Exam 3 Prep PDF

chapters judgement processthroughwhichpeopledrawconclusionsfromtheevidencethey encounter manyjudgementsbegin w a frequencyestimate assessmentofhow haveoccurred inthepast oftenvariousevents...

chapters judgement processthroughwhichpeopledrawconclusionsfromtheevidencethey encounter manyjudgementsbegin w a frequencyestimate assessmentofhow haveoccurred inthepast oftenvariousevents directaccesstofrequencyinformation oftendon'thave attributesubstitution forrelyingoneasilyassessedinfoi.eheuristics asaproxyforneededinfo strategy heuristics areefficentstrategies thatusuallyleadtothecorrectanswer heuristic availability theeasewithwhichexamplescometomind is aproxyforfrequencylivelihood typicallyaccuratebefrequenteventsobjectsarelivelytobeeasilyavailableinmemorybutcanstillresultinerrors judge intheenglishlanguage aretheremorewordsthatstartw theletter r or havetheletter r inthe3rdsp thereareactuallymorewords w r inthe3rdspot e.g carrotagreesorrybird althoughwordsthatbeginw r areeasiertobringtomind e.g redrunrain aremoredeathscausedbyshamattach orlightningstrines fatalityrateoflighteningstrivesisnearlydoublethanthatofshameattacksbutthelatteris typicallyreportedm rangeofavailabilityeffects studydonebyschwarzetal 1991 wereaskedtorecallpastepisodes inwhich students theyhadbeenassertive onegroupwasaskedtogive6examplestheothergroupwasaskedtogive12examples gaveonlygave6examplesjudgedthemselvesasmoreassertivethanthosewhogave12 thosewho easiertocomeupw 6than12 representativenessheuristic assumptionthatresemblancetotheprototypeprobability assumptionofhomogeneityanexpectationthateachindividual isrepresentativeofthe categoryoverall doyouassumethingsaboutpeoplebasedontheirprofession classparticipationexample  thegambler'sfallacy if acoinlandsonheadseveraltimesin arow w thegambler'sfallacyonemightthinkthenextflipismorelike tobetailsbethesequence should evenouteventhougheachflipisstilla 5050chance conjunction fallacy overestimation ofconjunctionofeventsovertheirindividualprobabilities eg probabilityforfeminist bankteller can'tbehigherthanprobabilityforindividualconstituents feministorbankteller dualprocessmodels sometimeshumanjudgementrisesaboveheuristics insomecontextspeopleseekoutmoreaccuratebaserateinformation aresensitivetopotentialsourcesofbiasetc typeIthinningfast automatic relianceonneuistion type2thinkingslower effortful morelikelytobecorrect typeofthinningusuallydependsoncontextofdecision morelikelytorelyontype1when timepressuretypeI isfasterthantype2 dividedattention type2requiresmoreeffort requiresfocus morelikelytorelyontype2when dobetteroncognitivereflectiontests CRT peoplewho decision making principleofutilitymaximizationorchoosingtheoptionw the greatestexpectedvalue balanceofcosts benefits problemdecisionsareoftenguided byfactorsthathavelittletodow utilitymaximization framingoutcomes prospecttheory gains7losesapproacheddifferently intheprospectofgains canberiskaversive prefercertainm smallgainstolargeuncertaingains eg prefercertaintyofsavinglives riskyprospectofequalorgreaterexpectedvalue risklessprospect intheprospectoflossescanberiskseeking ratherthantakeasurelossof400peopledyingtaketheriskofthepossibilityofnoone dying eg framingwordingoftensest prospect risulessprospect equalexpectedvalue  eachscenariohasidenticalutilitybuttheframingofthescenariochangesparticipantschoices programA ischosenifthe problemis positively framed willbesaved gains riskaversiontoguaranteegains programB ischosen if problemis negatively framed willdie lose riskseekingtoavoidloses diminishingreturnforbothgaina10s sharperlossforlossthangain loss lossaspsychologicallylargennthanthesamedollar aversionpeopletreatthesamedollar gain eg 100lossgiveyoumorepainthan 100gaingivesyoujoy reallyhateloss people risuseemingtoavoidsurelossinthelossframe fuzzytracetheoryFTT verbatimexactquantitative utility gistqualitativemeaning affectiveforecasting yourpredictionsaboutyourownfutureemotions ex howwouldyoufeelafterbreakingupw yourpartner theirreactionwouldbepositiveornegative