Development
and
Validation
of
Technology
Acceptance
Modelling
for
Evaluating
User
Acceptance
of
an
E
Ͳ
learning
framework
By
YALDA
DANESH
SEDIGH
A
thesis
submitted
to
The
University
of
Birmingham
for
the
degree
of
MASTER
OF
PHILOSOPHY
University of Birmingham Research Archive
e-theses repositoryThis unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation.
Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
ACKNOWLEDGEMENTS
ThisthesishasbeenagreatachievementformeandIwouldliketoacknowledgethesupport ofmysupervisor,DrTheodorosN.Arvanitis,throughoutmystudyandsupportgivenbymy coͲsupervisorDrAlexGibbintheinitialyearofmystudy.Iamgratefulforthefinancialand emotionalsupportfrommyfamily.IwouldalsoliketothankmycolleaguesintheHuman ComputerInteractionResearchCentre.AquestionnairesurveyedbyOudeRengerink’s(2011) aidedthisthesis.ThethesisresearchworkwascarriedoutattheUniversityofBirmingham;I enjoyedthefacilitiesprovidedbytheUniversity,suchastheMainLibraryandaccesstoonline
ABSTRACT
ThethesisaimedtodevelopandvalidateanewtheoreticalmodeltoassessEvidenceBased Medicine(EBM)trainers’technologyacceptanceofaneͲlearningapplicationassociatedtothe EUEBMTeachtheTrainerseͲcourse.ModellinguserinteractionswitheͲlearningapplications allowsthepredictionofhowEBMtrainersaremotivatedtousetheeͲcourseintheclinical setting.Aspartofthisresearch,asurveywasconstructedandanalysedusinganempirical modelcalledtheTechnologyAcceptanceModel(TAM).TheTAMwasdevelopedintotheeͲ TAM,anewmodel,whichcanassessauser’sadoptionofonlinelearningapplications.This thesisusedasurveytodeveloptheeͲTAMasanextensionfortechnologyacceptanceofonͲ linepublicationssuchastheblendedlearningapproachforEBMstudy.Thethesisvalidated theTAMandeͲTAM,whichfollowedanassessmentofEBMtrainers’acceptanceofthe application.Statisticalanalysis,includingreliabilitywithCronbach’sAlpha,factoranalysisand multipleͲregression analysis, were carried out on TAM, eͲTAM and data from the questionnairesthatshowedthemodelswerevalidforthisfieldofstudy.Thisassessment foundtheEBMtrainers’experience,perceivedusefulnessandattitudetowarduseasstrong predictorsofuserbehaviouralintentionandacceptanceoftheapplication.Overall,themost influentialfactorintheeͲTAMmodelwasExperience,whichexplainedoverafifthofthetotal varianceoftheuseracceptanceoftheeͲlearningapplication.
TABLE
OF
CONTENTS
ACKNOWLEDGEMENTSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲI
ABSTRACTͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲII
TABLEOFCONTENTSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲIII
LISTOFFIGURESͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲV
LISTOFTABLESͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲVII
1 INTRODUCTIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ1
1.1 EVIDENCEͲBASEDMEDICINEͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ2
1.2 MOTIVATIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ5
1.3 THEORETICALMODELLINGOFUSERACCEPTANCEͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ6
1.4 ANALYSISOFUSERACCEPTANCEINFORMATIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ8
1.5 AIMANDOBJECTIVESͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ9
1.6 CONTRIBUTIONSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ11
1.7 THESISOUTLINEͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ11
2 BACKGROUNDANDLITERATUREREVIEWͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ14
2.1 INTRODUCTIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ14
2.2 THEUSEOFEͲLEARNINGFOREBMTRAINERSANDITSACCEPTANCEͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ16
2.3 THEORETICALMODELLINGOFUSERACCEPTANCE:FROMTHEORYANDMODELLINGTOPRACTICEANDANALYSISͲͲͲͲͲͲͲͲͲ25
2.4 EXTERNALFACTORSFORTHETAMMODELͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ58
2.5 SUMMARYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ69
3 METHODͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ71
3.1 UNDERSTANDINGTHECORECONCEPTSOFTHEPROJECTͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ71
3.2 TECHNOLOGYACCEPTANCEMODELLINGͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ74
3.3 HYPOTHESESͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ81
3.4 PROPERTIESOFTHEQUESTIONNAIREͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ88
3.5 TESTINGRELIABILITYOFFACTORSWITHINTHEQUESTIONNAIREͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ93
3.6 TESTINGTHERELIABILITYOFTHEQUESTIONSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ95
3.7 FACTORANALYSISͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ97
4 TAMRESULTSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ104 4.1 INTRODUCTIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ104 4.2 RELIABILITYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ105 4.3 FACTORANALYSISͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ107 4.4 REGRESSIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ110 4.5 DISCUSSIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ112 4.6 SUMMARYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ114 5 EXTENDEDTAMRESULTSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ116
5.1 INTRODUCTIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ116 5.2 RELIABILITYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ117 5.3 FACTORANALYSISͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ121 5.4 REGRESSIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ123 5.5 DISCUSSIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ126 5.6 SUMMARYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ132
6 CONCLUSIONANDFURTHERWORKͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ133
6.1 PROPOSEDDEVELOPMENTSFORTTTͲEBMEͲCOURSEͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ134
6.2 OPPORTUNITIESPRESENTEDFORNEWRESEARCHͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ135
6.3 CONSIDEREDFURTHERWORKFORTHISSTUDYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ135 7 REFERENCESͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ137
