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Participatory Simulations: Building Collaborative Understanding through Immersive DynamicModelingAuthor(s): Vanessa ColellaReviewed work(s):Source: The Journal of the Learning Sciences, Vol. 9, No. 4 (2000), pp. 471-500Published by: Taylor & Francis, Ltd.Stable URL: http://www.jstor.org/stable/1466765 .

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THEJOURNAL FTHELEARNINGCIENCES,(4),471-500Copyright 2000,Lawrence rlbaum ssociates,nc.

Participatoryimulations: uildingCollaborativeUnderstandingThroughImmersiveDynamicModelingVanessaColella

MITMediaLaboratoryCambridge,MA

Thisarticle xplores newwayto helppeopleunderstandomplex,dynamic ys-tems.Participatoryimulationslungeearnersnto ife-sized, omputer-supportedsimulations,reating ewpathsoscientific nderstanding.y wearingmall, om-municatingomputersalledThinking ags, tudents re ransformedntoplayersna large-scalemicroworld.ikeclassicmicroworlds,articipatoryimulationsreateascenario,mediatedya setofunderlyingules,hat nablesnquiryndexperimen-tation. naddition,hesenewactivities llowstudentso"dive nto" learningnvi-ronment nddirectlyngagewith hecomplex ystem thand.Thisarticle escribesandanalyzes setof participatoryimulationshatwereconducted itha group fhighschoolbiology tudents. hestudents'xperiencesre rackedrom heir nitialencounter ithan mmersiveimulationhroughheir xplorationf thesystemandfinaldescriptionf itsunderlyingules.Thearticle xploresheeducationalotentialofparticipatoryimulations. heresults f thispilotstudy uggestanopportunityofurthernvestigateherolethatpersonalxperienceanplay ndevelopingnquiryskillsandscientific nderstanding.

Thestudents n a science classroomarechattering wayasthey playwith thelatestcomputer imulation.A virusis about o wipe out a smallcommunity.Will the in-habitantsdiscovera way to survive?A smallgroupof students n one cornerstareintentlyata computer,waitingfor theresults.As theywait, the virusmysteriouslyinfects a few "players" n theotherside of theclassroom.Shrieksechothrough heroomas each new set of redlights indicatesthat anotherplayerhas succumbed o

Correspondence ndrequests orreprints houldbe senttoVanessaColella,MIT MediaLaboratory,20 Ames Street,E15-120H Cambridge,MA 02139. E-mail:[email protected]

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472 COLELLAthedisease.Eachplayertruggleso evade hespreadingisease.Withoutwarning,red ightsemblazonhe wholepopulation.hediseasehasrun tscourse.

Thinkoramoment bouthe mage hat toryconjures pforyou.Ifyou pic-tured hisgameunfolding, oumighthavepictured roupsof students uddledarounda desktop computerplayingthe latest simulationgame-a sort of"SimVirus"rnewvirtualealityOutbreak.erhaps few studentsatcloseto themonitorwhileothersumped round ehindhemas theirplayersell ill.Perhapsfew fought orcontrolof the mouseas theytried n vain to savetheirplayer.Childrenlaying uchagamewouldobserveheresults n screenand hendecidehowtousethat nformationo better nderstandhe simulationmodel.Muchof our maginationbout owcomputersanbe used o enablenewkindsoflearningn thesciencessconstrainedytheboxandmonitormotifof thecom-puter.However,hegamedescribed bove s notplayedon acomputer,t eastnota traditionalomputer. hisarticleexploresparticipatoryimulations,n whichstudents ecomeplayersnunique,ife-sizedgames hataresupportedysmall,wearableomputers.Participatoryimulationsakethe simulation ff of thecomputercreenandbring t intotheexperientialorldof the learner. hestudents bovearenot ust

watchinghesimulation;naveryrealsense, heyare thesimulation. ywearingsmallcomputersalledThinkingTags,the students achbecomeagents n thesimulation. hestudents o not need o struggleokeeptrackof whichplayerssick,fortheflashing ed ightsbelong otheirclassmates. hequestionshat ol-low-Who gotthem ick?When?How?Why?-arenotmerelypartofexamininga computermodel; heyarepartof discoveringheunderlyingmysteries f theirveryownviralepidemic.Participatoryimulations uildonthe characteristicsfmicroworlds,n whichmodelscanbeexecuted, ndaugmenthemwith heaffordancesf realworld x-perience.Thesenewenvironmentsrea kindofrole-playingame hatcombinesthe immediacy f real-lifeadventure iththe consistent ulesandstructurefmicroworlds.articipantsxperience computer-supportedimulationf a sys-temand hencollaborativelyxploretsdynamics.nkeepingwith hecallsfor n-quiry-based cience, developingskills for systemsthinking,and fosteringcollaborativeearningnscienceclasses NationalCommitteen ScienceEduca-tionStandardsndAssessment, 996;Project 061, 1993), hisproject xploreshow earningakesplace ntheenvironmentreated yaparticipatoryimulation.

DESIGNINGEXPERIENCESThere is a long history of theoreticalclaims that children constructtheir ownknowledge through experience (Dewey, 1916, 1988; Montessori, 1912; Papert,1980; Tanner,1997). Manyeducatorshavetakenupthetaskof designingeducative

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UNDERSTANDINGTHROUGHDYNAMIC MODELING 473

experiences,often selecting or creatingparticularmaterials o enable an experi-ence. Whendevelopinghis conceptof kindergarten,FriedrichFroebelpioneeredthe ideathatparticular bjects,which hecalled"gifts,"couldbe giventochildren ostimulatecertainkinds of exploration.Heargued hatthesegiftswouldprovideex-periencesfor children hatwould likely lead to certainkindsof cognitivedevelop-ment(Brosterman,1997).1Muchof his notion of kindergartenocusedon how theorderlydeliveryof thegiftswould enablechildren obuildknowledge n acoherentfashion. Years later, Vygotsky wrote extensively on the notion that tools (likeFroebel'sgifts) couldenrichandbroadenboththescopeof activityandthescopeofthinkingof the child (Vygotsky, 1978). Otherresearchershave even speculatedabout the ways in which the objects present n the environment ould actuallyin-duce development(Fischer, 1980).2

Computers it rightinto this lineage. Even before the prevalenceof personalcomputers,Seymour Papertenvisioned a futurein which computer-based oolswouldprovidechildrenwith awhole rangeof transformative evelopmentalexpe-riences(Papert,1980).He imagined hatconstructionswithin thesepowerfulcom-puting engines would become fodder for children's imaginativeand intellectualruminations,much like gears (his own childhoodtool) hadbecome for him. Thefact thatcomputerscould take on so many differentroles, potentiallya role perchild, was especially exciting.Much effort has been expendedto build computational ools thatprovideop-portunities or childrento engage in experiencesthat would not be accessible tochildrenwithout those tools (Resnick et al., 1998). Virtual communities offerplaces for children to construct alternate realities (Bruckman, 1998); com-puter-basedmodeling environmentsenable the design and constructionof com-plex papersculptures Eisenberg& Eisenberg,1998); microcomputer-basedabsfacilitate children's collection of scientific data (Tinker, 1996); and Newto-nian-basedenvironmentsallow explorationof the laws of physics (White, 1993).Each of these computerizedtools supportsexploration, investigation, or cre-ation-activities central to an educativeexperience.The next section describesmicroworlds, hecomputer-basedools thatprovided heconceptualandcomputa-tional frameworks or the developmentof a new class of educationalexperiencescalled participatory imulations.A Computational Sandbox"Microworldswere originallyconceived to give childrena sortof computationalsandbox-a worldin whichtheycouldmanipulateobjectson thecomputer creen.

'See also Lillard(1972) forrelatedwork.2For anotherperspectiveon the importanceof tools in the developmentof understanding,ee Nor-man(1993).

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474 COLELLA

Ina realsandbox,childrenuse buckets,shovels, andsandto createminiaturecas-tles. While creatingthese sandcastles,childrenoften grapplewith concepts likeshape and scale. What base supports he tallest sandcastle?How big shouldtwopebblesbe if they aremeantto representa princeanda princess?A computerizedsandboxoffers morethanjust a sandbox on a screen.In a microworld-as in therealworld-a childcan takeactions thathave discernibleeffects on the world.Butinamicroworld, hechild alsohas someaccess to the formalrulesthatgovernhisorheractions.Microworldsoffer anonformal ntry nto aworldbasedonformal, og-ical constructs.