peoplecanusuallypredictwhether theyareofteninaccurate astotheintensityadurationofthefeelings peopletendtooverestimatetheextentoftheirfuturefeelings lossaversionagain focalism focusingonafutureeventwothinkingoftheeffects orconsequencesofotherevents i e thinkofeventashappening in a vacuum impactbias overestimatingintensity durationofemotions durationneglectforgetthat thistooshall pass logic syllogisms categoricalsyllogismslocialargumentscontainingtwopremises anda conclusion all m areb all darem therefore allaareb beliefbias if asyllogism'sconclusion happenstobesomethingpeoplebelievetobetrueanyhow they'relikelytojudgethe conclusion asfollowinglogicallyfrom thepremises iftheconclusionhappenstobesomethingtheybelievetobefalsethey'relikelytorejecttheconclusion asinval conditional statements if x theny Wason'sfourcardtask biem solving bywhichonedeterminesthestepsneeded toreachagoal process problemspace thesetofallstatesthatcanbereachedinsolvingtheproblem forreallifeproblemsveryextensive forexample problemspacein gameofchesshas700millionpathswithinjustafewturns problem solvingheuristicscanhelptonarrowthesearch heuristicshillclimbingstrategy ateachstepinsolvingaproblemchoosetheoptionthatmovesyou inthedirectionofyourgoal limiteduse manyproblemsrequirebrieflymovingawayfromthegoal atthesepoints peopletendto abandontheirstrategies thismustbethewrongstrategyI'mgoingthewrongway inotherwordstheycouldgetstuckatthelocalmaximumwhichpreventsyoufromreachingtheglobalmaximum heuristicsmeansend analysis whatmeansdoIhavetomakemy morelikemy currentstate goalstate define problems illdefinedproblemsthegoalstateends theavailableoperatorsforreachingthegoalmeansarenotclearlyspecified gradeinthiscourse getting agood or studyinghard  such arebestsolvedby problems sub creatingwelldefined goals canbebroken problems upintosub problems expertsaremorelikelytodothisthannovices expertsalso referenced organizetheirknowledgeeffectivelycross havealreadyassembledroutines addingextraconstraintsorassumptions heuristics analogy requiresfocusingontheproblem's deepstructure ratherjustthesuperficialfeaturese.g itmay notbeenoughtojustthink abouttumors mappingproblemsontostructurallyrelatedcasescanbedifficult problemsolvingcanbeimproved byencouragingpeopletofocusonthedeepstructure relationalmindsetduringinitallearning thenatureofcreativity convergentthinning anabilitytospotwaysinwhichseeminglydistinctideasmightbeinterconnected remoteassociatestest divergentthinning anabilitytomoveone'sthoughtsinnoverunanticipateddirections usetest alternative functionalfixedness thetendencytoberigidinthinningaboutan object's function FIF weremorelikelyto lfrfia.ph solvethecandleproblem if thetackswerenotplacedinsidetheboxwhenthe materialswere presented thinningoutsidethebox problemsolvingsetsnarrowyouroptionsforapproachingtheproblem reducesdistractionfromfutivestrategies aeasethesearch butcansometimesbuildyoutoimportantoptionsor solutions ourproblemsolvingis sometimeslimitedbyunnecessary ormisleading assumptions andit'shelpfultobreakfreeof thoseassumptions e g thesquareformedbythedots gestaltprinciples eg functionalfixedness problemsexamples penniesproblem movetwopennies so allcoinstouchthreeandonlythreepennies matchstickproblems romannumerals rules moveonlyonestick can'tremovestick resultcorrectmathstatement themomentofillumination wallas1926 arguedthatcreativethoughtproceedsinfourstages 1 preparation informationgathering 2 incubation consciousbreak 3illuminationinsightemerges ana moment 4verification confirmationthatthenewidea leadsto asolution manycreativediscoveriesdon'tincludethesestepsorhappenin abackandforthsequence oftennotabruptleapforward butsuccessionof miniinsights 11T abilitytoreasonsolveproblemsandgainnewknowledge oftenstudied inpsychometricapproach seemstounderstandthemostvalidwaytomeasureintelligence stanfordbinetintelligencescales binetinitiallydevelopedthescaletoidentifynormallya subnormallyintelligentchildren adapted stanfordresearchers gaveusthetermintelligence quotient IQ by bydividing