8 APPENDIXͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ143
8.1 DAVIS’EXPLANATIONOFTHEFISHBEINMODELͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ143
8.2 THETECHNOLOGYACCEPTANCEQUESTIONNAIREͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ146
8.3 IMPLEMENTATIONBARRIERSTOTEACHINGEVIDENCEBASEDMEDICINEINCLINICALPRACTICEQUESTIONNAIREͲͲͲͲͲͲͲͲͲ150
8.4 EͲTAMQUESTIONNAIREFACTORISATIONͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ157
8.5 GLOSSARYͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ160
8.6 TABLEOFACRONYMSͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲͲ161
LIST
OF
FIGURES
FIGURE1:TRADITIONALCLINICALPRACTICEANDIMPROVEMENTCYCLE,REPRODUCEDFROMTHANGARATINAMETAL.(2009)...19
FIGURE2:IMPROVEDLEARNINGANDUSEOFEBMINCLINICALENVIRONMENTWITHADDITIONALLEARNINGRESOURCES,REPRODUCED FROMTHANGARATINAM(2009)...20
FIGURE3:TTTͲEBMEͲLEARNINGCOURSEACCESSIBLEVIATHEINTERNET:MODULE1–WARDROUND...23
FIGURE4:THESIXCLINICALSETTINGSTHATARETAUGHTINTHETTTͲEBMEͲLEARNINGCURRICULUM,REPRODUCEDFROM(ZANREI, 2009)...24
FIGURE5:THEINNOVATIONͲDECISIONPROCESSCOMMUNICATIONCHANNELS,REPRODUCEDFROMROGERS(1995)...28
FIGURE6:ORIGINALVERSIONOFTHEORYOFREASONEDACTION(TRA),REPRODUCEDFROMAJZEN&MADDEN(1986)...31
FIGURE7:THEORYOFREASONEDACTION(TRA),REPRODUCEDFROMAJZEN&FISHBEIN(1980)...32
FIGURE8:SOCIALCOGNITIVETHEORY,REPRODUCEDFROMBANDURA(1986)...34
FIGURE9:THEORYOFPLANNEDBEHAVIOUR,REPRODUCEDFROMAJZENANDCOTE(2008)...36
FIGURE10:THETAMMODELBASEDON(DAVIS,1989)...38
FIGURE11:TAMWITHNUMBEREDLINKSBETWEENTHEFACTORSANDEXTERNALFACTORS,REPRODUCEDFROMDAVIS(1986)...39
FIGURE12:TAM2ͲEXTENSIONOFTHETAM,REPRODUCEDFROMVENKATESHANDDAVIS(2000B)...42
FIGURE13:UNIFIEDTHEORYOFACCEPTANCEANDUSEOFTECHNOLOGY,REPRODUCEDFROMVENKATESHETAL.(2003)...44
FIGURE14:TECHNOLOGYACCEPTANCEMODEL3(TAM3),REPRODUCEDFROMVENKATESHANDBALA(2008)...48
FIGURE15:RESEARCHMODELANDRESULTSOFTHEHYPOTHESISTEST,REPRODUCEDFROMONGETAL.(2004)...50
FIGURE16:THETECHNOLOGYACCEPTANCEMODEL,CONSIDEREDASABASEFORTHENEWMODELBYPITUCHANDLEE,REPRODUCED FROMPITUCHANDLEE(2006)...52
FIGURE17:MODELASHOWS‘FULLYMEDIATEDMODEL’FOREͲLEARNINGUSEDBYPITUCHANDLEE(2006),BASEDONTHETAMWITH EXTERNALVARIABLES...52
FIGURE18:MODELBSHOWSTHE‘PARTIALLYMEDIATEDMODEL’FOREͲLEARNINGUSE,REPRODUCEDFROMPITUCHANDLEE(2006) ...54
FIGURE23:SHOWSTHEEXTENDEDTAM...77
FIGURE24:SHOWSGROUPINGFOREXTERNALFACTORS...78
FIGURE25:SHOWINGEXTERNALFACTORSGROUPINGANDTHEMETHODOFCONNECTIONTOTHETAM...79
FIGURE26:NEWILLUSTRATIONOFTHEGENERALISATIONOFEXTERNALFACTORS,WHEREAGEANDGENDERHAVEBEENOMITTED,AND QUALITYISCONSIDEREDASPARTOFADESIGNDIMENSION...81
FIGURE27:THETECHNOLOGYACCEPTANCEMODEL(TAM),SHOWINGTHEHYPOTHESESASSUMEDFORTHISRESEARCH...83
FIGURE28:EXTENDEDTECHNOLOGYACCEPTANCEMODEL(EͲTAM),SHOWINGTHEHYPOTHESESASSUMEDFORTHISPARTOF RESEARCH...86
FIGURE29:EXAMPLEOFTHELIKERTSCALEFORMATUSEDINTHEQUESTIONNAIRES...90
FIGURE30:THEEXAMPLESOFTHEFITLINE(SAPSFORD,ETAL.,2006)...100
FIGURE31:ANEXAMPLEOFTHECORRELATIONCOEFFICIENT(RͲVALUE)(SAPSFORD,ETAL.,2006)...100
FIGURE32:CRONBACH'SALPHAIFITEMDELETED(CAIID)WITHREDHORIZONTALLINESHOWINGTHESTANDARDISEDCRONBACH’S ALPHA...107
FIGURE33:CORRECTEDITEMͲTOTALCORRELATION(CITC)WITHYͲAXISSETTOMINIMUMRECOMMENDEDVALUE...107
FIGURE34:FACTORLOADINGFOREACHFACTOR1TO4FROMTOPͲLEFTTOBOTTOMͲRIGHT...110
FIGURE35:THETECHNOLOGYACCEPTANCEMODELSHOWSTHEWEIGHTOFEACHFACTORONEACHOTHERWITHAECOEFFICIENT ...112
FIGURE36:CORRECTEDITEMͲTOTALCORRELATIONWITHREDHORIZONTALLINESHOWINGTHEMINIMUMRECOMMENDEDVALUES ...120
FIGURE37:CRONBACH’SALPHAIFITEMDELETEDWITHREDHORIZONTALLINESHOWINGTHESTANDARDISEDCRONBACH’SALPHA120 FIGURE38:PERCENTAGEOFVARIANCEEXPLAINED...123
FIGURE39:THEEͲTAMSHOWSTHEWEIGHTOFEACHFACTORONTHEOTHERONEWITHECOEFFICIENT...126
FIGURE40:SHOWINGTHELIMITATIONSWITHFACTORSANDHYPOTHESESINREDDASHEDͲLINEBOXESANDWITHDASHEDͲLINES...129
FIGURE42:THEDEMONSTRATIONOFTHERELATIONSANDINFLUENCEOFEXTERNALFACTORSONPERCEIVEDUSEFULNESS...131
FIGURE43:THEDEMONSTRATIONOFTHERELATIONSANDINFLUENCEOFEXTERNALFACTORSONPERCEIVEDEASEOFUSE...131
LIST
OF
TABLES
TABLE1:ALISTOFTHEHYPOTHESESTHATDISTINGUISHBETWEENDEPENDENTANDINDEPENDENTVARIABLES...83
TABLE2:LISTOFTHEHYPOTHESESTHATDISTINGUISHBETWEENDEPENDENTANDINDEPENDENTVARIABLES...87
TABLE3:SHOWINGEACHFACTORANDRELATEDCOMPONENTFOREACHFACTORSEPARATELY...89
TABLE4:SHOWINGEACHFACTORANDRELATEDCOMPONENTFOREACHFACTORSEPARATELY...92
TABLE5:AVERAGERELIABILITYANALYSIS...106
TABLE6:RELIABILITYANALYSISINDETAILFOREACHQUESTION...106
TABLE7:ROTATEDFACTORMATRIXOFTAMROTATEDWITHVARIMAXWITHKAISERNORMALIZATIONANDLESSTHAN0.5CUTͲOFFTO DRAWͲOUTFACTORS(DARKGREYSHADE),0.3CUTͲOFF(LIGHTGREYSHADE)...109
TABLE8:MULTIPLEREGRESSIONRESULTOFTECHNOLOGYACCEPTANCEMODEL...111
TABLE9:AVERAGERELIABILITYANALYSIS...117
TABLE10:RELIABILITYANALYSISINDETAILFOREACHQUESTION...119
TABLE11:FACTORLOADINGWITHDRAWͲOUTVARIABLES(DARKGREYSHADE)...122
TABLE12:REGRESSIONRESULTOFEͲTAM...124
TABLE13:THELISTOFTHEQUESTIONSFROMTTTͲEBMEͲLEARNINGCURRICULUM’SQUESTIONNAIREFROMOUDERENGERINK(2011) THATHAVEBEENDROWNEDOUTFORTHEEXPERIENCEPREDICTORINTHEEXTERNALFACTORS...159
1 INTRODUCTION
Medicalpractitionershavetoadaptquicklytolearn,understandandadoptnewtechnology asgeneraltrendsshowacontinuousintegrationoftechnologyandnewmedicalstrategies intotheworkplace.ThereisaneedforthemtolearnhowtouseeͲlearningtechnologiesand associatedinnovativesystemsonaroutinebasis,becausetheintegrationanduseofthese systemsintheworkplacewillimprovepatients’healthcare(OudeRengerink,etal.,2011).This meanstrainersofnewmedicalknowledgeandevidenceneedtolearnhowtoteacheffectively theuseofavailableinformationthrougheͲlearningsystems,suchastheeͲlearningframework for“teachingthetrainersevidenceͲbasedmedicine”(Thangaratinam,etal.,2009).Resulting frombettertraining,medicalpractitionerscanmanagetouseinnovativeapproachesto handleinformationandknowledge,suchasevidenceͲbasedmedicine,whileprovidingbetter healthcarepracticeonadailybasis.Overall,thisdevelopmentintheclinicalenvironmentwill benefitpatientswithbetterdiagnoses,treatment,andfollowupprocesses.