Picture a girl playing with a toy horse in her room. She can move the horsearoundandeven have it "talk" o otheranimals n the barnyard.The horsemight"gallop"and"trot" s she alters hespeedwith which she flies the horsearoundherplay space.Ina microworld,her horsecould still move around n space, talkingtootheranimals,but she mightbeginto investigate hemathematical elationshipbe-tween the horse's two speeds.Dependingon the microworld, he computermighteven showheranequation hatrelates hosespeeds.Or she could makethe gallop-ing speed dependenton the trotting speed. Certainly,she could performsimilarmentaloperations n the real world, but the microworldcan provide a seamlesstransition rom thenonformal,naive operations n the real worldto the formalde-scriptionsand investigationsof those operations n the microworld.In fact, re-search has suggestedthat microworldswhose formaldescriptionsclosely mirrorchildren'sexperiencewith patternsandactivities can be better earningenviron-ments (diSessa, 1988).Mostoften,amicroworld ocuses on a specific set of formalrules,constrainingthe types of actions a child can take but providingan opportunity o learn moreabout the rules governing those actions. Roschelle (1996) describes one suchlearningactivity, duringwhich two girls build up an understanding f the Envi-sioningMachine,a microworld hat facilitatesexplorationof velocity and acceler-ation. Like many microworlds, the Envisioning Machine provides "anintermediateevel of abstraction romthe literalfeaturesof thephysicalworld" p.241). The computerbecomes a bridge linking the patternsand activities in themicroworld inthis case,motionof a ball orparticle)with the formalexpressionofthose patternsand activities (arrowsrepresentingvelocity and acceleration)byconnecting patternand activity to representationsof the underlying processes.This bridgeenableschildrento interactwith boththe processesandpatterns heyobserveandtheformalsystemsthatgovernthose patternsandprocesses.As muchasFroebel'sgifts facilitatedspecificactivitiesand, n so doing,helpedchildrende-velop new understandings,microworldscan broadenthe rangeof activities andthoughtsin which childrencan engage.

Benefitsof microworlds. Teaching ften nvolvescreating ndorganizingspecial experiences to help children learn certain ideas. The flexibility of

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UNDERSTANDINGTHROUGHDYNAMICMODELING 475

microworldenvironmentsopensup the rangeof possible experiencesthat can becreated.Someresearchers aveclaimedthat"thecomputer s ... moreflexible andpreciseincraftingexperiences hatcan lead to essential nsights" diSessa, 1986,p.224). Teachersandresearchershave constructedmicroworlds hat makepossiblecountlessexperiences,fromexploringgeometricrelationships o building nterac-tive riverecosystems.Forexample,differentmicroworldsenable children o focusanexplorationonparticular spectsof physics (The EnvisioningMachine),mathe-matics(Logo), orpolitics (SimCity).One class of microworlds hatenable focusedexplorationof complex,dynamicsystems,hasgainedmainstream opularitynthepast few years. Game software like SimCity (1993) and SimLife (1992) helpedgeneratepopular nterestin complex systems. Programs ike Model-It (Jackson,Stratford,Krajcik,& Soloway, 1994), Stella (Roberts,Anderson, Deal, Garet,&Shaffer, 1983), StarLogo (Resnick, 1994), and Sugarscape(Epstein & Axtell,1996) enable users to experimentwith complex systems anddevelop better intu-itions about the mechanismsthatgoverndynamicinteractions.Microworldslet childrenexperimentwith real concepts in play space, or asPufall (1988) said, they create "a context within which children can thinkaboutdiscretespaceas real andnotaboutdiscretespaceas an abstractionfromthe ana-logue worlds of sensory-motorexperience"(p. 29). With microworlds, earningexperiencesareno longerconstrainedby what the real worldhas to offer. We canboth limit andaugmentthe real world, sometimes creating simplified spaces forexploringcomplextopics, other imescreatingwholly new experienceson-screen.Pufall (1988) furtherspeculatedthat the new interactionsmicroworldsenablemight"alter children's]patternsof developmentby allowing [them]to interact nways [they]cannotinteractwith the 'real'world"(p. 21).

Buildingon microworlds. Microworldsntroduced anybenefitsor earn-ing and presentedsome new challenges as well. Withouttryingto exhaustivelycover thebenefits of learning nthephysicalworld, t is worthmentioning hat herearehumanties to interactions n realspacethatare lost in cyberleamrning.houghsome usersbecome enamoredof the machine(Turkle, 1984),othersfeel distancedfrom thepatternsandprocessestheyobserve on a computer creen. Forsomepeo-ple, this distanceleads to a generaldistastefor the "cold,"unemotionalworld ofcomputing Turkle& Papert,1992).Othersare inclined to believe everything heysee on acomputer,notquestioning hevalidityorappropriatenessf simulationre-sults.SociologistPaulStarr 1994) witnessed oneuser's lack of intellectualcurios-ity about the underpinningsof SimCityand anothergroup's disinterest n rigor-ously questioning the assumptions underlying a computermodel designed toforecast futurehealth care costs. In SimCity,the underpinningsof the model arehidden from the user,perhapsstiflingcuriosity.Butthe assumptions n the healthcaremodel werereadilyaccessible,suggesting hatdevelopinga fullunderstandingof a computermodel is a formidable ask.

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As much researchon microworldshas shown, these challenges are not insur-mountable.Many microworldenvironmentsengage studentsin deep reasoningand sophisticatedanalysis (e.g., Eylon, Ronen, & Ganiel, 1996; Goldman,1996;Papert, 1980; Roschelle & Teasley, 1995; Rothberg & Awerbuch, 1994;Schoenfeld, 1990;Tabak& Reiser, 1997;White, 1993).Microworldsenable a di-verse set of experiences,encouragingchildren o broaden he scope of their intel-lectual investigations.Effective microworldsdon't turn learners'"experience[s]intoabstractions. Instead, heyturn]abstractions,ikethelaws of physics, into ex-perience"(diSessa, 1986, p. 212). By actualizing hese experiences,microworldsenable learners o directlyexperiencesimulations.Or moreprecisely,they enableusersto enjoy experienceswiththose simulations hatareas directas we canmakethem (diSessa, 1986).Inthepast,direct nteractionwith a simulatedenvironmentmeantmanipulatingagents or parametersn a microworldor controllingan avatar n a virtualworld.New technology allows us recast the notion of "directly"interactingwith acomputationally imulatedexperience.We cannow deploysimulations n therealworld, facilitatinga morepersonalexperiencefor learners.Our aim is that ust asmicroworldshavegreatlyenhanced helearningexperiencesavailableto students,participatory imulationswill provideanother angeof learningexperiences,uponwhich studentsandteacherscan draw.

Anotherwayto learnfromexperience. Participatoryimulationsacili-tateanotherway forlearners o collaborativelynvestigate herelationshipbetweenpatternsandprocessesinthe world and the rules thatgive rise to thosepatternsandprocesses.Participatoryimulationsbuild on thecharacteristics f microworlds, nwhich models can be executed, and augmentthem with the affordancesof realworld experience,enablinglearners o become the participantsn computer-sup-portedsimulationsof dynamicsystemsin realspace.Small,distributed omputerscreatea life-sized microworldby deployingconsistent,computational ulesinrealspace.Learners anexperienceand nfluencethis simulationdirectly.Thisinterac-tion,thoughstillmediatedbytechnology, s qualitativelydifferent romother ech-nology-controlledrole-playinggamesthatfacilitate nteraction hroughavatarsorwith thecomponentsof amicroworld.Participants' ersonalconnections o the ed-ucationalsituationenable them to bringtheirprevious experiencesto bearduringthe activity,establishstrongconnectionsto the activityand the otherparticipants,and,we hope, drawupontheirexperiencein the future.ParticipatoryctivitiesThe ParticipatorySimulationsProject nvestigateshow direct,personalparticipa-tion in a simulation eadsto a richlearningexperiencethat enables students o ex-plore the underlyingstructureof the simulation.The idea to use direct,personal

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participationo helpchildren or learners)gaina new perspectiveor build a betterunderstandings not a newone.Dewey emphasized hevalueof personalparticipa-tion ineducativeexperiences hroughouthe curriculum.nthe socialsciences,per-spective-takingactivities are quite common (Seidner, 1975). Studentsmight beaskedto take ontherole of communityactivistsorpoliticiansandsimulatea debateon thefutureof theloggingindustry.Thisdebategives theparticipants waytorep-resentthecharacters nd hinkabouthowthe variouscharactersmightfeel aboutanissue.

