UsingtheMasterCopyͲAddingEducationalContenttoCommercial VideoGames HeinrichSöbke1,ThomasBröker1andOliverKornadt2 1 BauhausͲUniversitätWeimar,FacultyofCivilEngineering,InnoProfile:Intelligentes Lernen(IntelligentLearning),Weimar,Germany 2 TechnischeUniversitätKaiserslautern,FacultyofCivilEngineering,Kaiserslautern,GerͲ many heinrich.soebke@uniͲweimar.de thomas.broeker@uniͲweimar.de
[email protected]Ͳkl.de Abstract: Successful development of educational video games has to overcome plenty of challenges. In addition to the requirementsofasuccessfulsoftwaredevelopmentproject,anattractivegameexperiencehastobedesignedandimpleͲ mented.Howeverafailureinoneofthemostambitioustasksofdevelopinganeducationalgameisknownas"chocolateͲ dippedbroccoli".ThistermwasusedbyBruckman(1999)todescribetheunsuccessfulintegrationofgamemechanicsand learningcontent.Analternativeapproachtoavoidtheseproblemsisnotnewbutstillseemstobeunderrepresentedinthe fieldofDigitalGameBasedLearning:theuseofexisting,popularvideogames.Recentresearchhasacknowledgedseveral videogamesaseducationalmediaforthetrainingofprofessionalskills.Besidesthatvideogamescanbeusedtospread domainknowledge.Suchvideogameseitheralreadycontainspecificdomainknowledgeortheycanbeextendedeasilyto embeddomainknowledge.Thispaperpresentscasestudiesoffourcommercialvideogames,whicharepotentiallyeligible foreducationalextension.Eachgamerepresentsadistinctcategory:Fliplifestandsforsimple,communityenhancingSocial Network Game (SNG) Triviador as a SNG is the synthesis of two well known board games (Risk and Trivial Pursuit). JuͲ raShooterStGBͲalreadydesignedasaneducationalgameͲexemplifiesmobiledevicegames.LastlySimCity5isarepreͲ sentativeofaclassicstrategyandsimulationgamewithfocusonsystems.Eachgameisshortlyintroduced,ourrelevant gameplay experiences and the potential learning content is described. Finally we identify potential extensions regarding additionallearningcontentforeachgame.Havingtheseexamplesinmindwesuggestamoresystematicapproachtouse commercialvideogamesaslearningtools:ifagamehasbeenprovenasaviablesourcefortransferofdomainknowledge, we suggest categorizing it due to two characteristics: complexity of learning content and mainly attracted player types. Basedonsuchacategorizationadirectoryofgamescanbecompiled.ThisdirectorythencanbeusedinaconcreteeducaͲ tionalscenariotoidentifyappropriategames.AsacategorizationforlearningcontentwesuggestBloom’srevisedtaxonͲ omy. A well known categorization for player types was proposed by Bartle. Although by farnot every commercial video gamecanbeenrichedwitheducationalcontent,theefforttocustomizeexistinggamesseemstobemuchsmallerthanthe efforttocreateeducationalgamesfromscratch.Thispaperarguesforasystematicapproachtofacilitatecommercialvideo gamesineducationalsettingsasanadditionaloptionapartfromindividualimplementationsofeducationalgames. Keywords:digitalgamebasedlearning;COTS;commercialvideogames;SimCity,JuraShooterStGB,Fliplife,Triviador