a person'smentalagebyhisorherchronological age calculated multiplyingby100 mentalagebasedontheaveragetestscoreofchildren at acertainage apersonof normal intelligence e.g a yroldw thementalageof hasanIQof100 appropriateforchildrenbutnotadults eg s us 8yrold 35us38yrold schleradultintelligencescaleWais we assessperformance onseveralsubscales eg verbalcomprehensionperceptualreasoningetc  the conceptof 10changed w wais IQ isderivedbyplacing an individual'sscoreon a frequencydistributionrelativetoothersameagetesttakers whenthisdistributionismoreorlesssymmetricalit'sreferred to asa normaldistribution w agraphicaldepiction knownasabellcurve general7specificintelligence spearman's twofactorytheoryofintelligence inpearatearly generalintelligence g somesourceofindividualvariationthatcausedsomepeople'sscorestobehigherthanthose godown then ofothersacrosstheboard crystallizedintelligence Gc pertainstopeople'sknowledge asreflectedintestsof vocabulary factsaboutthewor 0 fluidintelligence Gf involvescontentindependentanalytical processeswhichcomeinto playwhendiscerningpatterns intheenviornment understandinganalogiesanddrawinginferences intelligence s variationin individualsubsets specific multipleintelligences theory intelligenceisbest viewedasacollection ofabilitiesusedtosolveproblems orprocedureusefulcreations linguisticintelligencelogicalmathematicalintelligence aspatialintelligencemeasuredinstandardIQtest musicalintelligencebodilykinestheticintelligenceinterpersonalintelligenceintrapersonalintelligenceanaturalisticintelligence support formultipleintelligencestheorycomesfrompeople w suntsyndrome generallyhavelowintelligence astraditionallymeasured butincredibleskillin a particulardomain naturevsnurtureintelligence intelligencebeinginfluenced bygeneticsnature texperiencenurture thesetwoinfluencesdependoneachother natureside intelligencesimilaritymonozygotic dizygoticsibling unrelatedindividuals nurtureside childrenwhowereoriginallyabusedneglectedhadincreases in IQafteradoption especially inhighSESrearingfamily oflynneffect scoresonintelligencetestshaverisen approximately 3pointperdecadeoverthelastfewdecades chp.cc categorization concepts categorization theprocessofgroupingitemsorideastogethera distinguishingthemfromotheritemsorideas canalsobeunderstoodasconcepts themental representations inthebrainthatcorrespondtoobjectsorideasintheworld  conceptwhatis a dog conceptofdog isdelusional possibility our example ananimalw 4legsthatbarns wagsitstail problemw thedefinitionalapproach it'salwayspossibletofindexceptionstoourdefinitions familyresemblance wittgensteinmembers of categoriesshare afamilyresemblance no definingfeatures theremaybenofeaturesthataresharedbyallcategorymembers characteristicfeaturesacross familymembers eg brothersintheSmithfamilyusuallynhavedarkhair usuallywearglasses themorecharacteristicfeaturesof acategoryanobjecthasthemorelikely it istobelongtothatcategory example adogprobablynnhas4legsprobably barns probablynwagsitstail acreaturewhothesefeatures isuntimelytobeadog prototype specifytheprototype thecategoryexamplethatpossessesallthecharistic features e g asparrowisaprototypicalexampleofabirdwhereasanostrichisnot compareagainstthisidealaverage todeterminecategorymembership typicality gradedmembership theprototypeisusuallyanaverageofvariouscategorymembers thathavebeenencountered a category'sprototypewilldifferacrossindividualsbasedontheirexperiences theory prototype suggetsthatcategorymembership isjudgedbased ontheirtypicality howmuchtheyresembletheprototype gradedmembership objectscloseto aprototypearebetter membersofthecategorythanobjectsfartherfromtheprototype eg somedogsare doggier thanotherdogs sentenceverificationtask trueorfalserobinsarebirdsjudgementsaboutitemsthataremoredistantfromtheprototypetakemoretimetomake trueorfalsepenguinsarebirds task production nameasmanyfruitsbirdsasyoucan generallynamethe participants mosttypicalcategorymembersfirst these alsothosethatyieldfirstresponsetimesinthesentenceverificationtask