Activities like these areless common in the sciences,where the mechanisms obe studiedarenothuman eelings andbehaviorbutconceptslikeplanetarymotionormolecular nteractions.Nonetheless,studentssometimestake on those kinds ofroles as well, perhapspretending o be planets in orbit, in an effort to illustratethose phenomena.However, these activities are very different from their socialscience counterparts.Although hesocial science activitiesmight helpthe studentsto thinkabouthow a politician,for instance,would feel and behave under certaincircumstances, he science activities don'tnecessarilyhelp students o thinkaboutthe underlyingmechanisms of processes like planetarymotion. Role-playingac-tivities attemptto createlinks between personal experienceand a deeperunder-standingof why thatexperiencehappened,yet the science-based activities oftenend up being little morethanlarge-scaleillustrations.Researchershave attempted o connect personaland physical interactions ounderlying(nonhuman)mechanisms in a varietyof ways. Papert(1980) triedtoforge linksbetweenhumanactionand therules of TurtleGeometryby askingchil-dren to pretendthey were the turtleand then translate hatunderstandingnto asymbolicrepresentation f the instructions orthe turtle'smovement.Resnick andWilensky (1998) expandedonthis idea,involving large groupsof people in activi-ties to help themgain a richerunderstanding f the rulesgoverning emergentsys-tems.Recently,WilenskyandStroup 1999) developeda networkarchitecturehatgives studentscontrol over individualagents in a simulation environment.Re-searchers n systems dynamicsalso use groupactivities to help learnersdevelopsystems thinking capabilities (Booth Sweeney & Meadows, 1995, 1996;Meadows, 1986; Senge, Roberts,Ross, Smith, & Kleiner, 1994). Participatorysimulationsbuild on microworldsandthese groupactivities,usingwearablecom-puters o createan explicit linkbetweenpersonalexperience n realspaceand theunderlyingrulesthatmediatethose experiences(Colella, 1998; Colella,Borovoy,& Resnick, 1998).

THEPARTICIPATORYIMULATIONSROJECTTheParticipatory imulationsProject ooksspecificallyat howa new kind of learn-ing environmentcan motivatelearners, acilitate dataanalysis,collaborative he-ory-buildingandexperimentaldesign,andlead to a richerunderstanding f scien-

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tific phenomenaandtheprocessesof scientificinvestigation.By involvinga largenumberof students n a physical experienceof a simulation,the projectbringsamicroworldoff the computer creen and into the participants' pace.Ouraim is toestablishwhether,and if so how, participationn these activitiespromotes he de-velopmentof both the motivationandabilityto engage in scientificthinking.TheParticipatory imulationsProject s anextendedresearchendeavor,study-ing how personalexplorationof life-sized, computer-supportedimulations canhelpparticipants evelop inquiryskills andscientificunderstanding.Thousandsofpeoplehaveparticipatedn variousactivitiesat schools, in workshops,and atcon-ferences.Ineachactivity,peopleuse small,wearablecomputers o become agentsin the simulation.Forinstance,during he pond ecology simulationsome partici-pantsbecome schools of"big fish,"andothersbecome schools of"little fish."Asthey interactwith one another, hebig fish "eat" ittle fish, and the little fish "eat"fish food. The Tags keep trackof the numberof fish in each school. Participantscollaboratively nvestigatethe ways in whichcooperativeandcompetitivebehav-iors alterthe dynamicsof the ecological systemandchangethe carryingcapacityof the pond. Similarly, he tit-for-tatgameallows participantso experiencegametheory from a first-personperspective. Together,they can explorehow coopera-tive behaviorsevolve over time. In the virusactivitydescribed n this article,par-ticipants nteractas a diseasemoves through heircommunity.Thegroupworks toanalyzethe disease dynamicsandestablishhow the behaviorof individuals nflu-ences the outcome of the simulation. nall of theseparticipatoryimulations,peo-ple collaborativelyexplorethe system by changingtheirown behavior,collectingdata,runningexperiments,andobserving he effect thattheirbehaviorhas on thedynamicsof the system.Technological upportWeuse small,wearablecomputers alledThinkingTagsto enable directparticipa-tion in the simulation.The Tags collect information orthe participants like howmanyotherplayers heyhavemet)andhelpthemto interprethe stateof otherplay-ers(e.g., whethersomeone is "sick"or"healthy").Unlike the traditionalnotion ofwearablecomputing,whichfocusesonconnectinguserstoanexternalnetwork ikethe Web, the Tags connect all of the participants n their own discretenetwork,which facilitates nteruser onnectivityandprovides hecomputational upport orthe simulation.Rather han ust transforminghe experienceof anindividual,par-ticipatorysimulationstransform he interactionsamong people by linking themthroughapersonalizednetworkof communicating omputers.Participants ecomeplayersin acomputationallymediatedsystem comprisedof peopleandtheirsmall,personalcomputers.

Participatoryimulationsaresupported y avariationof theThinkingTagtech-nology developed at the Media Lab (Borovoy, McDonald, Martin,& Resnick,

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1996).TheTagsareused to transform achparticipantntoan"agent"n a simula-tion of a dynamicsystem.Inthese decentralized imulations,no one Tagacts as aserver,andno large (traditional) omputer s necessaryto run,experimentwith,oranalyzethe system.We developeda new versionof the ThinkingTags3to facili-tatecollaborativeanalysisof manyiterationsof the simulation.As in the originalThinkingTagdesign,we tookcareto ensure hatthe enhanced nformationdisplaywould not interfere with participants' social interactions (Borovoy, Martin,Resnick, & Silverman, 1998; Borovoy et al., 1996; Ishii, Kobayashi,& Arita,1994; Ishii & Ullmer, 1997).Like the originalThinkingTags,theTagsbuilt forparticipatoryimulationsarecomplete,albeitminiature,computerswith inputandoutputdevices anddisplaysforthe user. EachTag possesses aninfrared ransmitter ndreceiver,allowingit todynamicallyexchange informationwith all otherTags in the simulation.As thesimulationis running,the Tags are constantly exchanginginformationvia infra-red,thoughthis exchangeis invisible to the participants.The Tags have two dis-play devices, a double-digitnumberpad and five bicolor LEDs (see Figure 1).Duringthe simulation, heinformationdisplayedon theTags changes,andpartici-pants watch the Tags to discover informationabout themselves and aboutotherplayers.A resistive sensorport acts as an inputdevice, allowing users to attachsmalltools to theirTags andenablingthem to "dial-in" nformationor changetheprogram heirTag is running.This carefullychosen set of inputsandoutputspro-vides arich setof userinteractions,bothduring he simulationandduring he sub-sequentanalysis.ParticipantsThe 3-week-long pilot ParticipatorySimulationsStudy describedin this articletookplacein anurbanpublichighschoolclassroom.All of the studentsvolunteeredfor the projectand were told thatthey would be participatingn a projectto learnaboutdynamicsystemsin science.Classtime for5 daysovera 3-weekperiodwasdevotedto activitiesassociatedwith the Participatory imulationsStudy.The chosen Biology class consistedmainly of 10th-grade tudentswho weredescribedby theirteacherastraditionallypoorperformersn scienceclass. Sixteenstudents-7 girls and9 boys-participated in the study.The teacher also partici-patedin the activities,and on Day 4, a student eacherobservedthe class andpar-ticipated n the activities. The researcherauthor)was the facilitatorof the classes.In addition, wo studentsvideotaped he activities.4

3Special hanksto Kwin Kramer ordesigningandbuildingthis version of the ThinkingTags.4One studentwas a memberof theBiology class whopreferredo not be filmed forreligiousreasonsandthe otherwas a classmatefroma differentbiology class.