1. Introduction Videogamesarearelativelynewtypeofmedia.Originallyjustcreatedforentertainmentpurposestheyare nowalsousedineducationalsettings.Gee(2005)referstovideogamesaslearningmachines.Inthelightof the huge impact on players learning sophisticated models to master a game, educators started to develop educational games. However this approach has seen a lot of failures. EgenfeldtͲNielsen (2007) states that “edutainmentstartedasaseriousattempttocreatecomputergamesthattaughtchildrendifferentsubjects. Arguably, it ended up as a caricature of computer games and a reactionary use of learning theory.” Papert (1998) uses the picture of a Shavian reversal: “Shavian reversals — offspring that keep the bad features of eachparentandlosethegoodones—arevisibleinmostsoftwareproductsthatclaimtocomefromamating of education and entertainment”. Bruckman (1999) used the expression chocolateͲdipped broccoli for her observationthat“funisoftentreatedlikeasugarcoatingtobeaddedtoaneducationalcore”. Alltheseperceptionsmirroratleastpartiallytheultimatecomplexityofeducationalgamedevelopment:BuildͲ ingsoftwareisalreadyariskyventure:Ambler(2010)foundthatonlyaroundhalfofITprojectsaresuccessful. Thenexthurdletotakeistodesignanattractivegame:acommonlyacknowledgemethoduseseffortconsumͲ ingcyclesofdevelopmentandplaytesting(Fullerton2008).ForeducationalgamesthisprocesshastobeadͲ justed to certain learning targets and complemented with an appropriate context and content. Habgood & Ainsworth(2011)callaseamlessinterlacingofgameandeducationalcontent“intrinsicintegration”:learning
HeinrichSöbke,ThomasBrökerandOliverKornadt contentshouldnotappearasaforeignobjectinthegame.Notbeingallenough,thesecomplextaskshaveto becoveredwithlimitedfinancialresources,becausenormallyeducationalgamesdonotreachthosehighsales revenuesastheircommercialcounterpartsdo(Brökeretal.2011). AsonesolutiontothisdilemmaYoungetal.(2012)“believethatcommercialgamingcompaniesandeducaͲ tional researchers could mutually benefit by bringing academic content into the fictitious worlds originally createdwithouteducationalcontentobjectivesinmind”.Commercialvideogameshavebeenalreadyusedas educationaltools:TheFuturelabProject(Sandfordetal.2006)investigatedtheusageof“commercialoffthe shelf[(COTS)]computergamesinformaleducation”.TheSims2,RollerCoasterTycoonandKnightsofHonor havebeenthoseCOTSgameslookedatinthisstudy.TheSims2asamediuminformaleducationalsettings havebeenstudiedbyPeterson(2011)andPanoutsopoulos&Sampson(2012).A.N.Foster(2011)choseRoller CoasterTycoon3asatoolforthetransferofdisciplinaryknowledgeineconomicsandsocialstudies. 1 Lookingatalltheseexamplesatleastthreeareasofgameusageforeducationalpurposescanbeidentified : First,gamescanbeusedasamediumtospurreflection.AtWabashCollegePortalwassetonthebooklistof ancompulsoryseminar,which“isdevotedtoengagingstudentswithfundamentalquestionsofhumanityfrom multiple perspectives and fostering a sense of community” (Abbott 2010). Second games are used to teach professionalskills.Poling(2010)facilitatedStarCraftinacourseabout21stCenturySkills.Steinkuehler&DunͲ can (2008) found that successful play of World of Warcraft requires “scientific habits of mind”. And third gamesareemployedforconstructionofdisciplinaryknowledge.Squire(2003)taughthistorywithamodified versionofCivilizationIII.AcasestudyofMoshirnia(2007)donewithCivilizationIVleadtosimilarresults. Sofarwehavearguedthatbuildingsuccessfuleducationalvideogamesisahighlychallengingtask.Thenagain thereexistalotofintriguingcommercialvideogames.InthispaperwewanttoproposethesystematicinvesͲ tigation of COTS games for either existing learning content or the possibility to addand embed appropriate content.WeuseacomprehensivedefinitionofCOTSvideogame:Itisanydigitalgamewhichcouldbeusedas 2 host for potential educational content but which currently is not holding that content . In addition to dediͲ catededucationalgamesthiswouldbeafurther,effortsavingapproachtoestablishvideogamesaseducaͲ tionaltools.
