their area--divide probs in several subprobs & solve in specified order
    • (Analogy approach) more likley to emphasize structural similarity btwn probs not surface (superficial) similarities
    • Much faster & solve probs accurately
    • More automatic operations & particular stimulus situation quickly triggers a response
    • Usu use parallel processing
    • Better at monitoring their prob solving
    • Domain-specific
    • Knowledge base (schemas, etc.) [easier for professor to read a psych textbook than for us--expectations abt material to be read]
  20. Exemplar approach
    Semantic memory

    • Argues we 1st learn some specific ex's of a concept, then we classify each new stimulus by deciding how closely it resembles those specific ex's
    • Emphasizes your ex of "dog" would be rep'd by numerous ex's of dogs you've known
    • Proposes we don't need any list of featurres b/c all the necessary info is stored in the specific
    • exemplars (vs. feature comparison approach)
    • We make decisions abt category membership by comparing new item agaisnt stored rep of the category & if similarity's strong enough we conclude new item belongs to category--stored rep is a collection of numerous specific members of the category
    • Prob: our semantic memory would quickly become overpop'd w/numerous exemplars for numerous categories--may be more suitable when considering a category that has relatively few members; may be too bulky for some purposes--in many situations it's not effective to use a classification strategy based purely on exemplars
    • May coexist w/prototype approach--so a concept includes info abt both prototypes & specific exemplars; require same kind of cog process
  21. Exemplar
    Exemplar approach

    • Each ex of a concept stored in memory
    • Take up memory
  22. Netowrk models
    Semantic memory

    • More concerned abt the interconnections among related items (vs. whether an item belongs to a category)
    • Propose a netlike org of concepts in memory w/many interconnections
    • The meaning of a particular concept [apple] depends on concepts to which it's connected
    • Includes: Collins & Loftus network model, Anderson's ACT Theories, PDP approach
  23. Collins & Loftus network model
    Network models

    • Semantic memory is org'd in terms of netlike structures w/numerous interconnections
    • When we retrieve info activation spreads to related concepts
    • Includes nodes & links
    • Spreading activation
    • Freq used links have greater strenghts -> activation travels faster btwn the nodes (explains typicality effect)
    • Useful explanation of semantic priming
    • Has been superseded by more complex theories that attempt to explain broader aspects of general knowledge (Anderson's ACT theories & PDP approach)
    • Similar to Anderson's ACT theories: links btwn nodes become stronger as they're used more often--practice is vitally important in dvlping more extensive semantic memory
    • Interconnections rather than grp membership
  24. Node
    Collins & Loftus network model

    • Location in the network
    • Each concept is rep'd as this
    • Connected to other nodes by links to form a network
    • Activated when the name of a concept is mentioned & spreads from that node to other nodes w/which it's connected
    • Links btwn them become stronger as they're used more often
    • Also used in PDP approach
  25. Link
    Collins & Loftus network model

    • Connects a particular node w/another concept node to form a network
    • Freq used links have greater strengths-> activation travels faster btwn the nodes (typicality effect)
    • if many are activated simultaneously each link receives relatively little activation & knowledge will be retrieved slowly
    • Also PDP approach: each node has multiple links & activation of these networks is responsible for our cog processes
  26. Spreading activation
    The Collins & Loftus network model

    • When the name of a concept is mentioned the node rep'ing that concept is activated & the activaiton spreads/expands from that node to other nodes w/which it's connected
    • Activation requires longer to spread to more remote nodes in the network
    • C&Lfocuses on networks for words; vs. ACT-R focuses on larger units of meaning
  27. ACT-R
    Anderson's ACT theories

    • An acronym for "Automatic Components of Thought-Rational"
    • Series of network models that attempt to account for all of cognition
    • Created to explain all of this textbook's topics
    • Declarative knowledge
    • Based on larger units of meaning (vs. network model)
    • The meaning of a sentence can be rep'd by a propositional network (pattern of interconnected propositions)
    • Similar to C&L model: links btwn nodes become stronger as they're used more often--practice is vitally important in dvlping more extensive semantic memory
    • Assumes that at any moment as many as 10 noes are rep'd in your working memory
    • Activation can spread--but the limited capacity of working memory can restrict spreading
    • If many links are activated simultaneously each link receives relatively little action & knowledge will be retreived slowly
    • Focused on larger units of meaning (vs. C&L)
  28. Declarative knowledge
    Anderson's ACT theories