EͲhealthis a new approach tohealthcarepractice andisa frameworkfacilitatedby informationsystemssuchaslibraries,theInternet,onͲlineclinicaldatabases,research databases,decisionsupportinformationsystems,telephonesupportcentres,etc.(Broderick &Smaltz,2003).Thesefacilitiesincreasetheaccessibilityandavailabilityofinformationfor healthcareservices.EͲhealthcanbeintegratedintootherframeworks,suchaseͲlearning.EͲ learningutilisesInformationandCommunicationTechnology(ICT)systemstogiveusers accesstoknowledgeworldwide.EͲlearningletsusersstudywiththeaidofinteractive tutorials,preͲrecordedlecturesandotherdownloadableorstreamingmedia(Arbaugh,2004;
Singh,etal.,2005;Ngai,etal.,2007).TheinnovationofeͲlearningwithinthecontextofeͲ healthinhealthcareinstitutionscantrainhealthcarepractitionershowtouseassociated technologywithoutrestrictionsonthepractitioner’stimeorplace.
1.1
Evidence
Ͳ
based
Medicine
EvidenceͲbasedmedicine(EBM)isamedicalinformationframeworkandconsideredasa subsetofeͲhealthsystems(Eysenbach,2001).EBMcanbesupportedbyICTtechnologies (Schaper&Pervan,2007)andupgradesthetraditionalmedicaltheoryandpracticebyfocusing moreonthespecificneedsofpatients(Coppus,etal.,2007).Withtheaidoftraining,medical professionalscanaccessEBMinformationthroughonlinesoftwareͲbasedtechnologies,as wellasuseandupdatemedicalevidenceasanintegralpartoftheroutine(Kulier,etal., 2008b),asnewtheoriesandpracticesbecomeavailableinrealͲtime(Coppus,etal.,2007; Hatala,etal.,2006).
OnͲlinetrainingsoftwareapplicationscansupportprofessionalstowardstheuseofevidenceͲ basedmedicalknowledge(Kulier,etal.,2008a)andtherebysupporttheintegrationanduse ofEBMintheclinicalenvironment;furtherdiscussiononthistopicinSection2.2.Inaddition, accesstoEBMinformationfromanonlinemedicaldatabaseandsupportwitheͲlearning trainingsessionshasthepotentialtoimprovetheaccessibility,availabilityandawarenessof medicalinformationformedicalprofessionalsandtrainersofEBMintheclinicalenvironment (Coppus,etal.,2007;Hatala,etal.,2006).ItisbeneficialtoutilisetheadvantagesofeͲlearning forEBMstudy,specificallyintermsofitsabilityinprovidingathandinformationonaglobal scale.
Medicalandhealthcareevidence,availablefromonlineeͲlearningenvironments,cansave teachingtimewhenmanypeoplewanttolearntheEBMapproach,invariouslocationsand organisations.Moreover,publishingonlinecantakemediaformsofeͲbooks,andstreaming audioorvideo,whichallowsamorecostͲeffectivewayoflearningEBMcomparedtohard multimediaformslikeCDs,DVDsorbooks(Kulier,etal.,2008a).Whenprofessionalssubmit andauthorEBMinformationfromreliablesources,itprovidesofficialEBMsupportfor practitionersandtrainers(Hatala,etal.,2006).
EBMgivespractitionersasolidreferenceforthedurationoftheofpatientͲhealthcare practitionerinteractionincludingdiagnosis,treatmentandfollowup(Kulier,etal.,2008b). ThatreferenceallowsEBMtoprovideabasisforconvincingbothpatientandpractitionerto maketherightdecisionthrougheachstepinthecontinuityofhealthcare.However,EBMͲ baseddecisionshavealimitedeffectasaconfidencebuilderifthepractitionersareunsure abouttheuseofEBMduetotrainerslackingconfidenceindemonstratingitspotential (Thangaratinam,etal.,2009).TrainerscanteachEBMinvariousways,whichmightexplaina confusionoverwhichcurriculumtofollow(Coppus,etal.,2007).Ifthisisthecase,thenthere shouldbearecognisedandofficialcourseforteacherstouse(Thangaratinam,etal.,2009).
OnͲlinetrainingformedicalprofessionalshasgrownindemandinEurope,whiletheapproach ofeͲlearningneedsapprovalasanofficialqualification(OudeRengerink,etal.,2011).In addition,organisationshaveattemptedtoanalysehowusersacceptsuchsoftwareͲbased systems(Schaper&Pervan,2007)andthereforedevelopeͲlearningsystemstoincreaseits adoptioninhealthcare.
TherearemanybarriersassociatedwiththeuseracceptanceofanonlineEBMtrainingsystem (OudeRengerink,etal.,2011),butthesedonotoutͲweighthebenefitsofitswidespreaduse. Becauseofthis,thethesisconsidersfindinginfluentialbarriers/factorsimportantasitcanaid thedevelopmentofatechnologyacceptancemodelthatcanassesstheTeachingtheTrainers EBM(TTTͲEBM)eͲlearningapproachandtherebyitsadoption.