2. Casestudies TheproposedapproachtouseCOTSgamesforeducationalpurposesisbasedonafewassumptions:Itmaybe possiblethatagamecanembededucationalcontent.Forasystematicapproachtoclassifyagameitscontent shouldbegradedaccordingtoaknowledgetaxonomy–theknowledgedimensionofthegame.AwellͲknown taxonomyhasbeenintroducedbyBloom(1956)andmodifiedbyAndersonetal.(2000).Thisisnottheonly valid categorization – e.g. the already mentioned overview of Prensky (2007) classifies content specifically foundinvideogames,butitisataxonomycommonlyutilizedineducationalcontexts. Players are categorizedbyplayer type taxonomies, e.g.Bartle's player types (1996). In addition tothese asͲ sumptions we hypothesize that the learning objectives are given as well as the structure of the player type distribution.Thenitshouldbepossibletochooseanappropriategame,enrichitwithcontentanduseitinthe considerededucationalsetting.SuchanapproachwouldneedacatalogueofCOTSgamescapableofincluding educationalcontent.Ourcasestudiesintroducefourvideogamesaspotentialelementsforsuchacatalogue. Wedescribeeachgameinfourcategories.GamedescriptionisaroughsummaryofthegamesmaincharacterͲ istics.Itconveysashortimpressionofthegame.InthesectionGameplayexperienceswesummarizeourperͲ sonalimpressionsofthegameplayaswethinktheyarerelevanttousethatgameinaneducationalcontext. Learningcontentisthecaptionforananalysisofthestructureandtypeofpotentialeducationalcontent.The partPossibleadoptionsproposesappropriatechangesofthegamesoftwaretosupportthegame’susageasan educationaltool.
Prensky(2007)givesamorecomprehensiveoverviewofdifferenttypesoflearningcontentincludingfacts,skills,behaviourandcreativͲ ity. 2 ThisdefinitionimpliesalsoeducationalgamesthemselvesͲastheexampleJuraShooterStGBdemonstrates.Theimportantcharacteristic wewanttopointoutisthecombinationofanexistingvideogameandadditionaleducationalcontent 1
HeinrichSöbke,ThomasBrökerandOliverKornadt
2.1 Fliplife Game description: Fliplife is a multiplayer, HTML5 based browser game (Fliplife 2012; Fliplife.com 2012). Unlikeatypicalsocialnetworkgametherelationshipbetweentwoplayersisnotfixed,butdefinedaccording totheamountofcommonactions:Themoreinteractionstwoplayershave,thenearerbecomestheirrelationͲ ship.MainobjectiveofFliplifeisasimulationoftheplayer’slife:professionalcareer,educationandfreetime. TheplayerpursuesacareerbytakingpartinawellͲdefinedsetofprojects.Sparetimeactivitiesaresportsand parties.Theseactivitiesarerewardedwithenergy,whichisneededfordoingtheprojects.EducationisproͲ vided by multiple choice question based quizzes. Fliplife got special attention when it was said to be an asͲ sessmenttoolforaGermantrust(Söbke,Hadlich,etal.2012). Gameplayexperiences:ThebasicgamemechanicsofFliplifeseemtobeverysimple,althoughtheycanbuild thefoundationforcomplexproblems(Söbke,Bröker,etal.2012).IngeneralFliplifeshowsthecharacteristics of an online third place: players meet online in their spare time, make acquaintances and friends (Soukup 2006).ThegamemechanicscreateaframeforcommunicationwithcoͲplayers.FliplifemaybealowcostverͲ sionofanonlinegamewhichservesasathirdplace(Steinkuehler&Williams2006).