    Knowledge abt facts & things
  29. Proposition
    Anderson's ACT theories

    • The smallest unit of knowledge that can be judged either true/false; simplest piece of info you can say yes/no to ["is this a cat?"]
    • ["Susan gave a cat to Maria"]
    • Meaning of a sentence can be rep'd by pattern of interconnected propositions (propositional network)
    • Each is rep'd by a node & links rep'd by arrows
    • The network rep's the important relations in the propositions but not the exact wording
    • Abstract--don't rep a specific set of words
    • Each concept in a proposition can be rep'd by its own indiv network--these networks need to be complicated to accurately rep the dozens of associations we have for each item in semantic memory
  30. Parallel distributed processing (PDP) approach
    Network models

    • Argues cog processes can be understood in terms of networks that link together neuron-like units
    • Cog processes can be rep'd by a model in which activation flows thru networks that link toegether a large # of simple neuron-like units
    • Aka connectionism/neural networks
    • Emphasize the earlier models based on categorization are too restrictive & fail to account for subtlety of our knowledge abt the world
    • 3 central characteristics: (1) multiple patterns of activation may occur simultaneously (parallel processing); (2) each node has multiple links & activation of these networks is responsible for our cog processes; (3) concept is rep'd by a pattern of activity distributed throughout a set of nodes
    • Extremely complex, sophisticated, & abstract
    • Connections btwn these neuron-like units are weighted & the connection weights determine how much activation 1 unit can pass on to another unit
    • When a unit reaches a critical level of activation it may affect another unit either by exciting it/inhibiting it
    • Every new piece of info you learn will change strength of connections among relevant units by adjusting the connection weights
    • Sometimes we have only partial memory for some info rather than complete perfect memory
    • Broader than the other semantic memory theories
    • Explains overregularization in children: patterns of excitation w/in neural networks
    • Filling in gaps in info--when something's unknown/ambiguous--spontaneous generalizations & default assignment
  31. Serial search
    PDP approach

    • Conducting a complete search of all objs w/the specific characteristic b4 beginning a 2nd search of another characteristic
    • [Carrot: orange, below-ground, veggie, etc]
    • Vs. parallel search
  32. Parallel search
    PDP approach

    • Consider all attributes simultaneously
    • VS. serial search
  33. Spontaneous generalization
    PDP approach

    • Use indiv cases to draw inferences abt general info
    • Advantage of PDP approach
    • Make this when some info is missing in memory
    • Accounts for some of the memory errors & distortions
    • Can help explain stereotyping--draw conclusion abt a general category ["engineering students"]
    • Argues we don't simply retrieve a memory in same fashion we'd retrieve a bk from the lib--we reconstruct a memory & that memory sometimes includes inappropriate info
    • Inductive: relies on you drawing generalizations from indiv cases you see; 1 way we eval evidence
    • VS. default assignment
  34. Default assignment
    PDP approach

    • Based on info from other similar ppl/objs
    • Advantage of PDP approach
    • Fill in missing info abt a particular person/obj by making a best guess
    • Draw conclusions abt a specific member of a category [a particular enginerring student]
    • VS. spontaneous generalization
    • Deductive: using your knowledge abt a category to make some assumption abt an indiv item in that category
  35. Connection weights
    PDP approach

    • Determine how much activation 1 unit can pass on to another unit--since connections btwn the neuron-like units are weighted
    • If weight is +: during critical level of activation it excites another unit
    • If weight is neg: during critical level of activation it inhibits another unit
    • Learning a new piece of info changes the strength of connections among relevant units by adjusting these connection weights
  36. Graceful degradation
    PDP approach

    • Brain's ability to provide partial memory
    • [Tip-of-the-tongue phenomenon]
    • Explains why the brain continues to work somewhat accurately even when an accident, stroke, or dementia has destroyed portions of cortex
    • As memory declines, you're able to remember little pieces of it b4 it's completely gone
  37. Tip-of-the-tongue phenomenon
    PDP approach; Metacognition

