Studies in Computational Intelligence 436 Editor-in-Chief Prof.JanuszKacprzyk SystemsResearchInstitute PolishAcademyofSciences ul.Newelska6 01-447Warsaw Poland E-mail:[email protected] Forfurthervolumes: http://www.springer.com/series/7092 Evangelos Karapanos Modeling Users’ Experiences with Interactive Systems ABC Author Dr.EvangelosKarapanos MadeiraInteractive TechnologiesInstitute CampusdaPenteada Funchal Portugal ISSN1860-949X e-ISSN1860-9503 ISBN978-3-642-30999-1 e-ISBN978-3-642-31000-3 DOI10.1007/978-3-642-31000-3 SpringerHeidelbergNewYorkDordrechtLondon LibraryofCongressControlNumber:2012939886 (cid:2)c Springer-VerlagBerlinHeidelberg2013 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. 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Printedonacid-freepaper SpringerispartofSpringerScience+BusinessMedia(www.springer.com) Foreword Recentresearchin softreliabilityhasrevealedthatalmost50%ofproductreturns intheconsumerelectronicsmarketshouldnotbeattributedtoaviolationofproduct specifications,butrathertoflaweddesigndecisions,mostlymadeintheconceptde- signphase.CurrentresearchinthefieldofHuman-ComputerInteractionrecognizes that usability and usefulness are not the only relevant product attributes, and that moreattentionneedstobepaidtootherrelevantissuesofproductquality,suchas the aesthetic, emotional,and socialaspects of a product.But howcan we account forsuchnon-instrumentalqualityaspectsearlyinthedesignprocess?Andhowcan wedesignproductsthatcomplywiththevaluesofamixedaudience?Thisbookis not pretending to provide final answers to such questions, but rather explores the issues andleads the way to some interestingnew challenges.While manyauthors have been quick to adopt (rather superficially) new hot topics such as user expe- rience design,this bookaims to show the readerwhich interestingand non-trivial issuesarewaitingtobeexplored. Theneedfornewexperimentalmethodsandanalysisproceduresthatcanprovide insightin usersattitudestowardsearlyconceptsandthatcanaccountfor diversity in preferences, both across users and across time, was even hardly realized at the time when the research which is documented in this book project started. In this sense,someofthemajorcontributionsofthebookareinhelpingtodefinetheissues involved.Nexttoproposingspecificmethods,theauthorhascontributedbybring- ing together information from very diverse disciplines such as: human-computer interaction, psychophysics & psychometrics, statistics, personal construct theory, memoryandexperiencereconstruction,latentsemantic analysis, etc. In this sense this book is a prime example of multidisciplinary research, illustrating an excel- lentknowledgeofrelevantliterature,anddemonstratinganabilityto interpretand restructuresuchknowledge. Ofcoursethebookdoesntonlyidentifyproblemsbutalsomakesveryvaluable contributions for how to arrive at solutions. Chapter 2 introduces the concept of personalattributejudgmentsandarelatedexperimentalmethodcalledtherepertory gridtechnique(RGT).Whilethismethodiswell-knowninsome(morenaturalistic oriented)areas of research, it is less so in mainstream (morepositivistic oriented) VI Foreword areasofresearch.Thespecificcontributionofchapter2isshowinghowtheRGTcan becombinedwith quantitativemethods.Thisleads,amongstothers,to newstatis- ticalchallengesforfindingperspectivesthatareintermediatebetweenglobalaver- ages(acrossallparticipantsinanexperiment)andindividualjudgments.Inchapter 3, the proposedapproach is applied in a concrete industrial case to illustrate how developersand intended users of a new system can indeed develop very different perspectivesonwhatshouldbeconsideredimportantissues.Itisespeciallythisdif- ference in perspective that is held (at least partly) responsible for the above-cited softreliabilityproblem. Chapter 4 makes a switch fromthe diversitybetween subjects to the changein userexperienceovertime.Whilemanyresearchershaveunderlinedtheimportance of longitudinal studies, very few examples of such studies have actually been re- ported. The example case reported in chapter 4 illustrates a method for how to conduct such a (5 week) study but, more importantly, also provides a theoretical framework for how to analyze and structure the (mostly qualitative) observations thatarecollectedinsuchastudy.Theoutcomesofthestudyconfirmourintuition thatproductexperiencescanindeedchangesubstantially,especiallyinthefirstcou- ple of weeksafter a productpurchases.While the methodreportedin chapter4 is veryvaluableforin-depthscientificstudies,commercialdesignpracticesareproba- blybetterservedbylarge-scalesurveys.Howtoassistusersofproductsinrecollect- ing and reportingexperienceswith their productin a way thatis suitable for such