Figure1:Fliplife:projectdescription Learningcontent:Fliplifecontainsdomainknowledge:specialist’sexpertiseisrepresentedbycareerpathsand projects.Alsothegameobjectsarepartlydomainspecific.HowevertoplayFliplifesuccessfullythisknowledge isnotmandatory.ThesoͲcalleduniversityisanotherpossibilitytolearn:Thequizzesarequitedemandingand requirebroadgeneralknowledge. Possibleadoptions:Müller(2012)hasinvestigatedpossibilitiestointegratedomainknowledgeinFliplifeusing thedomainofbuildingphysics,adisciplineincivilengineeringconcerningthecomfortinbuildings.HersuggesͲ tionsincludeadomainspecificcareerpath,abuildingphysicsinstituteasemployerandprojectsfromthefield of buildingphysics. Apart from descriptive texts, striking graphics could emphasize technical details. Beyond thattheuniversitycansupportlearningbyfieldspecificquizzesandissuingfieldspecificrewardsandbadges. Furthermoreshesuggestsassignmentswhichrequiretheplayertodoatechnicalanalysisoftheprojects(e.g. “Execute3heatprotectionprojects.”whereheatprotectionisnotashownattributeofaproject,butderivable fromtheprojectdescription).Fortheintegrationofbuildingphysicslearningobjectivesitseemsappropriate toupgradetheplayer’sbuildingwithmoretechnicaldetailsasitisdoneinthecurrentversion.Anadditional minigamecoulddealwithwallstructures:Theplayerhastobuildwallstructuresfromagivensetofmaterials tomeetcertainrequirements.CrowdsourcingisalsoanoptionmentionedbyMüller:certaincouldcauseplayͲ erstodealwithtechnicaldetails.HermainapproachtocomplementFliplifewithdomainspecificknowͲhowis integrationofspecificinformation,graphicsanditems. As already mentioned succeeding in the game is not connected to any technical knowledge. Nevertheless it couldbringdomainaffiliatedpersonstogether.Ifthosepersonsareinvolvedinthegame,thegame’sstrength
HeinrichSöbke,ThomasBrökerandOliverKornadt as a virtual place could induce community building processes (“Community of Practice” (Lave & Wenger 1991)).
2.2 JuraShooterStGBͲJagdnachdemKatzenkönig Gamedescription:JuraShooterStGBͲJagdnachdemKatzenkönigisaneducationaliOSgametomemorizethe cruciallegaltermsofcriminallaw(LernfreakGbR2012).Thisdrill&practicegamewasproduced2011bya group inspired and led by the german lawyer Raban von Buttlar. Its title refers to a wellͲknown and widely discussedcriminalcause(Pötters2009).ObjectiveofthegameistounmaskthealiencatsoftheKatzenkönig (“catking”).Thisisdonebyinstantlytappingthecatsthatcarrypartsofthecorrectanswertoalawquestion. TheplayerisrewardedforcorrectanswerandgetsextrapointsforfasteranswersandforansweringinacorͲ rect order. Questions itself are collected in packages. Each package focuses on a certain topic. Currently all contentrelatestothedomainoflaw. Gameplay experiences: Our personal gameplay experiences have been dominated by audiovisual feedback causedbytappingthemonsters.Itseemstoactbothasarewardandashortcycledfeedback.Thisfeedback andtheadditionalentryinthehighscorelistarethemainmotivationalelementsofthisgame.ExtrinsicmotiͲ vationforlearningthecontentvanishesduringtheplay.Answeringquestionsbecomesatoolforreachinga highscore–atleastforacertaintypeofplayer.Thisconclusionisnotyetbackedupbyscientificdata.HowͲ everitisderivedfromtheentriesinhighscorelists:Topentriescanonlybereachedwhentheplayerinstantly tapsthefirstappearanceofeachanswer.Thatiswhenthecorrectanswerisperfectlymemorizedandcanbe answeredwithoutdelay(Buttlaretal.2012).
Figure2:JuraShooterStGB:Tappingdefinitionelements Learningcontent:Thelearningcontentofthisgameisobvious.Additionalpackagesoflearningcontentcanbe addedwithanexistingcontenteditor.Theeditordoesnotsimplysupportthetextofthequestionandwrong andcorrectanswers.Italsoallowsdeterminingstructuralattributesofaquestion,e.g.totakeaccountofthe orderoftheanswer’sparts. Possibleadoptions:PossibleadoptionsofthegameincludeͲbesidesknowledgeofotherdomainsͲdifferent typesandstructuresofquestions,e.g.matchingorestimationquestions.Itcouldalsobenecessarytochange the narrative (and accordingly graphics) because the main figure “Katzenkönig” is closely related to the law domain.