Thangaratinam(2009)pointedoutthattrainersofEBMshouldusetheavailableclinical environmentalfacilities,teachEBMpracticeanddemonstratehowtoapplytechnology associatedwithEBMineverydayclinicalactivitiesforthebenefitofthetrainees.Inherstudy, thisteachingmethodissetintoacurriculumcalled“TeachingtheTrainersEBM(TTTͲEBM)”, whichprovidesablendedlearningapproach,includinganeͲlearningframework.TheTTTͲEBM projectisalsoknownastheEUEBMTTTprojectinThangaratinam(2009),butthisthesisrefers toitastheformerthroughoutthethesis.TheTTTͲEBMeͲlearningcurriculumanditsblended learningapproachispartofaEuropeanͲwideproject,whichplaysaroleinproviding standardisedcontinuingprofessionaldevelopmentforEBMtrainersacrosstheEuropean Union(Thangaratinam,etal.,2009).ThiscurriculumisaccessedasaneͲcourseandisthefirst example of eͲlearning training system, designed for building trainer confidence and integratinglearningwithintheclinicalenvironment.Itincludeslearningandassessment facilitatedbyeͲlearningtechnology;thereexisteͲmodulesinvolvedwiththeuseofjournal clubs,morbidity/mortalitymeetingsandauditpresentations,whichtogetherisconsideredan eͲcourse.
andTimeConstraintaccountedforoverhalfofthevarianceintheuseracceptanceoftheEBM eͲlearningapplication. Meaning those factors are influentialto the TTTͲEBM project’s adoption.Therefore,thatprojectcanimprovewithdevelopmentsfocusedontheelimination ofnonͲessentialbarriersandtheinclusionorreinforcementoftheinfluentialfactorsshown inthisthesis.
1.2
Motivation
EBMtrainersneedtoteachpractitionerswithconfidence,whichaproposedEuropeanͲwide eͲcoursecangive,whereacceptanceoftheeͲcourse’sapplicationneedstobeassessedto ensureitswidespreaduse.Trainersneedtobemotivatedandconvincedtobeinvolvedwith thatapplicationthatteachesthemhowtoteachmedicalpractitionerstheuseandbenefitsof EBMintheworkplace(OudeRengerink,etal.,2011).However,thereisashortageof appropriatemodelstopredicttheuseracceptanceofthateͲlearningapplication.Therefore, thisthesisproposesanewmodelforuseracceptanceassessmentoftheTTTͲEBMeͲlearning curriculum,deliveredviatheeͲcourse.
TheneedforEBMtoachieveimprovedqualityhealthcarehasbeenacceptedandpublished inmanycountries,especiallyinEuropeanjournalssuchasfromDawesetal.(2005),Daviset al.(2007),andCoppusetal.(2007).Ideally,theoutcomesoftheTTTͲEBMprojectwillhelp EBMtrainersimproveclinicalstaff’sknowledgeandskillsofEBMpracticeineverydayclinical activities.Thus,movinghealthcareandmedicalprofessionalstoupgradeEBMknowledge independently,asKulier(2008b)hadpointedout.Hence,thecentralobjectiveofthisthesisis toevaluatetheuseracceptanceandassociatedhumanfactorconsiderationsforintegrating theTTTEBMblendedeͲlearningapproachfortheworkplace.
Theworkofthisthesiscontributedtouseracceptanceoftechnologyresearchbyeliminating irrelevantbarriersandfindinginfluentialfactorsofauser’sacceptanceoftheTTTͲEBM project.TheTTTͲEBMprojectimprovestheEuropeanhealthcaresectorthroughthedesign, development,promotionandpilotingofaEuropeantrainingprogramme(Thangaratinam,et al.,2009;OudeRengerink,etal.,2011).ThatTTTͲEBMprojectfocusesonteachinghealthcare trainersofEBM,throughanintensiveintegratedeͲlearningcurriculumwithinaclinical practice.ThedesignofthecurriculumandblendedeͲlearningcourseshouldbebeneficialfor theflexibilityofthetrainers’timeandplace.Thisthesisfocusesonhowtoimprovethequality of that project by evaluating factors that influence acceptance, future attitudes and behaviouralintentionsofusersenrolledontheTTTͲEBMeͲlearningcurriculum.
ModellingandpredictinghowusersaccepttheeͲlearningapplicationisafocusofthisthesis, whichitattemptstoassesswiththedevelopmentofatechnologyacceptancemodelsand associatedfactors,Section1.3furtherdiscussesthispoint.Themodelsdevelopedinthethesis evaluatesurveysofprofessionalcliniciansinthescopeoftheTTTͲEBMproject,namelyfrom Europeanclinicians.Inthisthesis,oursurvey,althoughsmallinscale,takesapanͲEuropean perspectiveofevaluatingtheTTTͲEBMeͲlearningframeworkanddevelopsawidelyaccepted empiricalmodeltodetecttheinfluenceofbarriersassociatedtoauser’sadoptionoftheeͲ course.
1.3
Theoretical
Modelling
of
User
Acceptance
TheTechnologyAcceptanceModel(TAM)isawellͲrecognisedempiricalmodelforitsability inpredictinghowandwhyITandcomputersystemsusersapproach,startandcontinueusing
typeoftechnology(Davis,1986).TheTAMhasevolvedintotheTAM2(Venkatesh&Davis, 2000b)andTAM3(Venkatesh&Bala,2008),withtheimplementationofadditionalfactors (formoredetail,seeSection2.4).Theseadditionalfactorswereusedtoproduceresultsthat arebettersuitedforspecificcontextssuchasauser’sexperience(Venkatesh&Davis,2000b; Venkatesh&Bala,2008),jobrelevance(Venkatesh&Davis,2000b;Venkatesh&Bala,2008) andcomputerselfͲefficacy(Venkatesh&Davis,1996;Venkatesh&Davis,2000b)aswellasto furtherexplainthevarianceofuserbehaviouralintentionoftheTAM’soriginalfactors. NumerousotherstudieshavedevelopedtheTAMwithadditionalfactorsofuseracceptance oftechnologyinhealthcareITtoprovideaspecificresearchmodeltofitastudyarea(Holden &Karsh,2010).ThefactorsthatthisthesisconsidersfordevelopingtheTAM,alsocalledsocial organisationalbarriers(OudeRengerink,etal.,2011),includeapparentchallengesand limitationsoftheclinicalenvironmentformedicalstaffandtrainers.Holden&Karsh(2010) reviewedthelimitationsoftheTAMandfoundareasofhealthcareITrelatingtoeͲlearning andInternetbasedsystemssuchaswebͲbasedelectronicmedicalrecords,mobilemedical informationsystems,onlinedisabilityevaluationsystems,telemedicinetechnology,ICTand InternetͲbasedhealthapplications.HethenevaluatedthosefactorswiththeTAM.
DevelopingtheTAM’scontextualassessmenttosuitablendedlearningapproach,byadding factorsrelatedtoeͲlearninginthehealthcarecontext,isnecessarybecauseitwouldmakeit avalidmodelforusersassociatedwiththisthesis,whereasDavisdevelopedtheTAMtoassess ITandcomputersystemusers(Holden&Karsh,2010).EventhougheͲlearningapplications areasubsetofITandcomputersystems,EBMandtheconceptofTTTͲEBMcanfunction independentofITandcomputersystems,whichmeansusingtheTAMtoassessusersofthe
eͲcoursewouldnotnecessarilyfitwithintheoriginalscopeoftheTAM.Thisclarifiesthe reasoningtodeveloptheTAMwithadditionalfactorstoachieveastrongerpredictionofthe useracceptanceoftechnologyfortheapplicationbecausenoothermodelshavetheunique abilityforassessingusersinthisspecificcontext.Anoutputofthisthesisisthedevelopment ofanextendedtechnologyacceptancemodel(eͲTAM),whichincludesthechosenadditional externalfactors.Section3.2.2hasmoreinformationonthedevelopmentanddefinitionofthe eͲTAM.