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FIGURE TwovirusTags.The opTaghasmet wopeople nd snotsick.ThebottomTaghasmetsixpeopleand s sick,asindicatedythefive redLEDs.ActivitiesAside froma very brief introduction o the researcherandthe basic operationsofthe Tags,the students'firstexperience n theParticipatory imulationsStudywasplayinga disease simulationgame.The contextwas set forthe first simulationbygivingthe studentsachallenge: omeet asmany peopleaspossiblewithoutgettingsick.Theyweretold thatone of theTagscontaineda virus andthat heycouldelectto stopmeetingpeople anytime heywantedsimply by turning heirTagaround oface theirstomachs orturning toff) andsittingdown.The studentswere told noth-ing about how the virus moved from one Tag to another,nor were they told any-thingabout the degreeof contagiousness, he possibility for latency,or any otherunderlyingrulethat could affectthe spreadof the disease, leavingthemin an am-biguous situation.None of the students'questionsaboutthe behaviorof the viruswereanswered.Instead, heyweregiventheopportunityo experienceandexplorethe disease simulationforthemselves.The studentsparticipatedor 45 to 55 min on each of 4 days andfor90 min onthe lastday.Theprojecthadthreephases.On thefirstday(Phase 1), studentswere

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introducedo theresearcher ndto afew otherexamplesof technologythatoperateon thesamegeneralprinciplesastheTags (Resnicketal., 1998).OnDays2, 3, and4 (Phase2), studentsparticipatedn diseasesimulations,orgames,andin analysesof those simulations.Thisphasehad threedistinctcomponents: he initialdiseasesimulation, he discussion of thatsimulation,andthe developmentandexecutionof experiments o test hypothesesabout that simulation.The studentscompletedsix diseasegamesoverthecourse of the3 days,withthe discoveriesfrom one sim-ulationleadingto the design of the next.Finally,on Day 5 (Phase3), studentsre-flected on their experiencesin the ParticipatorySimulationsStudyand asked toparticipate n one final simulationgame.TheDiseaseSimulationThroughout hispilot study,theunderlyingrulesof the simulation5werekeptcon-stant. The rules of the disease simulationwere as follows:

* The virus was latent(invisible) for approximately3 min.* Any personwhose Taghad thevirus,even if it was notvisible, could infectanotherperson'sTag.* The probability or infectionwhen meetingan infectedTagwas 100%.* PeoplewithTagsnumbered1or2 inthe onesposition(1,2, 11, 12, 21, etc.)were immuneto the virus.* ImmuneTags were not carriersof the disease.Duringthe simulation,the numberpad displayedthe numberof differentpeoplewithwhomeachparticipant adinteracted, ndthefive LEDsflashedred when theTagwas sick. TheTagsalso tracked nformation hattheparticipants ould accessafter hesimulation, ncluding he IDnumbersof all of the individualswithwhomaperson nteracted, he time of all interactions,and the ID numberof the individualresponsible for infection. Duringthe study reported n this article, students ac-cessed the storeddataonly to confirmtheirfinalhypotheses.In some of ourotherparticipatoryimulationsprojects, his datahas beenaggregated,displayed hroughStarLogo,and used formorein-depthanalysesof disease transmission.DataCollectionBringing new computational ools into a classroom can fundamentallyalter thestructure f the class's interactions.Theunit of analysisin theParticipatory imu-

5Since heTagsarefullyprogrammable,hese rules can be modifiedorcompletelychanged ora dif-ferentparticipatoryimulation.Forexample,somediseasesimulations onsist of a virus andanotherop-portunistic nfection. Othersimulationsdiffermoresubstantially,ike ourpond ecology gameinwhichparticipantsmodel predator-preynteractions.

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lationsStudywas not the individualchildnortheindividualchildplusthetool, butthe whole cognitive system in the classroom(Newman, 1990; Salomon, 1993).Newman defines the cognitive system as follows:

The eacherreates social ystemntheclassroomhat upportsertain inds f dis-courseandactivities;tudents ollaborate ithin hesystem, ontributingbserva-tions,answers, ndconcrete roductsuchastexts,projects,nddata.Thecognitivesystemncludesheexternalizedools, exts,data, nddiscourse,ll of which spro-ducedbyand ortheactivities.p. 187)During heParticipatory imulationsStudy,attentionwaspaidto how allaspectsofthe learningenvironment thegroupof students, heirconversations,and the toolsthey employed)contribute o buildingscientificunderstanding.Thisstudyanalyzedconversationsandexplicitcollaborativediscussionsduringtheactivities.The mainsourceof data ortheParticipatory imulationsStudywas acompletevideotape og of the sessionsthat, nparticular, imedtocaptureall of thewhole-groupconversations. naddition,audiotapebackupswere madeof everyses-sion,andfacilitator ogs werekept throughoutheproject.Studentswereoccasion-ally askedto writedown their deasabout he simulationdynamics,and all of thosestudent esponseswerekept.Weexamined hedata o findevidenceof ourfourmainaims:During heactivities,were students ngaged nthesimulation?Couldstudentsidentifyandanalyzeevidence from he simulation?Were heyable todesign experi-ments,predictoutcomes,and runexperiments o confirmordenytheir deas?Didstudentscarryout theirinvestigations n a scientific manner?

ANALYSISOF CLASSROOMACTIVITIESEngagementinthe SimulationIn the participatory imulationsProject,we aimed to motivate studentsby givingthema realexperiencethatwas mediatedby a set of underlying ormalrules.Onemeasure of success of a participatory imulation, hen, is the extent to which stu-dents felt as though they actually experiencedthe simulation.In this case, wejudgedthe experientialqualityof the simulationby observingthe extentto whichstudentssuspended heirdisbeliefandacted as thoughtheywerein the midst of anepidemic striking he membersof their small community.The following episode depictssome of the excitementand tension thatperme-atedthe learningenvironment:Episode 1Researcher: I got it from her.Student: You all got the virus!

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Stacy: I'm dead.Doug: (to Tony) Oh,you got the virusnow.Tony: (looking at Tag) You got it started.Rick: (singing) I ain't got the virus.Student: I'm healthy.Meredith: (holdingTagup) I don'thave the virus.Researcher: Who in this room met the most people?Chorus

of students: have 14,I got 16,I got 13 with novirus,metoo, Igot 14withno virus.Student: I need some medicine.

Studentsdisplayeda robust andpersistentwillingness to suspendtheir disbeliefandbehave as thoughthe simulationactivitywas real.The learningenvironmentpromotedastrongconnectionbetweenthe studentsandthe simulation.WhenStacyexclaimedthat shewas "dead," hewas nottalkingaboutan externalagentor ava-tar-she was talkingaboutherself in the simulation. Similarreferencesoccurredthroughout he study,as when a studentdeclared hat he neededmedicine.This level of engagementpermeated he next 4 days of the project.As eachgame unfolded,the studentsonce againhad a real-lifeexperienceof an epidemicinvadingtheir small community.Their task was not to mentallyconstruct he dy-namics of an epidemic from a writtendescriptionor a set of equations.Instead,they needed to figure out what was happening n their community.The activity"arousedcuriosity,strengthenednitiative,andsetup desiresandpurposes" n thestudents,propellingthemto develop anunderstanding f the simulationenviron-ment(Dewey, 1988,p. 20). Thiscompelling, nterpersonal xperience s one of thekey componentsof the participatory imulationand set the stage for the learningactivitiesthatfollowed.Thoughengagement n the immersiveexperienceis an integralandimportantcomponentof participatoryimulations, heimmersivecomponentperse does notdetermine he activity's educationalvalue. The experience's potentialfor leadingto growthrestson its abilityto allow the students o problematize heir ndetermi-nate situation(andlater to inquire nto its underlyingstructure). n this case con-siderable learning occurred as students were able to step back from theirimmediateexperienceandanalyzethesituation.Ackermann 1996) described hisprocess as "diving-in"and "stepping-out" s studentsmove back and forth be-tween full immersion in a problem and thinking about a problem. Similarly,Sterman 1994) distinguishedbetween the featuresof learningin and aboutdy-namic systems.6Many scientific problemsoffer the chance to step outsideof theproblemandthinkclearlyabout t. Fewproblems hatareappropriateorstudyat a

6Seealso diSessa (1986).