2.3 Triviador Game description: Triviador is a Social Network Game (SNG) available on the Social Network Service (SNS) Facebook(THX_Games_PLC2011).ItisanadoptionofthewellͲknownboardgameRisk.WhileRiskusesdice forrandomdecisions,Triviadorreplacesdicebyquestionsinseveralforms.Atthefirststageamultiplechoice
HeinrichSöbke,ThomasBrökerandOliverKornadt questionisasked.Ifbothplayerschoosetherightanswer,anestimationquestionwithanumericansweris issued.Theplayerwiththenearestanswerwins.Incaseofatiethefastestanswerwins.Asafurthergame elementplayerscanusejokerswhichincreasetheprobabilityoffindingthecorrectanswerindifferentways. Gameplay experiences: Our gameplay experiences contained a similar trait as those already mentioned for JuraShooterStGB:Especiallyinthewarmodethedesiretowinadueloutshinestheawarenessofprobable learning.Inthecontextofthisgamequestionsbecomeatooltowinamatch.TheyarenottheprimarypurͲ poseofplayingthegame,butanintegratedgamemechanic.
Figure3:Triviador:Selectingbases Learning content: The learning content of the game is given by questions and their answers. Questions are taken randomly from a pool of more than 10.000 questions. So far there are no mechanics for enhancing learning:aplayerbarelycanchoosethetopicofquestions.Alsothegamedeterminestherhythmofplay–a playercannotreflectatherownpaceaboutaquestionnorcanshereviewacompletedquestion. Possibleadoptions:Ingeneralthedisplayedquestionsarechosenrandomlyfromalargepoolofquestions.A soͲcalledTargetedSubjectBoosterallowstheattackingplayertochoosethedomainofthequestion.FurtherͲ moretherearesomecountryspecificversionsofTriviadorthatuseamapofthecountryandcountryrelated questions.ToenhancefurtherTriviador’scharacteristicsofalearningtooltheplayershouldbeabletochoose preferredtopicsinhispersonalgameoptions.Duringthematchingphaseofthegamepreferablytwoother playerswithsametopicpreferencesareassigned.Furthermoretheselectionofquestionscouldadheretoan algorithmofflashcardsystems(e.g.Leitner(2011)).Thisapproachcouldimprovetheeducationalbenefit. AnotherfeatureofTriviadoristhecrowdsourcingofquestions:Whenaplayerhasreachedacertainlevelshe isallowedtoenterownquestionsinseveralcategories.Thesequestionsundergoareviewbyotherplayers. Afterloggingintheycouldoptforansweringacertainamountofcrowdsourcedquestions.Theyhavetojudge thequestioninseveralcategories,e.g.ifthespellingandgrammariscorrectandiftheywanttoanswerthat questioninthegame.Bothactivitieshaveeducationalvalue.ThecreationofquestionsmeansproducingarteͲ factsandjudgingquestionsspursreflection. Wesuggesttaggingthequestionsasafurtherimprovement:untilnowthereisonlyafixedsetofdomaincateͲ gories.Tagswouldintroducemoreandspecializedcategories.Aquestioncouldbearmorethanonetagand belongtomorethanone(subͲ)category(Peters2009).