1.4
Analysis
of
User
Acceptance
Information
Theoreticalmodelsrepresentatheoryandresearchersassumethatthemodelcanpredictan outcomeofthetheoryoridentifyinfluentialfactors,suchaspredictingusersacceptingeͲ learningtechnologiesinthehealthcaresetting,byanalysingindividualdatafrommultipleͲ choicequestionnaires.Thetheoreticalmodel’sanalysisshowstheinfluenceoffactorsrelated bypredeterminedhypotheses,whichfitaroundthemaintheoryofthesubject,whichinthis thesisistheacceptanceoftechnologyandapproachtodeliverEBMtraining.Hypothesesand questionnaires,similartoresearchmodels,needadesignthatisspecificfortheresearch purposestogetreliableresultsforthemodeltoanalyse(seeSection3.4).Thisthesishasused twoquestionnairesdesignedinmindofunderstandingtheuseracceptanceofeͲlearning technologiestostudyEBMinaclinicalsetting.OudeRengerink(2011),whoconstructedone ofthequestionnairesfromaliteraturereview,distributed,surveyedandtestedit“usingthe nonͲparametricKruskal–WallistestortheWilcoxonRankSumtest”.Thattestfoundbarriers andfacilitatorsofteachingEBMinclinicalenvironments.
PreͲtestingquestionnaires,withareliabilityanalysis,isnormallyapreͲrequisiteinthedesign processofquestionnaires.Itvalidatestheresultsandassesseswhethereachquestion achievesthesamescorewhenputunderdifferentconditionsfromthesamecandidates,or fromdifferentcandidatesunderthesameconditions(Bailey&Pearson,1983;Kripanont, 2007;Field,2009).Moreinformationontheuseofreliabilityanalysis,inthisthesis,iscovered inSection3.5.TheCronbach’sAlphaapproach,asusedinthisthesis,seeSection3.5,iswidely usedforreliabilityassessmentbecauseithasbeenrecognisedasoneofthemostsignificant testsofreliabilityinvariousfieldsofsocialscience(Cortina,1993).Thereliabilityofthe questionnaire directly relates to the qualityof the resultsfromtheresearchmodels’ evaluation.ThisthesishasvalidatedbothquestionnairestosupporttheTAMandeͲTAM models’resultsandfindings.
Usingtechnologyacceptancemodels,suchastheTAM,facilitatesthecollectionofdatafor examiningwhichfactorhasaninfluenceontheuser’sadoptionoftheTTTͲEBMeͲlearning applicationanddrawsoutbarrierstowarditsacceptance.Thisthesispredictsuserbehaviour, intention,attitude,useracceptanceandadoptionofanonlineapplicationfortrainerstoteach EBMinaclinicalenvironment.ThisincludestheselectionoffactorsassociatedtoeͲlearning, aswellasanalysisofresultsfromtworesearchmodels(TAMandeͲTAM).Thisevaluationalso quantifiestheeffectofimportantbarriersthatimprovetheadoptionoftheTTTͲEBMeͲ learningapplication.
1.5
Aim
and
Objectives
Theaimofthisthesisinvolvesthetheoreticaltestingoffactorsforthedevelopmentofthe TAMintoamodelthatassessesablendedlearningapproachtowardteachingEBMtrainersin
aclinicalsetting.Thefactorscomefromanevaluationofpreviousresearchmodelsanda literaturereviewbasedoneͲlearning,EBMandTTTͲEBM.Thisstudyhasestablishedthe followingobjectivestoreachthataim:
x todrawͲouttheinfluentialfactorsoftheTAMandeͲTAMthathavearoleontheuser acceptance,futureattitudesandbehaviouralintentionsofusersoftheblended learningapproachadoptedintheTTTͲEBMproject x tofindandevaluatethemostinfluentialfactorsoftheTAMandeͲTAMforpredicting theuseracceptanceoftheblendedlearningapproach x tocriticallyselectsuitableexternalfactorsforuseinthedevelopmentoftheTAMthat havebeenweighedasbarriersineͲlearning x toevaluatetheTAM’sabilityinassessingindividualdataontheuseracceptanceofa blendedlearningapproachtoEBMstudy
x toevaluatetheeͲTAMinassessingtheuseracceptabilityoftheblendedlearning approach
x touseapretestedquestionnairetovalidateTAMandassesstheuseracceptanceof theTTTͲEBMprojectanduseanotherquestionnairetovalidatetheeͲTAMtofindout themostimportantbarriertoTTTͲEBM x toprovideabasisforotherresearchersinterestedincontinuingthedevelopmentof researchmodelsandimprovementoftheblendedlearningapproach x toprovideinsightintohowtheeͲlearningapplicationcanbeimprovedforthebenefit ofmedicalpractitionersandthetrainer’suseoftheapplication
1.6
Contributions
ThisstudydesignedaquestionnairefortheTTTͲEBMeͲlearningcurriculumandblended learningapproach,andusedittostudyandevaluatetheTAM.Adifferentquestionnaire designedbyOudeRengerink(2011)wasusedtoevaluatetheeffectivenessoftheeͲTAMin assessingtheuseracceptanceoftheTTTͲEBMeͲlearningapplication.Itsresultscontributeto researchinvolvedwiththeevaluationofbarriersandfactorsfortheuseracceptanceeͲ learningtechnologiesassociatedtoeͲhealthormorespecificallyEBM,wheredesignershave blended the study material into the workplace. The thesis’ results are beneficial to developmentoftheTTTͲEBMeͲlearningapplicationbecauseithaspredictedtheeͲcourse’s useracceptance. Thereiscontributiontotheoreticalmodellingdesignanddevelopmentresearchbydeveloping theTAMwithexternalfactorsandanestablishmentofanewmodel,theeͲTAM.Thisthesis criticallyreviewedawiderangeofresearchthathadevaluatedtheeffectofaddingexternal factorstotheTAManditsuseinassessingeͲlearningapplications.
1.7
Thesis
Outline
1.7.1 SecondChapter:BackgroundandLiteratureReview
Sufficientliteratureandbackgroundknowledgeisreviewedtounderstandthemeritsof similarresearchtothisthesisandtofindpotentialgapsortheoriesthatareunexploredinthe contextofdevelopingtechnologyacceptancemodels,eͲlearning,EBMandTTTͲEBM.The literaturereviewinSection2.4coverspotentialexternalfactorsthatotherresearchhas evaluatedtheuseracceptanceoftechnologyindifferentmodels,wheresomeareasof researchrelatedtowebͲbasedlearningoreͲlearning.
1.7.2 ThirdChapter:Methods
TheinformationfromChapter2exploresthecoreconceptsofdevelopingmodelsofuser acceptanceoftechnologyforeͲlearningapplications.Thisfollowsthedesignanddevelopment oftworesearchmodels,theTAMandeͲTAM,twoquestionnairesandthreeanalysismethods, reliability,factoranalysisandregression;usedtoevaluatetheuseracceptanceoftechnology.