typicalcategorymembersare ratingtasks itemsthatareclosertotheprototypeareratedasmoretypicalofthecategory exemplars casesitemspreviouslyencountered specific decide isthisachair attempttorememberspecificchairsyou'veseentomakedecisions comparetomemoriesofobjects exemplarapproachalsoshowstypical iilityeffect i e itemmoresimilartoexemplar quickerclassification atypicalobjectsitems betteratclassifyingthem bycomparingthemtoexemplarsratherthanprototypes retaininfopossiblylostwo a prototype exemplartheory insomecases categorizationreliesonknowledgeaboutspecificcategorymembers exemplarsratherthantheprototype comparison 1 19 conomicalsummaryofthecategory EIdeinto aboutcategoryvariabilitybutlesseconomical easiertoadjustcategoriesbasedonexemplarsthanprototypes acombinationofexemplars prototypes conceptualk nowledge isamixofemeplar aprototype earlylearningofteninvolvesexemplars ofteninvolvesaveragingexemplars experience togetprototypes withmoreexperiencewecanusebothexemplars prototypes toascertaincategorymembership objects recognize categories superordinatecategory broadestmost general I'musingmyelectronicdevice basiclevelcategory middlegroundusuallydefaultfor I'musingmyphone subordinatecategory mostspecific I'musingmyappleiphone  forcategories memory readstoryaboutaperson'slifewithinstorywasincludedsentencesline shewasdressingshenoticedthather while wasstained blanusfilledw oneof3typesofoptions clothes superordinate pantsbasic jeanssuperordinate memorytest 1week eg whileshewasdressingshenoticed results regardless ofinputlevel wasmostlyatbasiclevel outputi.eanswers of memoriesretainedhadabasicintermediatelevel abstraction generalorspecificinfo transformedintomore effectbidirectional subordinate basic superordinate subsuperordinateconveregedonbasiclevel listcommonattributesfor toolhammerclawhammer basiclevelcategories greaterincrease inintoatbasiclevelthansuperordinatelevel andmuchsmallerincrease whengoingfrombasictosubordinatelevel thatisgettingmorespecificdidn'taddmuchinfo priming categories primingwname furniture superordinate chair basic chair subordinate wooden askedif 2chairsarethesame primingw basicorsubordinatenameledtoquickerdecisions helpsthinkof amorespecificrepresentation hearingsuperordinate thinkofamoregeneralrepresentation slowertomakedecisions hierarchialnetwork containnodespiecesofinformation7linnsassociation betweennodes hierarchialstructureminimizesredundancy spreadingactivation activationorprocessingatnodewilltravelacrosslinns problem 1 verificationarefaster sentence ifthesentenceisaboutamoreprototypicalstimulus acanaryis abird vs anostrichisabird problem 2 theprincipleof non alwayshold redundancydoesn't birds havefeathersvs peacockshavefeathers distributednetwork paralleldistributedprocessing knowledgerepresented inadistributedmanneracrossconnectionsbetweenmultiplenodesratherthanstoredinsinglenodes mimicsbrainprocessing neuronsaremassivelyconnectedaprocessinfoinparallel thisparallelprocessingallowsforsimultaneous considerations ofmanydifferenttypesofinfoorconstraints eg allowsforsensitivitytocontextthatresolvesambiguousornoisyinto theprocessingofreadingstarts w unitsthatdetectvisualfeaturesdistinguishinglettersindifferentpositionsinaword in areadingmodel a layer ofdifferentvisualfeatureshasdifferentcombinationsactivatingdifferentlettersinthenextlayer finally differentcombinations ofletterswillactivatedifferentconceptsinthewordlayeratthetop propositionalnetwork thesmallestunitof knowledgethatcanbeeithertrueorfalse each ellipserepresents a proposition associationsconnectanellipsetootherconcepts associations arelabelledw theroleofconceptsintheproposition embodied cognition groundingproblems ifknowledgeisrepresented as symbolsthenhowdothosesymbolsmaptotheworld amodaltheories thewaysweexperiencetheworld semanticknowledgeisrepresentedsymbolically distinctfrom embodied cognition semanticknowledgeisrepresented bysensory motorsystems havedifficultyaccountingforabstractconceptsthatcannotbedirectlyexperiencedviasensory ormotorsystems e justicefreedom