    • 1 form of graceful degradation
    • Subjective feeling you have when you're confident you know the target word for which you're searching but you can't recall it
    • Metacog: ppl know enough abt their memory for the target word to be able to say "this word is on the tip of my tongue"--likely to identify 1st letter & other attributes of target word w/similar sounding words that resemble it
    • Bilinguals experience it more freq than monolinguals (larger vocab -> more opportunity for confusing words)
    • Ppl successfully retrieve the word abt 1/2 the time usu w/in 1st 2 min (associated w/strongest feelings)
    • These words are likely to be correctly recognized later
  38. Schema
    • Generalized knowledge abt a situation, event, or person
    • Influences way we understand a situation/event
    • Theories helpful to explain how ppl process complex situations & events--propose ppl encode in their memory "generic" info abt a situation then use this info to understand & remember new ex's of the schema
    • Guide your recognition & understanding of new ex's b/c you say to yourself "this is just like what happened when..."
    • Emphasize how top-down & bottom-up processing work together
    • Allow us to predict what will happen in new situation & predictions usu correct
    • Heuristics
    • Emphasize active nature of our cog processes--event happens & immediately try to think how it's related to an established schema--if not consistent w/a schema need to reconcile the inconsistency
    • Can sometimes lead us astray & make errors (usu rational)
    • Used interchangeably w/term script
    • During cog processing they operate: during selection of material to be remembered, in boundary extension, during abstraction, during interpretation, & during integration
    • Memory selection: sometimes ppl remember material better when consistent w/schema [office schema] & other remember best when it's inconsistent (violates expectations, vivid, surprising)
    • Boundary extension: schemas help us fill in missing material during memory tasks--memory stores schema-consistent images rather than partial figures
    • Abstraction: remember the gist so our abstracted version is consistent w/original schema; integrate info to construct large schemas (when don't neeed to remember exact words)
    • Inferences: use schemas to interpret material & "remember" their own interpretation rather than original message; influence when reading ambiguous material
    • Integration: schema-consistent likely when recall is delayed & ppl are performing simultaneous task--material becomes integrated w/existing schemas & recall is altered
    • Clearly influence our memory but not completely
    • Experts & novices differ substantially--need appropriate schemas to understand a topic properly; knowledge base
    • Cognitive maps
  39. Heuristics

    • General rules that are typically accurate
    • Include schemas
    • Cog maps: general prob-solving strategy that usu produces a correct solution; rep relative positions in our mental maps
    • It's easier to store a schematic version of an event than a precise version of it that accurately reps all the little details
    • Prob-solving: strategy where you ignore some alternatives & explore only those that seem esp. likely to produce a solution; need to weigh benefits of heuristic's speed vs. costs of possibly missing correct solution
    • Most widely used heuristics in prob solving: analogy, means-ends heuristic, hill-climbing heuristic
    • Decision making: when we need to make difficult decision we use a guideline that's simple & easy to access; usu fail to appreciate their limits so don't always make best decisions
    • Short-cut strategy to figuring something out
  40. Schema therapy

    • Used in clinical psych
    • Clinician works together w/client in order to create appropriate new schemas that can replace maladaptive schemas dvlpd early in life ["mistrust schema"]
  41. Script

    • Common kind of schema--subcategory--like many schemas wrapped into 1
    • Simple, well-structured sequence of events (in specified order) associated w/highly familiar activity
    • Abstraction, prototype of series of events that share underlying similarity
    • Often used interchangeably w/schema--but narrower term
    • ["Restaurant script"]
    • Much of our ed consists of learning scripts we're expected to follow in our culture
    • Violation -> can be surprising & unsettling
    • When identified early memory recall can be much better [laundry paragraph]
    • Operates in cog processing during: selection, boundary extension, abstraction, interpretation, & integration
  42. Boundary extension

    • When you store a scene in memory--use schemas/scripts for this
    • Tendency to remember having viewed a greater portion of a scene than was actually shown
    • We have a schema for a scene [someone's garbage area] & our cog processes fill in the incomplete objs
    • Material is visual & our schemas help us fill in missing material during memory tasks
    • Activate perceptual schema when comprehending a photo--based on expectations--extend beyond photo as a mental image
    • Implication for eye witness testimony
    • Our memory stroes more idealized schema-consistent images rather than partial figures
  43. Abstraction

    • Memory process that stores the meaning of a message but not the exact words
    • We tend to recall the gist/general meaning w/impressive accuracy so our abstracted version of the passage is consistent w/the original schema
    • VS. verbatim memory
    • Constructive approach vs. pragmatic approach
    • Usu we integrate info from indiv sentences so we can construct large schemas--esp when we don't need to remember exact words
    • But sometimes we know specific words do matter so pay close attention to precise wording
  44. Verbatim memory

    • Word-for-word recall
    • Ppl usu bad w/this, even a few min after passage is presented
    • Professional actors need to have a good 1 to remember exact words
    • VS. abstraction
    • Constructive approach: verbatim impossible
    • Pragmatic approach: if ppl realize they need to pay attention to exact wording their verbatim memory can be highly accurate--esp. if insult/criticism
    • For most things we don't need this
  45. False alarm

