ComputationalDiscourseScience:ApplicationsforEmergingLearningEnvironments

NiaDowellCognitive Psychology

Institute forIntelligent SystemsUniversity ofMemphis

https://sites.google.com/site/niadowell/

Psychology Linguistics Communication Education ComputerScience

InternationalRelations

BusinessIntelligence

NaturalLanguageProcessing

TextAnalytics

ComputationalLinguistics

TextMining Discourseprocessing

CorpusAnalysis

LinguisticAnalysis

ComputationalDiscourseScience

• CollaborativeInteractionandLanguage• Modelingknowledgeconstruction insmallgroupcollaborativeinteractions• Exploringsocialcapital&learninginMOOCs• Modelingsocioaffectiveresponsesincollaborativeinteractions• Modelingcognitivepresenceincollaborativeinteractions

• Emotions,LearningandLanguage• Humanperceptionofnaturalisticaffectivestatesduringhuman-computerinteractions• Cohesionrelationshipsintutorialdialogueaspredictorsofaffectivestates

• TeachersQualityTraining• Exploringgrowthofpedagogicalandcontentknowledgethroughlanguage

• PoliticalLanguageandCrisis• Modelingsocialdisequilibriuminauthoritarianregimes• TemporaldynamicsofsocialcohesionandcasualtiesduringtheSyrianrevolution• DiscourseandsocialdynamicsinArabSpring

• ClinicalInteractions• Qualityoftherapistsandclientsinterpersonalcommunication• Psychologicalfunctioning

BigPicture:ComputationalDiscourseScience

Overview

• Textanalytics:TheoryandApproaches

• Significantapplicationsinlearningsciences

• Movingforward

• Opendiscussion

What

Why

Methodforderivingvaluablemeaning/insights frompatternsandtrendsinlanguage,discourseandtext

80%ofalldataisunstructured:Thismeansnewsarticles,researchreports,educationalmaterial,computer-mediatedcommunication,etc.

TheScopeofAnalyticalApproaches

ManualContentAnalysis AutomatedTextAnalysis

• Theoreticallymotivated

• Hasbeenhistoricallyinformative

• Subjective

• Timeconsuming;notscalable

• Theoreticallymotivated

• Psychologicallyvalidated

• Objective, systematic,andquantitative

• Fast;scalable

• Enables realtimeadaptive,personalized feedbackforstudents

ModelsofDiscourseProcessing inPsychology� Construction-integrationmodel(Kintsch)� Structurebuildingframework(Gernsbacher)� Causalstructure(Trabasso,VandenBroek)� Landscapemodel(VandenBroek)� Constructionisttheory(Graesser,Singer,Trabasso)� Eventindexingmodel(Zwaan,Magliano,Graesser)� Memory-basedresonancemodel(Myers,O’Brien)� Embodiedcognition(Glenberg,Zwaan)

GenreandrhetoricalstructureSituationmodel• Causal,intentional,temporal,

spatiallogicalrelationships• ConnectivesTextbase• Explicitideas(propositions)• ReferentialcohesionSyntaxWords

Graesser&McNamara(2011).TopicsinCognitiveScience.

MultilevelTheoreticalFramework

Word

Syntax

ReferentialCohesion

SituationModel

Genre/topic

LanguageandDiscourseAnalysisToolsacrossLevels

Coh-Metrix

WordNet

MRCDatabase

Celex

LIWC

Sentiment

Abstractness

Coh-Metrix

PennTreebank

CharniakParser

Coh-Metrix

SourceRater

LSA

Coh-Metrix

Coh-Metrix

Biber

LDA-TopicModeling

Words

Syntax

Semantic/Sentences

DiscourseConnections

Genre/Topic

Pragmatic

LanguageandComprehension

Weleak…

Words

Syntax

Semantic/Sentences

DiscourseConnections

Genre/Topic

Pragmatic

Nonverbalbehavior

Cognitive,Affective,andSocialProcessesareConveyedacrossMultipleLevels

Overview

• Textanalytics:TheoryandApproaches

• Significantapplicationsinlearningsciences

• Movingforward

• Opendiscussion

Creation,Evaluation,Detection,&Prediction

EvaluatingTexts • Objectivemeasure textcharacteristicsthatcanbeused to

• Evaluatetextdifficulty ofstudentassignments

• Maketextmodifications tofacilitatelearning…adding surfacelevelindicators ofrelationsbetweenideas inthetexts(anaphoric referents,synonymous,connective ties, backgroundinformation)