HeinrichSöbke,ThomasBrökerandOliverKornadt
2.4 SimCity Gamedescription:SimCityisawellͲknownandpopularsimulationgame.Thefirstversionhasbeenpublished in1989.Earlierthisyear(2013)SimCity5 3 hasbeenissuedonanewtechnicalfoundation.SimCityisabout building,developingandmanagingcities.Thusaplayertakestheroleofanengineerwhenheinteractswith theunderlyingsystems.WillWright,whooriginallydesignedSimCity,considerssimulationgamesastoolsfor experimentingwiththeirbasesystems(Wright2007).SimCityhasbeenusedandinvestigatedaseducational tool(Adams1998;Gaber2007;Minnery&Searle2012). Gameplay experiences: The attractiveness of SimCity has already been proven by millions of sold copies of everysingleversionofthegame.SimCity5nowsupportsonlinemultiplayergameplay,e.g.itconnectscitiesof neighbouredplayersassourcesandsinksof(material)streams.Fromthetechnicalviewpointofanengineerof 4 urbanhydrology weexaminedthemodelelementsofthisdiscipline.WeonlyfoundarudimentaryandscheͲ maticimplementationofanurbanhydrologysystem.D’Artista&Hellweger(2007)haveexaminedSimCity4 andmarkeditscompliancewithcurrenturbanhydrologymodelsasinsufficient.Comparedtotheirfindingsthe lastversionofSimCitycontainsmoredetailedmodels 5 .However,theystilldonotmeettherequirementsof realisticsimulationmodels 6 . Learningcontent:AnimportantlearninggoalconnectedtosimulationgamesistheunderstandingoftheunͲ derlyingsystems.Everysimulationgameisbasedonamodel.Playersrevealandlearnthegame’smodeldurͲ inggameplay.AsourexperiencessuggestgamemodelsoftendonotmeetrequirementsofrealityͲlikemodels, i.e.thestructureofmodeldoesnotreflectimportantrealworldelements.Devischmarksblurred,incorrect modelsasoneargumentagainstusageofsimulationgamesforlearningaboutrealsystems(2008).Ingeneral the genre Simulation Game has often been used as a pedagogical tool, which is demonstrated by different examples: Foster (2011)examined theknowledge construction using Roller Coaster Tycoon, Squirehas used modsofCivilizationIIItoteachsocialscience.Mobilitywasbuiltasaneducationalsimulationgamebasedon scientificallyvalidatedmodelsfortransportsystems(Brannolteetal.2000),butithasalsoreachedattractiveͲ 7 nessasavideogame . Possibleadoptions:TheruledrivensimulationengineGlassBoxofSimcity5ishighlyconfigurable.Itcouldbe thebaseforothersimulationgamesaswell(Willmott2012).UntilnowtheAPIofGlassBoxhasnotbeendisͲ closed.Ifthatwouldhappen,adjustingmodelelementsofSimCitycouldleadtorealisticscenarios.
2.5 Questions:Avalidgameelementforlearning? Multiplechoicequestions(MCQ)areamainpedagogicalelementofthreeofthefourabovepresentedcase studies.MCQsareoftencriticized.Oneargumentisthattheyjustcontainknowledgeattherecalllevel.And studentslearntochoosetherightanswerfromasetofoptionsinsteadofknowingallalternativestheyhave 8 . Scouller(1998)attributessurfacelearningtoMCQbasedexaminations. Nicol(2007)presentsaframeworkforMCQsasaneducationaltool.IngeneralMCQsareconsideredasavalid assessmenttoolfortheunderstandingofabstractconcepts(Hopkins1998).Iz&Fok(2007)gaveanexample forthedomainofgeomaticsͲshowingthatitispossibletocoveralllevelsofthecognitivedomainofBloom’s taxonomy with MCQs.Higher levels of complexity mayrequire activities outsidethe test, e.g.doing calculaͲ tions to determine the correct answer. Furthermore they found a relation between the complexity of the questionandthetimestudentsspentonansweringthatquestion.AlsoSimkin&Kuechler(2005)experienced difficulties in constructing MCQs of higher knowledge levels, but they confirmed that this is an practicable approach. WerefertothecurrentversionofSimCityasSimCity5,althoughitisofficiallynamedSimCity. Urbanhydrologyis–besidesbuildingphysicsandlawͲoneofthedisciplinesweareusingforexemplifyingusabilityofcommercialvideo gamesaseducationaltools. 