1.7.3 FourthChapter:ResultsTAM
ThischapterprovidesandexplainstheresultsoftheTAM’sevaluationoftheeͲcourse.It showshowthisstudyidentifiedthemostinfluentialfactorusingreliability,factorand regressionanalyses.Finally,anyanomaliesintheresultsareexplored,whichareexplained withreferencetopastworksofotherresearchers.
1.7.4 FifthChapter:eͲTAMResults
ThischaptershowsthedevelopedTAMmodel,theeͲTAM,anditsassessmentinbeingable toevaluatetheuseracceptanceoftechnologyforeͲlearningapplications.AthreeͲstage analysisprocessofreliability,factorandregressionisusedtoevaluatethepredictivestrength ofthenewmodelandbringoutanyweaknessforfurtherdevelopment.Themostinfluential factoroftheeͲTAMisidentified,whichconstitutesasthegreatestbarrierforuseradoption oftheTTTͲEBMeͲlearningapplication.
1.7.5 SixthChapter:ConclusionandFurtherWork
ThefurtherworkchapterprovidesusefulinsightintohowtheTTTͲEBMprojectmayimprove withtheknowledgegeneratedinthisthesis.Newopportunitiesarepresentedforresearchers
potentialflawsoftheeͲTAMandquestionnaires,aswellasexploringhowresearcherscould
2 BACKGROUND
AND
LITERATURE
REVIEW
2.1
Introduction
EvidenceͲbasedmedicine(EBM),whenusedeffectivelybymedicalpractitioners,isconsidered beneficialforthequalityofhealthcare(OudeRengerink,etal.,2011),jobperformance competency(Hatala, etal.,2006)andethics of medicalpractitionersapproaching the decisionͲmakingprocessofpatientͲpractitionerinteractions(Thangaratinam,etal.,2009). ThereisalargenumberoflearningresourcestoteachEBMuse,whichmayconfusethetrainer ofwhatcurriculumtofollow(Coppus,etal.,2007).Moreover,thereisaneedformodelling andpredictionofhowEBMtrainersteachmedicalpractitionerstouseEBMinclinical environments.Anapproachtothischallengeismodellingthetrainer’sacceptanceofa blendedlearningapproachtoEBMstudy.
EBMtrainers,astheirprofession,areresponsibleforprovidingmedicalpractitionersan approachtopracticeEBMandrelatedtechnologiesinworkplaces.Thiscreatesalinkfromthe traininggivenbyEBMtrainerstothebettermedicalpracticereceivedbypatients.Becauseof thislink,wewanttoknowandquantifythetrainers’barriersassociatedtoEBMteaching.
TheidentificationofbarriersaffectingEBMteachinginvolvesanassessmentoftriedand testedmethodsinsimilarareas.Factorscanrepresentbarriersforuseinaresearchmodel; Section2.4discussesthecategorizationoffactors.Establishingaresearchmodeloftrainers’ acceptanceofinnovativeEBMtrainingmethodscanprovideasolidbasistoimproveEBM trainers’teachingmethods.UltimatelyitisassumedtheoutcomesofbetterEBMtraining
methodsreflectinmedicalpractitionersprovidingbetterEBMutilisationandtherebythe patientsreceivingbetterhealthcare.
Publishedresearchfromthe1950’suptothepresenttimehaveshownthedevelopmentof modelsthathavebecomeincreasingabletopredicttheuseracceptanceofinnovative technologies,wherepresentͲdaymodelscanassessuseradoptionofeͲlearningtechnology andsystemsassociatedtoeͲhealthorhealthcare.Outcomesofpreviousdevelopmentonuser acceptancemodellinghasshownageneraltrendoffittingmodelstospecifiedusersor applications ͲsuchasmodellingtrainerstofurtherdeveloptheinnovationprocessofeͲ learningapplications,asdiscussedinSection2.4.Byfurtherunderstandingthereasonsbehind theoutcomesofrelevantresearchmodels,whendevelopingones’ownmodel,itispossible tohaveabetterapproachtomodellingbyavoidingthepitfallsandsetbacksofprevious researchers.Moreover,theselectionofexternalfactorsfrompreviousresearchgivesa backgroundtocompareresultswiththisthesis.
Theliteraturereviewaddressesthreeresearchareasassociatedtodevelopingmodelsthat predictuserbehaviouralintentionandassessmentofEBMtrainersthatteachmedical practitionersinaclinicalenvironment.Thefirstsection,whichexplainstheneedsofpatients, medicalpractitionersandEBMtrainers,addressestheuseofeͲlearningforEBMandTeach theTrainersEBM(TTTͲEBM),whereSection2.2.4explainsmoreabouttheTTTͲEBMproject. Thesecondsectiondescribesandexplorestheoreticalmodellingincludingmodelsthatcan assessauser’sacceptanceoftechnology.Thissectionalsodiscussessimilaritiesofthe differentpropertiesofthemodels,suchasfactorsandhypotheses,aswellaswhatfeatures ofthemodelsarebetteratassessingtheuseracceptanceofinnovativetechnologiesincluding
eͲlearning.Thefinalsectiondiscussesandanalysestheimportantexternalfactorsconsidered asbarriersorfactorsinresearchjournalssuchasAjzenandFishbein(1980),Davis(1986), Masrom(2007),Thangaratinam(2009),OudeRengerink(2011)andmanyotherstudies associatedtotechnologyacceptancemodelling.Thesechosenexternalfactorsareusedinthe developmentoftheeͲTAMmodel,whichfitstheusersoftheTTTͲEBMeͲlearningprojectand isillustratedinSection3.2.2.
2.2
The
use
of
e
Ͳ
Learning
for
EBM
trainers
and
its
acceptance
KnowledgeofeͲlearningandhowusersfeelaboutusingitasateachingtechnologyapplication leadstounderstandinghowclinicianscanintegratethelearningintoaclinicalsetting(Sun,et al.,2006;Saadé&Kira,2009;Pituch&Lee,2006).HereareafewwellͲknownbenefitsofeͲ learninginthecontextofthisthesis: x EͲlearningfacilitatesuserstolearncoursesthatareaccessibleonline,whichprovides flexibilityoftimefortheEBMͲtrainerstolearn(Sun,etal.,2006;Ong,etal.,2004). x EBMcanbesourcedonaneͲlearningframework,whichgivesEBMͲtrainersthe
freedomoflearninginfrontofanyInternetͲenabledcomputer(Sun,etal.,2006; Masrom,2007).
x AneͲlearningqualification,onhowtoteachEBMtomedicalpractitioners,gives conformitytoEBMͲtrainersonhowtoteach(Thangaratinam,etal.,2009;Oude Rengerink,etal.,2011;Coppus,etal.,2007).