    • When ppl "remember" an item that wasn't originally presented
    • During recognition tests ppl usu convinced they'd seen the new items b4
    • Particularly likely for complex sentences consistent w/original schema
    • Rarely made for sentences that violate meaning of earlier sentences
    • Made more for paraphrases of bland sentences than sarcastic ones
  46. Constructive model of memory
    Schemas & Memory abstraction

    • Ppl integrate info from indiv sentences in order to construct larger ideas
    • Later they beleive they've already seen the complex sentences b/c they've combined the various facts in memory
    • Once sentences are fused in memory we
    • can't untangle them into their original components & recall them verbatim
    • Emphasizes active nature of our cog processes: sentences don't passively enter memory where each is stored separately--we combine them into a coherent story fitting related pieces together
    • Can lead us astray if applied inappropriately [when testing verbatim memory]
    • Listen to strories -> recognition test = combos
    • Integrate info from indiv sentences to form broader ideas
  47. Pragmatic view of memory
    Schemas & Memory Abstraction

    • Proposes that ppl pay attention to aspect of a message that's most relevant to current goals
    • Ppl know they usu need to recall gist quite accurately but can ignore specific sentences
    • But if they realize they do need to pay attention to exact wording their verbatim memory can be highly accurate--esp if criticism/insult
    • Perhaps we're esp sensitive abt emotionally threatening material so we make effort to recall exact words
    • Sarcastic vs. neutral condition
  48. Inferences
    Schemas; Reading

    • Allow us to go beyond given info, greatly expanding our knowledge
    • During interpretation phase
    • Recall can contain these
    • Logical interpretations & conclusions that weren't part of original stimulus material
    • Usu ppl use own schemas to interpret material & "remember" their own interpretation rather than original message
    • A person's unique interests & personal background often shape contents of memory
    • Schemas influence them when we're reading ambiguous material--our cog processes actively work to make sense of it so our top-down shapes memory for complex material
    • Background knowledge can mislead ppl causing them to "remember" inferences that weren't actually stated
    • Gender stereotypes: make inferences abt indiv's personal characteristics based on gender
    • Persuasion: ads, "remembering" inferences never actually stated
    • Reading: draw on our world knowledge to activate info that's not explicitly stated in a written passage--draw reasonable conclusion
    • Constructionist view: readers draw inferences abt causes of events & rel's btwn events
    • Readers create these to integrate discourse & construct a well-org'd story
    • We're sometimes just as likely to remember our inferences as the statements actually said--our inferences blend w/text forming cohesive story
  49. Gender stereotypes

    • Widely shared sets of beliefs abt the characteristics of females & males
    • Even when 1 is partially accurate it can't be applied to every indiv of the gender
    • When ppl know someone's gender they often make inferences abt the indiv's personal characteristics [men more competitive than women]
    • During recognition tests most will think they originally saw a sentence consistent w/widely held gender stereotype--make stereotype-consistent inference
    • Implicit memory task: assess ppl's gender stereotypes w/o asking directly (ERP, IAT)
    • Have the power to influence ppl's self images & sense of academic competence
  50. Explicit memory task
    • Directly instructs participants to remember info previously learned (recognize/recall)
    • Ppl may guess what researchers are measuring for -> designed implicit memory tasks
    • Gender stereotypes: better recognition for schema-consistent info [women were gossiping at water cooler vs. talking abt sports]
  51. Implicit memory task
    • Designed to prevent participants guessing motivations (explicit memory task)
    • Ppl perform a cog task that doesn't directly ask for recall/recognition
    • Goal: assess ppl's gender stereotypes w/o asking them directly
    • Supposed to discourage ppl from providing socially desirable answers
    • Assess ppl's semantic memory--their general knowledge abt gender in a culture & tendency to make gender-consistent inferences
    • 2 kinds: ERP & IAT
    • Elderly: requires participants to perform perceptual/cog task; past experience w/the material facilitates performance on task (read familiar sentence faster)--good at this
  52. Event-related potential (ERP) technique
    Implicit memory task

    • Records tiny fluctuations in brain's electrical activity in response to a stimulus
    • Quickly change in response to a surprising word (stereotype-inconsistent info)
    • Assess gender stereotypes using this neuroscience technique
    • Very rapid measure--immediately see change when reading inconsistent info [women talking abt sports]
  53. Implicit Association Test (IAT)
    Implicit memory task

    • Used to assess implicit gender stereotypes
    • Based on principle that ppl can mentally pair related words together much more easily than they can pair unrelated words
    • Ppl w/strong gender stereotypes would think math & males fit in same category while arts & females in another -> fast response
    • Inconsistent pairings: difficulty associating math terms w/women & arts w/men -> responses much slower
Card Set
Psy 108: ch 8
Cognitive psychology