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high school level offer the chance to dive so convincinglyinto a problem.Partici-patorysimulationscreatea unique opportunityor students o enjoybothof theseimportantperspectives during heprocessesof definingandsolving problems.The notion of divinginto a scientificproblem o betterunderstandt hasnotal-ways been highly valuedby researchers.The scientific communityhas tradition-ally valueddetached,objectivemodes of experimentation t the expense of more"connected"methods;however, some examples from scientific practice ndicatethata revaluationof connectedsciencemaybe in order.7participatoryimulationscanbringconnectedscience to the classroomwithoutforcingstudents o abandonthe explorationof scientifically importantproblems.As studentscollected dataand designed experiments,they remained n touch with the problemat hand. Anontrivialcharacteristicof the participatory imulationsenvironmentmade thisconnectionpossible-the studentswere collecting dataaboutandexperimentingon their own behavior.IdentificationndAnalysis f EvidenceLikemanymicroworlddesigners,we wantedto createa learningenvironment hatenabled students o defineproblemsand construct establehypotheses.Inorder obegin the process of formally analyzingtheir simulation,the studentsneeded toidentifyandanalyzeevidence tohelpthemarticulate tractableproblemandbeginto hypothesizeabout ts structure. n this section,we describea few representativeinstances n whichthey extracteddatafromthe simulationsandanalyzedthatdatato betterframethe problemathand.At the close of the firstsimulation, herewas no clearlydefinedproblem orthestudents o explore,butthey were certainly n a problematic ituation.Almost allof the students n theclassweresick-a surprising utcomeformanyof thepartic-ipantswho thoughtthatthey had avoided the virus.The facilitatorasked if therewas anyonein the class who managednotto get sick.The studentsbegancompar-ing notes in an attempt o explainthe outcomeof the simulation.First the students accumulateddata,and then they began to make assertionsbased on the available information.Some of the students'initial assertionswerehypotheses about why something happened,some were suggestions about howthey could proveor disprovea particularhypothesis,andotherswere ideas aboutwhatproblemthey should be investigating n the firstplace. Studentsofferedsup-portingevidence for or contradictory vidence againstmany of these assertions.As the available evidence accumulatedand ideas proliferated, he potential forconstructing establehypothesesaboutthe viralbehaviorgrew.

7SeeKeller 1983) foranexampleof howdivinginto aproblemcanyield innovativeandpreviouslyunimagined olutionsto scientificquestionsandWilensky(1993, inpress)fordiscussionsof connectedmathematicsandscience.

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Inthe following episode, studentswerepresenting heirpieces of datafrom thesimulation.Notice thatdatain a participatory imulation arereally observationsabout a student'sbehavioror stateduringor afterthe game.Episode2Rick: We should all meet eachother.Joan: I met Doug like 2 minutesbeforehe gave the virusto other

people andI didn'tget sick.Allison: How do you clear these?Student: I need a medicine,I need an antibiotic.Researcher: Is thereanyonewho startedwith the virusother hanthis guyin the front?Rick: Doug. (Supplyingthe nameof the guy in front)Allison: That'sjust 'cause Doug's dirty.Joan: Doug didn't startoff with the virus.Researcher: Who startedoutwith the virus?Allison: 'Cause I met him, I met him.Joan: 'Cause I met Doug andI didn'tget the virus.Allison: Doug was the secondpersonI met.Doug: I ... I met herandthen,Ijust, the virus wasjust like pop.Allison: I didn'tget the virus until I got it fromsomebodyelse.

Heredatawas presented some of it before this episodebegan)thatculminated nthenotionthatDoughad nfectedalotof people.Butthe students'suggestionswerenotespecially focusedonrunningexperimentsortesting hypotheses.Whenthe re-searcher estated hequestion"Whostartedoutwith the virus?" he studentscontin-ued offeringsuggestionsand ideas but did not responddirectlyto the question.A laterepisoderevealed he students'morestructured ttemptsotestthevalidityofthepropositionthat personcouldbeinfectedbythelastpersonheorshemet:

Episode3Liz: All right,I'm all set; I'm not meetingnobody else.Liz: I'm sick.Rick: Oh, Ijust boot beeped8her.Stacy: Liz's the firstone. Liz's the first one to get sick!Stacy: Who'd you sharewith?9Do you remember?Allison: (Whilewritingon theboard)Wait,who was the last one yousharedwith?

8Because heTagsmake atiny"beep" ach timetheyinteractwith anotherTag,some studentsbegandescribingameetingas"beeping"or "bootbeeping."Thislanguagewas lacedwithinnuendoabout hetype of interaction hatstudents elt the Tagswere simulating.9"Sharingwith" is anotherway that students alk aboutmeetingone another.

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Liz: Rick.Allison: Wait,you gotta go in order.Stacy: OK,lookat,Doug,Rick was the lastpersonshe sharedwith.Liz: It's Rick's fault, it's all Rick's fault.Stacy: No 'cause I sharedwith Rick.Liz: I sharedwith Rick too.

As students described their observations, like, "Rick was the last person shesharedwith," others respondedeither with data from their own experience orwith hypotheses that could provide an interpretive rame for the previous data.For instance,Liz hypothesizedthat "it's all Rick's fault" aftera number of ob-servations that sick people had recently shared with Rick. This interpretiveframe turnedout to be inadequateto explain everyone's experience. Two stu-dentsquicklyrebuttedLiz's hypothesiswith observations hatthey had eachmetRick and were not yet sick.At this point, studentsconvergedon a few problematic ssues in their situationthatthey wanted to solve, including discoveringthe identityof PatientZero(thepersonwho startedoutwiththevirus)anddescribing heway thatthevirusmovedfrom one personto another.Theirearlier, ll-structuredpresentationof evidencefragmentsgave way to a moresystematiccollectionof evidence thatcouldsuggestwhich hypotheseswarrant urthernvestigation.Theparticipatoryimulationpro-vided a settingfor the students o engagein inquiry.Theirpatternof inquiry s con-sistent with the notion that ideas leadto moredirectedobservation,which in turnbrings new facts to light and suggests fruitful directions to pursue (Dewey,1938/1998).

ExperimentalesignandExecutionIn addition to enabling students to identify problemsand constructhypotheses,we designedthe participatory imulationsenvironment o facilitateexperimentaldesign andexecution. Studentsexplorethe underlyingrules of the simulationbyalteringtheirown behaviors andobservingthe effects of those alterationson thedynamicsandoutcome of the simulation.Like scientistsprobinga new domain,the studentsprogressively develop a keenersense of the kinds of outcomestheycan produceandbegin to proposemore specific actions thatthey feel will shedsome light on the disease dynamics. Their "observationof facts and suggestedmeanings or ideas arise and develop in correspondencewith each other. Themore facts of the case [that]come to light in consequenceof being subjectedtoobservation,the clearer and more pertinentbecome the conceptionsof the waythe problemconstitutedby these facts is to be dealtwith"(Dewey, 1938/1998, p.173). Their suggestions become ideas that, when examined in referenceto the

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situation,engenderthe capacityto predictand test solutionsto theirproblematicsituation.This sectiondescribes he students'experimentaldesignand execution n apar-ticipatory imulation.Justastheirdescriptionsof theexperimental tateduring hedata collection phase were about their own state, their experimentaldesign in-volves varyingtheirown behavioralpatterns o elucidatethe viraldynamics.Stu-dents offeredideas abouthow they could use variations n their own behaviortodiscoverpatterns n the viral behavior. As the experimentingproceededandhy-potheseswere refined,the students mproved heirabilityto predictthe viralout-come based on a certainset of (experimentallyconfigured)behaviors.Through

experimentingandcollecting additionaldata aboutthe relationshipbetweentheirownbehaviorandthe behaviorof thevirus(by conductingadditional imulations),theywereeventuallyableto statethe rulesthatgoverntheviral behavior.Thispro-cess is a formof scientificexperimentation,n which a systemis probedundervar-ious conditions to reveal the underlying processes that govern the system'sbehavior.During Episode2, Rickproposedanexperiment o figureoutwhy some peopledidn'tget sick whenhe exclaimed,"Weshouldall meet each other."At thattime,his proposalwas ignoredby most of his classmates,as there was no communityagreementonwhataspectof theproblematic ituationwas under nvestigation.Astheirinvestigationmoved forward,students'propositionsfor a varietyof experi-ments to reveal the underlyingdynamicsof viral transmissionbecame more fre-quentandfocused.