Generally,eͲlearningcanbeusedforInternetͲenabledlearningofvarioussubjectsandhas increasingimportanceinteachingsystems(Pituch&Lee,2006;Sun,etal.,2006;Ngai,etal., 2007).TheadoptionofeͲlearningintoinstitutesworldwidehasseenanincreaseinrecent years(Sun,etal.,2006;Saadé&Kira,2009).AccordingtoareportfromtheInternationalData Corporation,theeͲlearningmarketintheUnitedStateshadanestimatedincreasefrom$2.2 billionto$23billionfrom2000to2004(Pituch&Lee,2006).EͲlearningisconsideredasan opportunityforhighereducationstudentstodevelop.Eventhoughithasadvantagesover traditionaleducation(Sun,etal.,2006),itisnotconsideredasareplacementforthe traditionalclassroomcourses(Masrom,2007).
2.2.1 EͲLearning
EͲlearningsystemsuseICT(InformationCommunicationTechnology)tofacilitatelearning, whichisbeneficialfordistancelearners,learnerswithlimitationsoftimeandplaceaswellas learnerswholiketolearncollectivelyorasagroup.Similartotheabovestatement,Singhet al.(2005)mentionedthattherearevariouswaystodefineeͲlearning,suchasdistance learning,onlinelearningandnetworkedlearning.TheIEEELearningTechnologyStandard CommitteedescribeseͲlearningasasystemsimilartowebͲbasedlearningsystems,where userscanaccessandlearntheircoursematerialonline.Peoplemayaccessthissystemthrough webͲbrowsers,whichisaninterfaceforuserstolearnandpracticewithapplications(IEEE, 2009).EͲlearningusesICTsopeoplecanaccessinformation,suchasmedicalrecords,that administratorscouldstoreonasingleserver,whichisalsoupdatablefromadistance. ThereforeusingICTforteachingandlearningpurposesisalsoconsideredeͲlearning(Masrom, 2007).Thesefeaturesfacilitateandsupportlearningforamasspopulation.
TherehavebeenmanystudiesonthebenefitsofeͲlearning,suchasshowninHofmann (2002),KekkonenͲMonetaetal.(2002),Pituch&Lee(2006)andNgaietal.(2007).KekkonenͲ Moneta(2002)foundstudentsfromeͲlearningclasseshaveasimilarprogressasagroupin faceͲtoͲfacelectures.InfavourofeͲlearning,Hofmann(2002)stateddistancelearningwas betterduetousersneedingatobecome“activelearners”,ortodevelopahighselfͲesteem tolearnindividuallywithoutforcefromateacherorsupervisor.Pituch&Lee(2006)also statedeͲlearningasbettersuitedtodistancelearnersbygivingtheuserfreedomoftimewith advantagesofprovidingsynchronousorasynchronouscommunicationbetweenteacherand student.Moreover,Ngaietal.(2007)foundthatstudentshaveapositiveapproachtoonline learningandbetterlearning outcomesusingeͲlearningandWebCT(TheUniversityof Birmingham,2012)comparedtolectureͲbasedcourses.Overall,theyshowedthateͲlearning enablesflexibilityofstudy,studyimprovementaswellasreductionofcostsforacademic institutions(Ngai,etal.,2007).
2.2.2 LearningEBMwitheͲlearning
ThefundamentalsandreasoningbehindtheuseofEvidenceͲBasedMedicine(EBM)were discussedinSection1.1.EBMisamedicaldecisionͲmakingapproach,enablingpractitioners toimproveandevaluatepatientcarebyfindingthebestavailableevidencethroughthe considerationofupͲtoͲdateavailableinformation(Kulier,etal.,2008b;BMJPublishing,2009). TeachingandlearningEBMinaneͲlearningtrainingenvironmenthassimilaradvantagesto otherlectureͲbasedlessons.Davisetal.(2007)foundequalknowledgegainsbetweeneͲ learningandtraditionalcourses,whereasNgaietal.(2007),inaliteraturereview,found
conferences,workshops,journalclubs,educationalmeetings,includinghavingaccessto medicalliteratureandguidelines(Khan&Coomarasamy,2006;Thangaratinam,etal.,2009).
Figure1:Traditionalclinicalpracticeandimprovementcycle,reproducedfrom
Thangaratinametal.(2009)
Figure1illustratesthetraditionalapproachtoimprovingmedicalpracticeintheclinical environment (Thangaratinam, et al., 2009). Theprocess involves medicalpractitioners assessing patients’ problems by using their experience and understanding of medical practices.Fromthat,theymakeadecisiononadiagnosis,andtheprocesscontinueswitha selfͲimprovementcyclefromtreatmenttofollowup.AsignificantlimitationofthisEBM frameworkisthelackofupͲtoͲdateknowledge,thelackofevidencetorecogniseapatients’ problemandthelackofsolutionsforit(Hatala,etal.,2006).ThestudyfromHatalaetal. (2006)highlightstheneedforEBMtobeintegratedintotheworkplaceandtaughtforusein clinician’sdailyactivities.Hatalaetal.(2006)suggestEBManditstrainingfacilitiesbe improvedtoincreasethequalityofthedecisionmakingprocessinclinicalpractice.
Figure2:ImprovedlearninganduseofEBMinclinicalenvironmentwithadditionallearning
resources,reproducedfromThangaratinam(2009)
AnimprovementmodeltoFigure1isFigure2,whereseveralEBMlearningprocessesare proposedtobeblendedintotheworkplace(Thangaratinam,etal.,2009).Thisincludesa blendedlearningapproachwitheͲlearningcoursesthatdirectlyrelatetoEBMpractice.Such eͲcoursesincludeauditmeetings,journalclubs,mortalitymeetingsandwardrounds.The
2006).CliniciansshouldlearntoworkwithEBMsotheycanutilisethebenefitsofimproved jobperformanceandapproachmedicaldecisionswithconfidence,butmoreimportantly, trainersneedtotrainclinicianstouseEBMwithoutitdisturbingclinicians’workflow.The impactofpredictingthetechnologyacceptanceoftheblendedlearningapproachwithaneͲ coursewouldalloweͲlearningdesignerstodevelopanapplicationthatfitstheneedsof cliniciansandtheirroutine.
2.2.3 ImprovingEBMusewithTTTͲEBM
TrainershavetraditionallytaughtmedicalpractitionersEBMoutsidethecontextofthe trainees’workplace;thishascausedagapbetweenlearningandpractice(Korenstein,etal., 2002).Korensteinetal.(2002)undertookastudythatwouldchangethecurriculaofEBM trainers,byplacingEBMtrainingintotheclinicalsetting.Dawesetal.(2005)alsostudiedthe skillsandtrainingneededtopracticeEBMapproachesandcurricula.Intheirdiscussion,they pointedouttheneedforcleartrainingthatconnectstoskills:peoplewhoworkinhealthcare organisationsneedtohavetheabilitytoprocessnewknowledgebyobtaining,quantifying, usingandinvolvingitintheirjobs(Dawes,etal.,2005).Meaningtheircareerswillinvolve takingonprogressivedevelopmentsofevidence,trainingandpractices.
