Table of Contents II. A Framework for Examining th

RegulatoryFitandClassificationLearning1UsingClassificationtoUnderstandtheMotivation-LearningInterfaceW.ToddMaddox1ArthurB.MarkmanGrantC.BaldwinUniversityofTexas,AustinSept7,2005ToappearinB.H.RossandA.B.Markman’s“ThePsychologyofLearningandMotivation”TableofContentsI.IntroductionII.AFrameworkforExaminingtheMotivation-ClassificationLearningInterfaceIII.ApplyingtheRegulatoryFitFrameworktoClassificationIV.RegulatoryFitEffectsonRule-BasedClassificationLearningV.RegulatoryFitEffectsonInformation-IntegrationClassificationLearningVI.SummaryofClassificationLearningResultsVII.RegulatoryFitEffectsonDecisionCriterionLearningVIII.SummaryandFutureDirectionsIX.ClosingRemarksI.IntroductionMostbehaviorismotivated.Aswemaneuverthroughtheenvironment,weareconstantlyselectingbehaviorsfromalargerepertoireofpossibilities.Cognitionplaysalargeroleinselectingabehavior,buttheselectedbehaviorisalsostronglydeterminedbyourmotivationalstatetoapproachpositiveoutcomesoravoidnegativeoutcomes.Cognitiveresearchtypicallyfocusesoninformationprocessinganditseffectsonlearningandbehaviorwithlittleattentionpaidtothefactorsthatdriveormotivateonetoact.1ThisresearchwassupportedinpartbyNationalInstituteofHealthGrantR01MH59196toWTM,andR21DA15211toABM.WethankGregAshby,RichardIvry,andAlanPickeringforusefuldiscussionsthatinfluencedthiswork.WealsothankScottLauritzenforhelpwithdatacollection.CorrespondenceconcerningthisarticleshouldbeaddressedtoW.ToddMaddoxorArthurMarkmanbothat:UniversityofTexas,1UniversityStationA8000,DepartmentofPsychology,Austin,Texas,78712(e-mail:[e-mail]@psy.utexas.edu.)RegulatoryFitandClassificationLearning2Theinfluenceofactivegoalsonbehaviorhasbeenthefocusofrecentsocialpsychologicalresearch(e.g.,Aarts,Gollwitzer,&Hassin,2004;Ferguson&Bargh,2004;Fishbach,Friedman,&Kruglanski,2003;Higgins,2000),butlittleworkhasexaminedtheeffectsofmotivationonlearning(cf.Maddox,Baldwin,&Markman,inpress;Markman,Baldwin,&Maddox,inpress;Markman,Maddox,&Baldwin,inpress).Acompleteunderstandingoftherelationshipbetweenlearningandbehaviorrequiresafocusontheinterplaybetweenmotivationandcognition(Carver&Scheier,1998;Higgins,1997).Thebroadaimofthischapteristogeneratearenewedinterestinbridgingtheartificialgapthathasformedbetweenresearchfocusedonmotivationandresearchfocusedonlearning.Thetwowereintimatelyrelatedinthe1950’sand1960’s(Miller,1957,1959;Young,1959),butsincethentheyhavediverged,partiallybecausepsychologybecamemoredividedandarea-driven.Workonlearningbecamethedomainofcognitiveandanimalpsychologists,whereasmotivationwasstudiedbysocialandeducationalpsychologists.Furthermore,researchincognitivepsychologyhasoftenfocusedonthecharacteristicsofparticulartasks(suchasclassification,orvisualsearch),andsotherehasbeenlittleemphasisonintegratingphenomenaacrossdomains.Therehasbeenaparalleldevelopmentincognitivepsychologyandneuroscience.Cognitivepsychologyhasbeguntogeneratemoreintegrativetheories.Atthesametime,researchinneurosciencemakesclearthatthebraindoesnotdistinguishbetweenmotivationalareasandlearningareas.Infact,someofthemostimportantbrainregionsforlearningsuchastheprefrontalcortex,theanteriorcingulateandthecaudatenucleusareeitherdirectlyorindirectlyinterconnectedwithbrainregionsknowntobeinvolvedinmotivation,affect,andpersonality,suchastheamygdalaandtheorbitorfrontalcortexjusttonametwo.Inaddition,detailedneurobiologicaltheoriesarebeginningtotakeholdthatpostulatespecificinterdependenciesbetween“cognitive”and“motivational/emotional/personality”brainregions(e.g.,Ashby,Isen&Turken,1999;Bechara,Damasio,&Damasio,2000;Gray,1987;Pickering&Gray,2001).Althoughthebulkofthetheoreticaldevelopmentinthischapterwillbebehaviorally-based,wewillexploretheneurobiologicalunderpinningsinsomedetailinsectionVIII.Themorespecificaimofthischapteristoprovideaframeworkforexploringmotivationalinfluencesonlearning.Specifically,weexaminetheinfluenceofregulatoryfocus(Higgins,2000)onperceptualclassificationlearning.Perceptualclassificationlearningprovidesanexcellentdomainforstudyingthemotivation-learninginterface,becausequickandaccurateclassificationiscentraltothesurvivalofallorganismsandisperformedthousandsoftimesaday.Inaddition,anumberofsophisticatedmathematicalmodelshavebeendevelopedthatprovidetheresearcherwithinsightintothestrategiesthatpeopleadoptthroughoutlearning.Inthenext(second)sectionwebrieflyreviewRegulatoryFocusTheory(Higgins,2000),anddevelopaframeworkforinvestigatingtheinfluenceofmotivationonbehavior.Theframeworkidentifiesanumberofkeypersonality,motivational,andenvironmentalfactorsthatinteracttodetermineperformanceonlearningtasks.Thethirdsectionappliesthisframeworktoclassificationlearning,andoutlinestwostrongpredictionsthatcanbegeneratedfromtheframework.Thefourthsectionreviewsrecentlypublishedstudiesfromourlaboratoryandseveralongoingstudiesthatprovideinitialtestsofthesepredictions.Thefifthsectionextendstheframeworktothedomainofdecisioncriterionlearning.Weconcludewithsomegeneralremarks.II.AFrameworkforExaminingtheMotivation-ClassificationLearningInterfaceThemotivationli