embodiedcognition socialness wordsassocialtools account anembodiedviewonabstractconcepts abstractwords e.gjusticefreedomarelearned understoodprimarilythroughsocial linguisticinteractions evidence supporting thatdistinguishes abstractfromconcreteword studieshaveextractedsocialnessas alatentfactor propertygenerationa featurerating He language of oflanguage psycholinguistics study cognitiveunderpinnings anytheoryoflanguageneedstoaccountforatleastthefollowingqualities language is communicative tothings ideas ameaningful language isreferentialrefers languageisstructured syntaxgrammar languageiscreativecreationofmeaningfulneverbeforespokensentences organizationoflanguage of sentence coherentsequence words word acompletediscreteunitofmeaningin a language morpheme smallestlanguageunit thatcarriesmeaning unitofsoundthatservestodistinguish phonemesmallest phonologyproduction ofspeech categorizationofspeechsoundsbasedon voicingwethervocalfolds vibrate eg 2 vs.ES mannerofproductionhowtheairflowis restricted eg airflowcompletelystoppeduspartiallyrestrictedCpvs f placeofarticulationwhere theairflowisrestricted eg closingoflips b p tonguebehindupperteethCd Ct internationalphoneticalphabetIPA ambiguityinspeechproduction speechsegmentation theslicing ofacontinuousspeechstreamintoappropriatesegments coarticulation inproducingspeecheachphoneme isslightlyaltereddependingonadjacentphonemes makesspeechproductionfaster morefluent acousticalpatterns forphonemesdifferindifferentcontexts resolutioninspeechproduction ambiguity eImci t.ph restorationeffect peopleareableto fillin missing phonemesbasedoncontextualcuesknowledge orexpectation example thestategovernorsmetwtheirrespectivelegilaturesconveninginthecapitalcity topdownprocessingcanchangewhatpeoplehear 2visualinput themcgurneffect lipreadingaffectsyourspeechproduction combiningphonemes phonemes morphemes words onlysomecombinationsofphonemesareacceptablewithinalanguage exthesequence I isnotacceptablewithinasyllableinEnglish rulesforadjustingphonemesarebasedoncombinations morphemes contentmorphemes morphemes thatdescribeplacespeopleactionsetcsuchas run eat a shoe functionmorphemes morphemes thatmodifycontentmorphemessuchas spre aer new building words generativity thecapacitytocreateanendlessseriesofnewcombinationsfromasmallsetoffundamentalunits progressintechnology malwarespyware sexual selfie social politicalchanges metro oncenew canbecombined w otherphonemesmorphemestoalignw thelanguage'ssyntax wordsarecreatedthey uno hackswouldbecalleda hacker someone syntax rulesthatgovernthestructureofaphraseorsentence theboyhittheball vs theboyhitball the howeverasentencecan rulesbutstillbemeaningful violatesynatic cookiemonster'sdemand mewantcookie rulesalsodon'tdependonmeaning synatic eg ideassleepfuriously colorlessgreen phasestructure phasestructurerule theoverallorganizationofthesentence parsing referstotheprocessofdeterminingeachword'ssynatic roleina sentence peopleparsesentencesastheyhear them usuallyeffectivebutcanleadtomisinterpretations Chomsky Chomskyarguedthatbehaviorismcouldn'taccountforhowlanguageis acquired povertyofstimulus lackofinformationintheenviornmentaboutcorrectlanguageuse childrendon't evidenceforungrammaticalsentences receivenegative universalgrammar thereisasetofuniversalprinciplesthatapplytoalllanguages eg recursionembedoneclauseinsideanother thedogthatchasedthecatthatstolethecheese barnedloudly languageacquisitiondevice ahypotheticaltoolinthehumanbrainthatletschildrenlearn understandlanguagequickly languageacquisitiondeviceismodular itdevelops operatesindependently ofothercognitiveabilities evidence williamssyndrome ageneticcondition w intellectualdisabilitybutpreserved languageskills acriticalperiodforlanguageacquisition criticalperiod atimewhenchildrenareoptimallyequipped tolearntherulesof aparticularchange childrenappeartohave moredifficultypickingupa languageafter theyreachpuberty theideaofa criticalperiodis supported by Genie anabusedchildthatwasisolatedfrominfancy notspokentountilshewas13yrsold