5 Forexamplewaterpumpscanbeupgradedtofiltrationpumps.Thisallowsthereuseofdirtywaterasdrinkingwater. 6 Asanexampleitisnotpossibletousesurfacewaterfordrinkingwatercatchment.Alsostormwatermanagementisnonexistentinthe game. 7 Thiswaswitnessedbyadialoguepartner:whenheheardabouttheauthors’affiliationtoBauhausͲUniversität,hementionedthegame MobilitywhichproductionhasbeenscientificallyaccompaniedbymembersofthatUniversity.Henamedthisgameacauseformanyshort nightsofhisformerlife. 8 As an example: the examination regulations of our faculty exclude MCQ based examinations explicitly as a valid test tool th (http://www.uniͲweimar.de/cms/fileadmin/uni/files/ka/mdu_akad/07/30_2007.pdf,lastaccessedApril,12 2013) 3
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HeinrichSöbke,ThomasBrökerandOliverKornadt Palmer&Devitt(2007)stated,basedonastudyinthedomainofmedicine,thatMCQtests“arecapableof withstanding the intellectual and statistical scrutiny imposed by a high stakes exit examination”. Mukhopadhyayetal.(2010)madeasimilarconclusionalsoforMCQsinmedicaleducation. MCQmaynotbefuncausinggameelements.Theyareneitherpartofaproblemsolving,constructivegameͲ play.Buttheyareavalideducationalinstrument.Andasfarastheycanbeintegratedingameplaywithout affectingintrinsicmotivationnegatively,theycanbeusedasaneducationaltoolforthetransferofknowledge. Prensky(2011) defines an appropriate measurement for fun and learning in aneducational game:“1. Isthe gamefunenoughthatsomeonewhoisnotinitstargetaudiencewouldwanttoplayit[...]?2.Dopeopleusing itthinkofthemselvesas‘players’[...]?3.Istheexperienceaddictive?[...]4.Aretheplayers’skillsinthesubject matter and learning content of the game [...] significantly improving at a rapid rate, and getting better the longerheorsheplays?[...].”Duetoourexperiencesthesequestionscanbeansweredpositivelyforallofour MCQ“enriched”examples–mostlywithoutanyrestriction,butalwaystoacertaingrade.
2.6 Levelsofknowledgecomplexity Gamestructureandgamemechanicsformtheframeforknowledgethatcanbeincludedinthegame.Sothe complexity of the learning objectives depends on the game. The following discussion of an example uses Bloom’srevisedtaxonomy:JuraShooterStGB’scurrentlearningcontentcoverslevel1to3intheKnowledge Dimension:FactualKnowledgeisincludedintheformofdomainterminology.ThegamealsocontainsConcepͲ tualKnowledge:legalstructuresandmodelsareobjectofthequestions,e.g.aplayerhastobefamiliarwith the “legal model” of a second degree murder. An example for Procedural Knowledge is a list of necessary elementsofanoffensetoconstituteapunishablecrime(“Knowledgeofcriteriafordeterminingwhentouse appropriateprocedures”).TheCognitiveProcessdimensionisonlysupportedinthefirstlevel:Theplayerjust needstorememberfacts.Theuseofadditionaltypesofquestionsrequiresachangeofthegamesoftware. HoweveritwouldenablethegametoincludecontentofotherCognitiveDimension’slevelsthanlevel1“ReͲ member”.Asanexampleorderingquestionswouldrequirecomparisons,whichislocatedinlevel2“UnderͲ stand”.AsTriviadordoessupportonlyasmallersetofquestiontypes(SelectionquestionandEstimationquesͲ tion),thecomplexityoftheknowledgeislower. Iz&FokdemonstratedthatalllevelsoftheCognitiveDimensioncanbereachedbyansweringquestions.HowͲ evertheattractivityofquestionsmaybelowwhenansweringneedsalotofworkoutsideofthegame.SimulaͲ tionsgamesͲlikeSimCityͲallowtoexperimentwithpotentialanswersinthegameitself.Becauseofversatile possibilitiesofinteractionbetweenplayerandsoftwaresimulationgamescanincludealsohigherlevelsofthe taxonomy–atthecostofmuchmoreeffortfordevelopmentofthegame.