Episode4Researcher: Do you have a strategy o avoid that[thevirus]?Allison: Stay away frompeople.Student: But you don't know who.Allison: That'swhat makesit confusing.Rick: Iknowhowwe couldgetit,everyone urnon thembadgesand

just turn em aroundandthen whoeverhasthe uh,whoever'sthing lights up first.Doug: How 'bout all the people, each one [has a] partner,and thenonly meet with one personand whoevergets sick.Rick: Everyone urn heirbadgearound o noone can communicatewith them and whoever's thing turnsred first.Doug: But can't the hostnotget sick, like thepersonwho has thevi-rus his buttonswon't get red buthe couldgive it to someoneelse?Yeah,we couldpick groups, ikeum,theycommunicatewitheachother, heycommunicatewith twopeopleand f they getsick thenthese arethe people who have the virus.

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Stacy: Go around heroomagain ikewe didbefore andthen as soonas your thingturnscolor, like, yell, out,you know what I'msaying,when it turnscolor,tryto seewho was the firstperson.And then we couldrecord, ike, who we sharedwith.

In this episode, a number of students described possible experimentalproto-cols. Rick wanted everyone to avoid meeting otherpeople to determinewhoseTag showed viral symptoms (lit up) first. He felt that his plan would help de-termine the identity of Patient Zero (the initial host). Doug was concernedthatRick's plan did not control for the possibility that Patient Zero could just be acarrier and never display the symptoms of the virus. Stacy wanted to run anunconstrainedsimulation and watch for the first appearanceof viral symptoms.Over time, many studentsproposed experiments,and the groupdecided whichones they wanted to conduct, often based on a comparisonbetween the datathat the experimentwas expected to produceand the currentlyavailable facts.Because there is a high level of iterativityand flexibility in participatory imu-lations, it was easy to accommodate as many experiments as the studentswanted to run.The students n the studyexhibiteda remarkableevel of prideandownershipabout theirproposedexperiments.All studentspossessed the abilityto articulateexperiments,which, afterall, were really prescriptions or alteringtheirown be-havior in a way thatthey felt would illuminate he rulesof the virus.Any studentcould offer an experimental uggestionordirectthe groupto takea particular c-tion andobserve theresults. It was upto the groupto determinewhose suggestionmade the most sense, given the problemat hand.Episode 5

Allison: I thinkwe should ust turnourson and wait and see whoevergets sick first.Rick: (Leapingout of his chair)THAT WAS MY PLAN!You got that on tape, right,I said it first!...conducting the experiment ...Rick: We're supposedto chill.Student: Allison you wannaexchange?Allison: No, we're not supposedto have anybody.

Everybody's supposedto have zero.Stacy: Is everybody supposedto have zero?Researcher: That's what I thought.Rick: This is my experiment!Tom: Oh, I get it. We're tryingto see if anybodyturnsup red.Student: One minute.Allison: I thinkwe shouldgive it 10 minutes.

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Thestudentsconceived theexperimentsandretainedcompletecontrolovertheex-perimentalruns,thoughthe facilitatorcould aid studentsduringthose runs. Thisstudentcontrolwas possiblebecauseof auniqueattribute f participatory imula-tions-there was no simulationunless all of the student-agents reatedone. If anyclass memberbecamemarginalized,eitherbecausehe was confused as to the na-tureof theexperimentorbecausehewastrying o subvert heexperimental rocess,the group pulledhim back in.10Rerunninga simulationor conductingan experi-ment in this environmentnecessitated the participationof every student. Other-wise, it was as if the simulationwas only partiallyrunning,a situation hatwouldnot yield useful results.Episode6

Stacy: Oh look, it's red.Allison: Justonly beep her once and that's the only person you meetwith is Stacy.Rick: Why?Thenwe're all gonnaendup with it!Allison: No, 'cause we have to see who's immune.Doug: I'm not going to beep her.Rick: I don't want to beep her.Allison: You have to, or else the experimentwon't work.

InbothEpisodes5 and6, therewas communitynegotiationabout hedesignandex-ecution of the experiments.Studentscontinued o offer ideas for new experimentsandask forexplanationsaboutwhy certainpropositionswereexpectedtoyieldpar-ticularpieces of information rom thesimulation.But oncethegroupbeganto col-lect data,studentsexertedpressureon one another o complywith the statedproto-cols. The nature of the participatorysimulation ensured that all of the classmembersworkedtogether.In this way, participatory imulationsdifferfrom col-laborativeenvironments n which the facilitatormust keep all of the students o-gether.As Allison explained o herclassmate,Rick,"youhave to [participatewithus] or else the experimentwon't work."

ProgressionfScientificActivityThestudents n thispilotstudywere firstchallenged o meet a lot of peoplewithoutcatching hevirusand henencouragedo articulate clearunderstanding fthe sim-ulation. Theparticipatoryimulation hatenabled heiractivitieswas a motivatinglearningenvironment.Studentsworked ogetherasthey figuredout whatwas hap-

'0SeeGranott1998) for a discussion on definingthe size of, andsubsequentlyanalyzing, heunitofcollaboration.

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peningin thesimulation.As ina traditionalmicroworld, he studentsneededtoun-derstand heunderlying ulesofthe simulationofullycomprehendtsdynamicsandfinal outcome.They helped each othergatherevidence, define the problem,andbuild heoriesabout hedynamicsofthe system.Finally, hey designedandexecutedexperiments otesttheirhypothesesabout herulesoftheirsimulation nvironment.The students earnedaboutthese rulesnotby masteringa specific symbolicrepre-sentationofthem butby consideringandmodifying heirowninterpersonalnterac-tions andobserving heresultingviraldynamicsuntiltheycouldreliablypredictanexperimentaloutcome.Forinstance,attheendof thestudy,theycouldpredictwhowould orwould notgetsickaftermeetingPatientZeroandhowlongit wouldtakeforan infectedpersonto show symptomsof the virus.Duringthis study,the studentsplayed a total of six virusgames. Eachsimula-tion game took only a few min to play; however, studentstypically spent moretime-up to 25 or 30 min-discussing each game andplanningtheirstrategyforthe next one. Inthe first few games,studentswerenotinquiring ntoa well-definedproblem.Instead,theirfocus was on generalobservationanddata collection. Astheygainedfurther xperience nthesimulationenvironment,hey agreedon a fewspecific problemsthatthey wantedto solve. In the latergames, they were moresystematic as they designed experimentsand collected datato confirm or denytheirhypotheses.An analysis of the episodes from the first participatory imulationgame re-vealed that instances of data collection andpreliminarydataanalysiswere morefrequent han nstancesof experimentaldesign.As the students ried o make senseof the firstgame,therewas much discussionabouteachindividual'sexperience nthe simulation.There was almost no focus on designingexperiments o elucidatethe dynamics of the system. As a result of their lack of experimentalplanning,GameTwo followed a very similarpatternof behaviorandappeared o yield littlenew informationabout hedynamicsof thesystem.Inspiteof thisaimlessappear-ance, Games One and Two were not unimportant.The evidencethat the studentsgatheredand the experiencesthatthey accrued became the foundationfor theirmoresystematicapproach oproblemdefinitionandexperimentaldesignin GameThree.

Game Threetookplace on the 2nddayof participatory ctivities.11Duringthisgame, the studentsagreedon a problem:figuringout how the virus spreadfromstudentto student.Then, they workedtogetherto analyzethe data thatthey hadcollected. Morefocusedexperimentaldesignemergedduring hisgame.The con-currentpursuitof gatheringnew facts anddesigningandrunningnew experimentscontinuedthrough he next threegames, increasing n the numberof occurrencesper game, until the groupcould articulate heunderlyingrulesof the simulation.

"Ourexperiencein this andotherparticipatoryimulationshas shownthatallowingtime for inde-pendentreflection results in moreproficientproblemdefinitionandexperimentaldesign.

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Thispatternof activityis consistentwith thecharacteristics f scientificinquirythatwe aimedto facilitate.As describedby Hall (1996), "inquiryproceedsby a re-flective interplaybetweenselectingconditions n a situation hat framea problemandconceivingof relatedactivitiesthatwill bringabouta solution" p.211). Intheparticipatoryimulationsenvironment, tudents ramedmultipleproblemsand ex-ecutedexperimentalactionsto discover the solutionsto thoseproblems.Althoughthis pilot study does not allow us to conclude that the participatory imulationalone causedstudents o engage in inquiry, t does allow us to observe thatin thisenvironmentstudents are able to define a problem, inquireinto its nature,andsolve the problem.Ourhope is thatthis experiencewill be one of many in whichthe studentsbuild andpracticethe skills of scientific inquiry.