• ReverseCohesion Effect

EvaluatingTexts:ReverseCohesionEffect

LowCohesionVersionHighCohesionVersion

McNamara,Kintsch,Songer,&Kintsch,1996

Computer-Mediated Learning

IntelligentTutoring Systems

MassiveOpenOnlineCourses

OnlineCollaborativeLearningandBlendedEnvironments

Theory+BigData+LearningAnalytics

Digitaltracesleftbylearners

Valuablelearningdynamics

Dede,2015

Emotions During Learning

EmotionSensorsandChannels

Dialogue

Face

Posture

Speech

ConversationalCues

• DialogueFeatures– StudentAnswerQuality– TutorFeedback– TutorDirectness– Cohesion– ResponseVerbosity

D’Mello,Dowell,&Graesser,2009

ClassificationAccuracy• Posture – Boredom(73%)andFlow(82%)• Face – Confusion(76%)andDelight(90%)• Dialogue – Frustration(78%)

D’Mello,Picard,&Graesser,2007

Computer-Mediated Collaborative Learning(CMCL)

Whatmakescollaborativelearningsuccessful?

Whatdoesitlooklike?

Whatarethemainfactorsthatinfluencecollaborativedynamics?

Aretheydifferentforindividualsandgroups?

Howdotheyevolveovertime?

Howcanwecreatealearningenvironmentthatcultivatesthosecollaborationskillsforstudents?

Cognitive,Affective,andSocialProcesses

Smallgroupsof3-5students

MOOCs

Dowell,Joksimović,Skrypnyk,et.al.,2015;Dowell,Cade,Tausczik,Pennebaker,&Graesser, 2014;Cade, Dowell, Tausczik,Pennebaker,&Graesser, 2014

MultilevelNatureofGroupProcesses

OverallGroupInteraction

IndividualLearner

Interactionsbetween individualsovertime

OverallGroupInteraction

IndividualLearner

GlobalDiscoursePatternsofSuccessfulCollaboration

Students’latentcognitive,andsocialprocessescanbemonitoredbyanalyzinglanguageanddiscourse

Discoursemechanismsofestablishing successful socialco-constructionofknowledgeappearstorelyonadeeper levelcohesionalignmentratherthanamoresurfacesemantic level

Moresophisticated naturallanguageprocessingvs.shallowmeasures likeparticipationmaybeneededtoimproveadaptiveCMCL

Unitofanalysis:Collaborativegroupsarenotthesumoftheirparts

CognitiveAffectiveSocial Learner

HolisticLearnerModeling

Monitoringcognitiveprocesses- tohelpunderstandtheirpriorknowledgeofdomain

Optimizinglearners’interactionswitheducationalmaterial– Scalingitfortheappropriatelevelofdifficulty

Optimizinglearners’socialinteractions- personalizedsuggestions

Monitoringstudentsaffectduringlearning– tofacilitateadaptivefeedback

Overview

• Textanalytics:TheoryandApproaches

• Significantapplicationsinlearningsciences

• Movingforward

• Opendiscussion

MainprogramsofresearchgoingforwardAholisticviewofcognitive,affective,andsocialprocesses:CombingdataanalyticstogaindeeperinsightsWe havehighlightedtherichcontextualinformationthatcanbegleanedfromcombingdeeperlevellinguisticanalysisandSocialNetworkAnalysis

Natural languageProcessing+ TopicModeling + SocialNetworkAnalysisBehavioralData+

MainprogramsofresearchgoingforwardBuildingonwhatweknow:Microdataanalyticsinthecontextofbigdatainonlineenvironments- re-conceptualizing“success”

Interactionsbetween individualsovertime

InternalCohesion

Responsiveness

SocialImpact

Newness

CommunicationDensity

IntersectionTheory+AdvancedLearningAnalytics+BigData

Wearehere