surveysistheissuebeingaddressedinchapter5.Again,thechapterprovidesacom- binationofamethod,implementedinthesoftwaretooliScale,andawell-structured scientificmotivation,introducingthereaderinanefficientwaytorelevantissueson memory and memory recollection. It is shown how different theories on memory recollectioncan lead to differentvariationsof a method(more specifically,a con- structive and a value-account approach), and how a scientific experiment can be usedtomakeaninformedchoicebetweensuchpossiblealternatives. Thelastchapterisclearlyalsothemostspeculativeone.Ifthemethodproposed in chapter 5 can be introduced successfully, then the amount of reported user ex- periences can be expected to easily grow to a size where processing by a human analystissimplynolongerfeasible.Thisraisestheissueofhowtoextractdesign- relevant knowledge from such a large database of textual information. Chapter 6 discussesbothafullyautomatedandasemi-automatedapproachforaddressingthis issue.Especiallythesemi-automatedapproachseemsverypromising,butsubstan- tialadditionalresearchwillberequiredtosettle theissue. Whilethe problemsare non-straightforward,the potentialimpacton designpractices, andthe related eco- nomicalbenefits,canhardlybeoverrated. Imconvincedthatthisbookwillprovidefoodforthoughtforbothnoviceandex- periencedresearchersanddesignersinterestedincontributingtothenewandgrow- ingareaofuserexperiences.Formepersonally,Ienjoyedverymuchcoachingthe author,EvangelosKarapanosinhisexplorationsthatarereportedinthisbook. Eindhoven,March2012 Jean-BernardMartens Acknowledgements The work described in this book has been carried out under the auspices of the J.F.SchoutenGraduateSchoolofUser-SystemInteractionResearch,andhasbeen sponsored by the Dutch Ministry of Economic Affairs within the IOP-IPCR pro- gram, throughthe Soft Reliability project, under the auspices of Philips and Oce´. Excerpts of this book have been previously published in Karapanos and Martens (2007)andKarapanosetal.(2009a,2008a,2009c,b). Contents 1 Introduction.................................................. 1 1.1 FromUsabilitytoExperience ............................... 2 1.2 TwoDistinctApproachesinUserExperienceResearch.......... 3 1.2.1 ReductionistApproaches............................. 4 1.2.2 HolisticApproaches................................. 6 1.3 DiversityinUserExperience................................ 8 1.3.1 AFrameworkofDiversityinSubjectiveJudgments....... 8 1.3.2 FourSourcesofDiversityinUserExperience ........... 10 1.4 MethodologicalIssuesinAccountingforDiversity ............. 11 1.4.1 UnderstandingInterpersonalDiversitythroughPersonal AttributeJudgments................................. 13 1.4.2 UnderstandingtheDynamicsofExperiencethrough ExperienceNarratives ............................... 14 1.5 ManuscriptOutline ........................................ 15 2 PersonalAttributeJudgments .................................. 17 2.1 Introduction .............................................. 17 2.2 TheRepertoryGridTechnique .............................. 20 2.3 TheQuantitativeSideofRepertoryGrid-SomeConcerns ....... 21 2.3.1 AreWeReallyInterestedinIdiosyncraticViews? ........ 21 2.3.2 OnBipolarity ...................................... 22 2.3.3 OntheMeasurementofMeaning...................... 25 2.4 AnalyzingPersonalAttributeJudgments-AnInitial Exploration............................................... 25 2.5 TheStudy................................................ 27 2.5.1 Method ........................................... 27 2.6 AnalysisProcedure ........................................ 29 2.6.1 IdentifyingHomogeneousUserGroupsinthe User SegmentationMap .................................. 29 2.6.2 ClassifyingAttributesforInterpersonalAnalysis......... 29 X Contents 2.6.3 ChartingPerceptualMapsforHomogeneousGroupsof Users ............................................. 31 2.7 Discussion ............................................... 35 2.8 Conclusion............................................... 38 3 AnalyzingPersonalAttributeJudgments ........................ 41 3.1 Introduction .............................................. 41 3.2 TheStudy................................................ 42 3.3 AMulti-dimensionalScalingApproachtoAccount forDiversity.............................................. 42 3.3.1 IdentifyingtheDifferentViews........................ 44 3.3.2 DefiningGoodness-of-FitCriteria ..................... 44 3.3.3 TwoDiverseViewsforOneParticipant................. 45 3.3.4 AssessingtheSimilaritybetweenDifferentViews........ 48 3.3.5 GroupingtheHomogeneousViews .................... 49 3.3.6 HowDotheDiverseViewsComparetotheAverage View?............................................. 50 3.4 Discussion ............................................... 53 3.5 Conclusion............................................... 