DISCUSSIONOurpreviouswork withthe ThinkingTags (Borovoyet al., 1996, 1998) informedmuchof theearlydesignof participatoryimulations.We wantedto keepthe tech-nological aspectsof theactivityunobtrusive, ven thoughthecomputerswere me-diatingthe simulation.The simulation tself utilized the Tags' abilityto structureinteractions, n this case by handling he spreadof thevirus.As we continuedourclassroomworkwithparticipatoryimulations,we looked moreclosely atthe spe-cific ways thatactivities ike this one cansupport ollaborative cientificinvestiga-tions.Overtime, a numberof designprinciples orconstructingandimplementingparticipatory imulationshave emerged.Muchwork remainsto be done to deter-mine the best ways to use participatory imulationsandothersimilar activitiesinthe context of classroom earninggoals.We hopethatthe following design princi-ples will provetobe fruitful tartingpointsaswe continue o investigate he educa-tionalefficacy of participatory imulations.

Keepthe TechnologyUnobtrusiveCarewas takento preservenatural ocial interactions,using the Tagsto augment,not takeover, communicationandcollaboration. nthe Participatory imulationsStudy,this designchoice accomplished wo important oals.First, heTagsdo notget in theway of the natural ommunicationbetween students.Second,thoughthetechnologyis quiteunobtrusive, he studentsbecomedeeplyengaged nthe diseaseexperience.Therearemanywell-documentedandvariedexamplesof Computer-SupportedCollaborativeLearning(e.g., Koschmann,1996). Participatory imulationspro-vide anotherexample of a computer-based ollaborativeenvironment hat fullysupportsnaturalcommunicationamongstudents.Participantsuse voice, gesture,

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andexpressionto communicatewith one another, ather hansharing nformationthrough ext andimages on-screen.Students' nteractionswith each otherandthesimulationare notconstrainedby largemonitorsor awkward echnologyconfigu-rations.12Moreover, he minimaltechnology displayseems to encouragestudentsto use their own imaginationandpriorexperienceduringthe activities. The stu-dents areable to use social cues andknowledgeabouteach otherto enhancetheirengagementin the game. PictureRick's pridewhen he exclaimedthat he wasn'tsick: "I'mthe man ... that'sright,I'ma clean headagain... You allwant tobe likeme." Orthe initialsuspicionthatTomwas the first carrier:"Who startedoutwithit? I thinkTom did.Why?Because ... look at him. (laughter)Sometimesyou cantell like that."Or the notion thatDoug startedout with the virus because he was"dirty."On the last day of theproject,two studentsrecall theirexperiences:Episode7

Tony: You don't feel good when you have the virus unless there'ssomethingnotworkingupthere.... Yeah, 'causeI didn'tlikeit, I got it [thevirus]when I wasn't even in the roomand thatwas just upsetting o me. It's a hard hingto deal with.Episode 8

Doug: Say you have HIVorsomething,avirus,and t don'tshowupin your systemright away, you couldgive it to someone elsewithoutknowing.Theparticipatoryimulationallows the inclusionof thepriorknowledge,attitudes,habits,and nterests hat hestudentsbring otheexperience.The studentswho par-ticipatein participatory imulationsdrawon the frameworkof the simulationandtheir own knowledge andimaginationas they experiencein the simulation.Theyact andrespondas thoughthe simulation s real,eventhoughthere s verylittleex-plicit visual support orthe metaphorof the game.TheTags' minimaldisplaydoes not impairandmay support he students'abil-ity orwillingness to suspendtheirdisbeliefaboutthe simulation,andthe unobtru-sive natureof theTagtechnologysupports ichinteractions mongalarge groupofstudents.This resultmay have implicationsfor designing engaging educationaltechnology, the budget for which rarelyrivals thatof priceyvirtualrealitygamesinwhich fancy graphicsandhead-mounteddisplaysprovideall of the contextfor avirtuallyrealexperience.

12See Stewart,Bederson,andDruin 1999) andStewart,Raybourn,Bederson,andDruin(1998) foradifferentapproach o enablingmultiplestudents o interactwith a single computer.

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AddCoherent,ConsistentRules o theExperiential orldFor many years, role-playing games have entertainedchildrenand adults.Thesegames, like DungeonsandDragons,enableparticipantso adoptcertainpersonasandin so doing require hatthe participants ehave like their characterswould inany given situation.Computers,andin particularhe Internet,have expandedtherangeandpopularityof these games (Turkle, 1995). The ThinkingTags createanew kindof role-playinggamethatcombinesthe immediacyof real-lifeadventurewith the consistentrulesof mediatedgames andmicroworlds.Withoutconstrain-ing the communicationorthe behaviorof the students, heTagsprovidea tremen-dousamountof structurenthe environment.TheTagscarry heunderlying ules ofthe simulation viralrulesinthis study) ntothe students'world.In somesense, theTagstransform hestudents ntoagents namicroworld,evenastheyallow the stu-dents to retaintheir own personalities.

Bringinga microworld nto the realm of students'experienceenables themtoexplore the underlyingformal structureof that world without abandoning heirown perspective.Theymake use of the consistentbehaviorof the Tagsas they de-sign experimentalprotocolsto reveal the rules thatgovernviral behavior.Eachofthesecomponentsof theparticipatoryimulationarises becausetheTagscreateanenvironment hat s initiallymysteriousbut,uponfurther eflectionandaction,be-comes transparent.The use of the Tags allows the students o reachtransparencythrougha new paththat drawsupon the students'own personalexperiencesandtheir own systematicexplanationsof those experiences.Whendesigningthis participatoryimulation,we constructeda simulation hatexploresafewimportant oncepts,ratherhancreatingasimulation hatcloselymir-rorsareal-lifesituation. nthisexample,we focus ontheconceptsof latencyand m-munity.Thoughmanystudentscompare hisparticipatoryimulation oHIV,we donot model any of the complexitiesof HIV transmission andthe infection rateof100% s quitedifferent rom hatof HIV).Wepurposely nclude heartifactof onlybeingabletomeet anotherpersononceinthis simulationbecause t makes he modeltractable,not because it increasesfidelity to a real-worlddisease. Roughgarden(1996) called thistypeof model,whichseeksto capture he most fundamental artsof thesystemand llustrateageneralprinciple,an idea model Participatoryimula-tions allowus to createarich earningenvironmenthat s basedupona "smallclus-ter"of essential ideas(diSessa, 1986);inthiscase, latencyand mmunity. tmaybethatmorecomplex systemsmodels arebetterexplored hroughothermedia, nclud-ing microworldsand traditional imulationenvironments.RecreateScientific henomenanInterpersonalpaceParticipatoryimulationsbringstudents nto directcontactwithscientificphenom-enaby deployingthephenomena nthe students'own interpersonalpace.Because

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the simulationoccurs in realspacewithstudentsasagents,there s no gulfbetweenparticipants' mmediateexperienceandthe simulation-they are the populationthatis being affected.Participants'nternalconditionsorresponsesto the simula-tion are not treatedas separate romtheirinquiry nto the simulation.Thoughtheparticipatoryimulation s anintentionally ontrivedenvironment,hestudentsarecompelledby theirexperience,often exclaiming duringthe virus simulationthatthey have "died"or "caughtHIV."Farfrompreventing nquiryorimpeding he studyof important cientificmate-rial,participants'personalexperience nthe simulationreduces he barriero entryfor thedesignandexecutionof scientificexperiments.This reducedbarriermayoc-curbecauseparticipatoryimulationsaskthe students o considerandexplorepat-ternsin their own behavior.Any participant an collect data(by reportingon theirownexperienceor thatofa peer)orproposeanexperiment by suggestinga newpat-ternof humanbehavior).Thevirus simulationanalyzedheresupported richset ofexperientialandexperimentaloutcomesin a socially meaningfulcontext.