3. Conclusionsanddiscussion Educationalgamesoftendonotmeetthepromiseofasensedeffortlesslearning.Habgood(2007)observes "chocolatecoveredbrocoli"Ͳlikeedutainmentapplications.Missing“intrinsicintegration”,i.e.intrinsicmotivaͲ tioncannotbeconsistentlyperpetuatedduringgameplay,isconsideredasanimportantreason(Habgood& Ainsworth 2011). These failures may result from the enormous complexity to create an “intrinsically inteͲ grated”educationalvideogame. WeproposeanadditionalapproachtoemployvideogamesaseducationalmediafordomainknowledgetransͲ fer:thesystematicreviewofexistingcommercialoffͲtheͲshelf(COTS)videogames.Byusingexistinggamesthe onlychallengetoovercomeistoembededucationalcontentwhilethegamesoftwarehasbeenproducedand 9 thegameitselfhasbeenprovenasattractive .Furthermoresuccessfulgamesareconsideredtobelearning machinesteachingtheircontenteffectively(Gee2005;Becker2006). Inalargerframeworksuitablevideogamescouldbeclassifiedaccordingtotwocriteria:afirstcriterionisthe potentiallearningcontentthegameiscapabletoembed.WeproposeBloom’srevisedTaxonomy(Andersonet al.2000)asanappropriatecategorization.Thesecondcriterionisthepredominantplayertypeofthegame. Theseclassificationswouldallowselectingappropriategamesforadefinedlearningcontentandaknownset oflearners. Forexampleoftenthesegamesoutperformtheireducational“counterparts”intermsofaudiovisualpresentation(Breuer2012).
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HeinrichSöbke,ThomasBrökerandOliverKornadt Ofcoursethisapproachhastofightsomeimponderables.OneofthemisthequestionifthesuggestedtaxͲ onomies are resilient in this context. Bartle’s taxonomycreated for players of a Multi User Dungeon (MUD) maynotbedirectlyapplicabletoplayersofothergamegenres.Anotheritemneedingfurtherresearchisthe transfertoothercontext.Gee(2003)postulatesthatsuccessfullearningingamesdependsoncontext,i.e.the constructedknowledgeisnottransferredtoothercontexts.Soplayerslearntomasterthegame,butarenot abletoapplytheirknowledgeinrealworldcontexts(Rehm2013;Niegemann2009).ThismaybecomeaprobͲ lem, as contexts given by commercial games cannot be adjusted easily. So the proposed classification may needtobeextendedbyacontextdimension.Alsoitmaybequestionableifnecessarygamerelatedchanges arefeasible–thedeveloperofagamemaypursueotherapproaches.Concerningoursamplethereisamixed situation: SimCity has been announced to be open for new content, but the GlassBox API has not yet been revealed.Triviadorisopeninparts:newquestionscanbeadded,butnonewcategoriescanbeestablished andselectedduringgameplay.Fliplifeisextensibletheoretically,butdefactoitisnotyetclarifiedifthedevelͲ opercompanywouldsupportcustomizedversions.ThishasalreadybeendoneforJuraShooterStGB,whichis theonlyreadyforreusegameamongourcasestudies. Another challenge of simulation games is the problem of simplified and blurred models, whichdonot suffiͲ ciently mirror domain knowledge. FarmVille (Zynga 2009) can be taken as an example: It is build for being extended with additional content (Mahajan 2010). But for crops and animals almost the only fact which is connected to reality is their name – unless they are not pure fantasy elements. Other important simulation modelcharacteristics–asforexamplematurationperiods–areonlygamespecific. Theproposedapproachhasstillalotofchallengestoovercome.GameswhichcanbeenrichedwitheducaͲ tional content are admittedly a rare species. On the other hand the possible gains of employing (modified) COTSgamesarecompelling;evensmallachievementsmightbeworthwhile.Itisanadditionaloptioninthe fieldofgamebasedlearning.AnextsteponouragendaistoextendJuraShooterStGBtothefieldofurban hydrology.WhiletheextensionoftheotherthreeexamplesismorehypotheticalandstillhastobesubstantiͲ ated,inthecaseofJuraShooterStGBthefinancialefforthasbeencalculated:itisaboutoneͲtenthoftheorigiͲ nalapplication.
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