56 4 UserExperienceOverTime .................................... 57 4.1 Introduction .............................................. 57 4.2 BackgroundonExperienceandTemporality ................... 58 4.2.1 TemporalAspectsinFrameworksofExperience ......... 59 4.2.2 Beauty,GoodnessandTime .......................... 59 4.3 Study1 .................................................. 60 4.3.1 Method ........................................... 60 4.3.2 Results............................................ 61 4.3.3 Discussion......................................... 64 4.3.4 LimitationsoftheStudy ............................. 65 4.4 Study2 .................................................. 66 4.4.1 TheStudy ......................................... 67 4.4.2 DataAnalysis ...................................... 69 4.4.3 Findings........................................... 70 4.4.4 Discussion......................................... 78 4.4.5 ImplicationsforDesign .............................. 79 4.5 Discussion ............................................... 81 4.6 Conclusion............................................... 82 5 iScale:StudyingLong-TermExperiencesthroughMemory ........ 85 5.1 Introduction .............................................. 85 5.2 ReconstructingExperiencesfromMemory .................... 89 5.2.1 TheConstructiveApproach........................... 89 5.2.2 TheValue-AccountApproach......................... 90 Contents XI 5.2.3 GraphingAffectasaWaytoSupporttheReconstruction ofExperiences ..................................... 91 5.2.4 iScale............................................. 91 5.3 Study 1: Understanding Graphing as a Tool for the ReconstructionofExperiences............................... 94 5.3.1 Method ........................................... 94 5.3.2 AnalysisandResults ................................ 96 5.3.3 Discussion......................................... 101 5.4 Study2:BenefitsandDrawbacksoftheConstructiveandthe Value-AccountVersionofiScale............................. 102 5.4.1 Method ........................................... 102 5.4.2 AnalysisandResults ................................ 105 5.4.3 Discussion......................................... 108 5.5 ConclusionandFutureWork ................................ 110 5.6 Appendix-TemporalTransformation......................... 113 6 A Semi-Automated Approach to the Content Analysis of ExperienceNarratives ......................................... 115 6.1 Introduction .............................................. 115 6.2 AutomatedApproachestoSemanticClassification.............. 117 6.2.1 TheLatent-SemanticAnalysisProcedure ............... 117 6.2.2 LimitationsofLatent-SemanticAnalysisintheContext ofQualitativeContentAnalysis ....................... 119 6.3 ASemi-automatedApproachtoContentAnalysis .............. 120 6.3.1 IncorporatingExistingDomain-SpecificKnowledge...... 120 6.3.2 IterativeOpenCoding ............................... 121 6.3.3 ComputingNarrativeSimilarity ....................... 126 6.3.4 HierarchicalClustering .............................. 127 6.3.5 VisualizingInsights ................................. 127 6.4 ValidationoftheProposedApproach ......................... 129 6.4.1 PreparingtheDataset................................ 129 6.4.2 ConceptAnalysis ................................... 130 6.4.3 Latent-SemanticAnalysisonRestrictedTerms........... 131 6.4.4 TraditionalLatent-SemanticAnalysis .................. 132 6.4.5 ClusterAnalysisonDissimilarityMatrices.............. 132 6.5 Discussion ............................................... 134 6.6 Conclusion............................................... 136 7 Conclusions .................................................. 137 7.1 ContributionsofThisWork ................................. 137 7.1.1 ConceptualizingDiversityinUserExperience ........... 138 7.1.2 EstablishingEmpiricalEvidenceforthePrevalenceof DiversityinUserExperience ......................... 138 7.1.3 ProposingMethodologicalToolsfortheStudy ofDiversity ........................................ 139 XII Contents 7.2 ImplicationsfortheProductCreationProcess.................. 142 7.2.1 IntegratingSubjectiveandBehavioralData.............. 142 7.2.2 TheEndofSpecifications? ........................... 144 7.3 AvenuesforFutureResearch ................................ 144 7.3.1 LeveragingInsightsacrossDifferentExploratory Studies............................................ 144 7.3.2 ComputationalToolsforMakingSurveyResearch Scalable........................................... 145 7.3.3 EmpiricalKnowledgeBasesforFormingDesignGoals ... 146 7.3.4 ANewBasisforUserInsights? ....................... 146 References........................................................ 151