Facilitate imilar utNon-IdenticalxperiencesThe activitiesin a participatoryimulationaredesignedso thateverystudenthasasimilarandmeaningfulexperience.Similarexperiencesof the activityensurethatthe studentsshareacommonbase fromwhichthey explorethe simulation.Whenaparticipantdescribesherexperienceof the activity,her classmatescan understandandrelateto herdescription, n partbased on their own experiences.Later,whenstudentscollectdataandproposeexperiments, heyare all equallypreparedo takepart n these activities.Meaningfulexperiencesensurethatevery participant's x-perience s importantwithrespect ounderstandinghebehaviorofthe whole simu-lation. Because a participatory imulation s a completelydistributed ystem, nosingle Tagis "running"hewhole simulation.No one student'sTagis more or lessimportant hananyother student'sTag,3 andsimilarly,no student'sexperience sany more or less important hanany other student'sexperience.In fact, all of thestudentsmustcontribute heirexperiences o thegroupdiscussionin order o makeitpossibleto understand hedynamicsof thesystem.Statedanotherway, eachstu-dent's ownvantagepointmustbe articulated ndexplored n order or thegroup oachieve anunderstanding f the whole system.The activitiesthemselves enable a"social organization n which all individuals have an opportunity o contributesomething"and "towhich all feel a responsibility" Dewey, 1988, pp. 34-35).

'3With hepossible exceptionof PatientZero who beginsthe infection;however,thatdesignation schosenrandomlyatthebeginningof eachgame, meaning hat(inthiscase)PatientZeromightbe Dougthe firstgame,Rick the second, andLiz the third,and so on.

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UNDERSTANDINGHROUGH YNAMICMODELING 495

However, not every experience is designed to be identical. StudentswhoseTags are immune to the virus have experiences that differ consistently fromthose of their classmates. Students who elect to behave in a particularman-ner-perhaps meeting a lot of people or perhaps interactingwith no one atall-also have incongruousexperiences. The asymmetryof experience is cre-ated not by the differing talents of the students but by their differing experi-ences of the activity. In orderto decipher the underlying mechanisms of thewhole virus simulation, students must first develop an understandingof whathappenedto them and then listen to what happenedto other people. As theirdescriptionsbuild one by one, the studentsbegin to develop an understandingof the system as a whole. The experiences that differ fromthe mainstreamcanthen be identified as outliers, and alternativehypotheses can be proposed forthose data points.

Participatoryimulationsenableakindof collaborative earning nwhicheverychild's experiencebuilds towardanunderstanding f the whole. However,partici-patorysimulationsset up a differentstructure or collaboration hanmany otherforms of collaborative earningdo (Aronson,Blaney, Stephan,Sikes, & Snapp,1978;Collins, Brown,& Newman, 1989;Slavin, 1996)becauseonly a collabora-tive effortthatengages all of the participantswill enable the groupto constructamodel of the whole simulation.Everystudentneedsto sharehis orherexperienceof the simulationandeverystudentmustparticipatentheexperimental unsof thesimulation.The process involved in building a collective understandingof thewhole systempushesstudents o make theirthinkingovert(Brown& Campione,1990) asthey explaintheirideas andpredictions o theirclassmates.Thisenviron-ment is particularly ich for looking at the process of collaborationbecause thetechnology supportsand mediates a problem context that involves the wholegroup,allows face-to-face collaboration,andprovidesa computational ubstratefor experimentaldesign andexecution.

EnableStudentso DeviseTheirOwnSolutionsInthepilot Participatory imulationsStudy,studentswere notgiven a specific vo-cabulary o use whendiscussingthe rules of the simulation,nor weretheygiven analternativewrittenrepresentationo describe hedata heycollectedorthehypothe-ses theyproposed.Thislack of predefined tructure ormeaning-making ctivitiesappears o be bothpromisingandproblematic.Throughout he activities,but especially afterthe thirdgame, the studentsen-deavorto clearlyexpresstheirideas so thatothers can follow the points they aremaking.In time, they beginto agreeon ways to talk aboutthe activitythatevery-one can understand. Here, they use the Tag numbers to express the concept of im-munity.

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496 COLELLA

Episode 9Tony: It was a pattern ike that 20 21 thing.The numbers.Meredith: Itwas 1 2 11 21.Tony: I said the 21 thing.Meredith: Itwasn't specific.Tony: It was specific-you knew whatI was talkingabout.It was

specific enough.WhenTonymentions the "2021 thing,"he is referencing he factthat he thinksacertain et of Tagsare mmune othevirus.WhenMeredith orrectshimby indicat-ing exactlywhichTagsareimmune,he protests,pointingout thateven if his com-mentwas not precise,it was sufficientfor herto understandwhathe meant.This type of discourse s consistentwiththat of manyotherparticipatory imu-lationswe have run,in which participantsdigressfrom data collection or experi-mentaldesign to settle on a precisemeaningfor "immunity" r "carrier."In thecase of immunity,students ypicallydiscusswhetherornot immunepeoplecanin-fect others even if they never show symptomsof the virus. In the case of a carrier,participants suallydebatewhetherornota carrier an evershow symptomsof thedisease.)In its current mplementation, acilitatorsof a simulationdo not providecor-rect definitions for these or other debatedterms, even if the definitionthat thestudentsultimately agreeon is not preciselycorrect.This processallows the stu-dents to arriveat their own vocabularyfor articulating he rules of the simula-tion. Although we have not yet undertakenextensive researchin this area, theconsistencywith which variousstudentgroupswork to define specific meaningsfor their descriptionsof the simulationsuggests that more research nto this ac-tivity may be warranted.

Similarly, hefacilitator n thisstudydidnotsuggestanykindof alternative ep-resentation orthe data or therules of the simulation.Some groupsof students ryto designcharts,diagrams,or othergraphicaldepictionsto aid in theiranalysesoftheproblem.Thegroup nthispilot studydrew a charton the boardof the lastper-son that each studenthadmet (duringEpisode3). Unfortunately,unlike creatingrepresentationsorsystemwidebehaviorsandoutcomes,it is quitedifficult torep-resent individualbehaviors and outcomes in agent-basedsimulations (like thisparticipatory imulation)in a mannerthat illuminatesthe key interactions e.g.,Feigenbaum,Kannan,Vardi, & Viswanathan, n press). Otherresearchershaveexplored he cognitivegainsthatpeoplemake whencreating heirownrepresenta-tions (Bamberger,1998;diSessa, Hammer,Sherin,& Kolpakowski,1991;Greeno& Hall, 1997; Hall, 1996;Nemirovsky, 1994), andwe hope to find a way to in-clude such activitiesin futureparticipatory imulations.In fact,during his pilot study,the researcher acilitatedall of the participatorysimulationactivities.Although his structuredidenableus to explorethe students'

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behaviorandinquiry, t was not ideal for investigatingthe role of the facilitator.We expectthat,as inproblem-basedearning, he facilitator'srole in participatorysimulations s complexandimportanto the educational uccess of the activity.Anumberof teachers n high schools,universities,andgraduate chools havebegunimplementingparticipatory imulations n their classrooms. We anticipate earn-ing more about the complex relationshipsthat support this learning activitythroughan analysisof theirclassroomexperiences.Thispilot studysuggeststhatdeployingmicroworlds nrealspaceoffersanop-portunity o reevaluate herole thatstructuredxperiencescanplay in understand-ing the mechanisms hatgovernpatternsandprocessesin the world.We hopethatfutureresearchwill help shed light on the ways thatparticipatingn simulationscan supportchildren'sdevelopingscientificunderstanding.

ACKNOWLEDGMENTSThis researchhas been generouslysupportedby the LEGOGroup,the NationalScienceFoundation grants9358519-RED andCDA-9616444), andtheMIT Me-dia Laboratory'sThingsThatThinkandDigital Life consortia.Specialthanks o my advisor,MitchelResnick,for his supportand valuable n-sightthroughoutheproject, o TimothyKoschmann or his helpfulcommentsandmanyenlighteningconversations, o BrianSmithfor his candidfeedbackandas-sistance, and to Janet Kolodner and MarkGuzdial for their encouragement.Iwould also like to thankJeremyRoschelle and an anonymousreviewer for theircontributionsto the article. Thanks to the members of the Epistemology andLearningGroupat the MIT Media Laboratory, specially RichardBorovoy andKwin Kramer. am indebted o the manystudentsand teacherswho havepartici-patedin this project.

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