Davisetal.(2007)studiedcomputerͲbasedlecturingforpostgraduatesandundergraduates. InsupportofKekkonenͲMoneta’s(2002)results,Davisetal.showedthatcomputerͲbased teachingisasͲgoodͲasfaceͲtoͲfacelecturingforEBM.ThetwostudiesfromDavishave introducedcomputerͲbasedteachingasaneffectiveandinnovativemeansofteachingEBM. ComputerͲbasedlearningandteachinghasanadvantageoverfaceͲtoͲfaceteachingand learningasfollows:
x Flexibilityintimeandworkplace
x Interactiveforlearnerswithcontrollableprogresssuchaspauseorrevise x Standardisedteachingqualityforamassaudience
LearnershaveaprovenacceptanceofEBMwhileusingcomputerͲbasedteachingsystems (Davis,etal.,2007).TheirresultshighlightsthatcomputerͲbasedteachingoreͲlearning systemscanbeusedtoreachthesamelearningoutcomesasthetraditionalapproach.
ThetrainersofEBMcanbothgivetraditionalandeͲlearningcoursestomedicalpractitioners, buttrainersmustunderstandthedifferentcontextsoftheirtrainingsessions.BeforetheTTTͲ EBMprojectinitiated,theneedtomovetheteachersfromstandalonecoursestomore integratedworkͲbasedteachingwasprovenbyotherstudiessuchas,DelMaretal.(2004), KhanandCoomarasamyin(2004;2006),Coppusetal.(2007)andThangaratinametal.(2009). Theseauthorssummarisedthereasonsforthiskindoftrainingbecausetrainershadalackof confidence:
x IndemonstratingEBMintheworkplace
x InteachinghowtoapplyEBMatthesametimeasotherclinicalactivities
x InunderstandingabouttheavailableopportunitiesandfacilitiestoteachEBMina clinicalworkplace to distinguish, incorporate and applyupͲtoͲdate evidence to improvehealthcare
2.2.4 TTTͲEBMeͲlearningcurriculum
deliveryofEBMtrainingsessionsineverydayclinicalpractice.Thiscurriculumaimstohelp cliniciansbecomingfamiliarwiththefacilitiesavailabletotrainEBM,suchasonlinelearning inamultimediaformatseeFigure3,andtherebygivethemconfidenceinprovidingtheEBM trainingcourse.AmainobjectivetotheTTTͲEBMprojectistostandardizeaEuropeanͲwide curriculumofteachingEBMinclinics,whichisintegraltoclinicians’workschedule.Thecourse useseͲlearningtoincorporatetrainingandonthejobpractice,whilecarryingoutroutine tasks,whichgivesthedoctorsflexibilityoftimeandplace.TheoverallgoalisthiseͲlearning applicationincreasesEBMtrainers’confidenceleadingtothedeliveryofbetterhealthcare provisionandorganisationsthatbenefitthepatient(Zanrei,2009).
Figure3:TTTͲEBMeͲlearningcourseaccessibleviatheInternet:Module1–WardRound TheTTTͲEBMeͲlearningcurriculumcontainssixstepsthatareaccessibleinfivedifferent languagesandcoveredinthefollowingsequentialorder:wardround,evidenceͲbasedjournal club,formalclinicalassessment,outpatientclinic,formalclinicalmeetingsandclinicalaudit meetings(Thangaratinam,etal.,2009)assowninFigure4.Eachcoursecomprisesofdifferent
learningmaterialincludingvideoclipsofrealworldEBMpracticeandeͲlearningcontentto informhowtoteachEBM,whichalsoprovidesresourcesonthemodules(Zanrei,2009).An exampleoftheeͲlearningpartofonemoduleincludesa10–15minuteseminarfollowedby anonlinemultipleͲchoicequestiontest. Figure4:ThesixclinicalsettingsthataretaughtintheTTTͲEBMeͲlearningcurriculum, reproducedfrom(Zanrei,2009) TheTTTͲEBMprojecthasasitsmainpurposetohelpEuropeanhealthcareoverall.Asstated intheintroductionofthisthesis,thisstudysupportstheaimsoftheTTTͲEBMprojectby developingtheTAMintoamodelthathasfactorstoassessEBMtrainers’acceptanceofan eͲlearningapplication,wheretheTTTͲEBMdesignedtheapplication.InChapter4and Chapter5,thisstudyusedtechnologyacceptancemodelstoanalysequestionnairesrelatedto theTTTͲEBMproject,wherethequestionnaires’studygroupwereEBMtrainers.Asignificant outcomeofthosechapterswasnotjustevidencetosupportthemodels,butalsoprovided resultsthattheTTTͲEBMprojectmayusetoimprovetheuseracceptanceoftheireͲlearning
2.3
Theoretical
Modelling
of
User
Acceptance:
From
Theory
and
Modelling
to
Practice
and
Analysis
EBMͲtrainerscanuseeͲlearning’sadvantagesoftimeandplaceflexibilitywhenstudyingEBM; however,thedisadvantageistheymustacceptnewtechnologyintotheirworkinglives.Design anddevelopmentoftheoreticalmodelsfacilitatesthemeasurementofauser’sacceptanceof technology.Auser,beingeithermedicalpractitionerorEBMͲtrainer,willhaveindividual reactionstotechnology.Thesereactionsareclassifiedintobehaviouralconstructs,alsoknown asfactors,whichEBMcoursedesignersormanagerscantrytoinfluence,orbarrierstheycan reducetoimprovetheirsystem.
Researchersoftendeveloptheirowntechnologyacceptancemodelbasedonempirical evidenceorknowledgeofestablishedmodels,suchastheTechnologyAcceptanceModel (TAM)seeSection2.3.1.5.Theymaydevelopamodelintoamodelthathasfactorsspecificto theapplication,whichrepresentsademographicusergroup’sacceptanceoftechnology,such asNgaietal.’s(2007)modelfortheacceptanceofWebͲbasedlearningsystems.Section2.3.2 showssomeotherapplicationspecificmodels. Varioussourcesofresearchtrytoexplainpeople’sbehaviour,intention,beliefandattitude towardsusingtechnology.Researchinthisfieldhasdevelopedtheoreticalframeworksofuser technologyacceptancetoimprovetheusers’adoptionofnewtechnology,suchaseͲlearning systems.ThissectionofthechaptercontinueswithexamplesofsuchstudiesinthefieldofeͲ learning,andtheuseoftheassociatedtechnologyacceptancetheories.Thesebuildupa stronginformationbasisforthedevelopmentofaspecificmodelforusewithinthecontextof theTTTͲEBMblendedeͲlearningapproach,asdiscussedinSection2.4.
2.3.1 TheoryandModellingofUserAcceptanceofTechnology
Thissectiondiscussesthefollowingfrequentlycitedeightresearchmodelsrelatedtouser behaviourassessment: x InnovationDiffusionTheory x TheoryofReasonedAction(TRA) x SocialCognitiveTheory x TheoryofPlannedBehaviour(TPB) x TechnologyAcceptanceModel(TAM) x TechnologyAcceptanceModel2(TAM2) x TheUnifiedTheoryofAcceptanceandUseofTechnology x TechnologyAcceptanceModel3(TAM3) ThereviewconsiderstheTAM’sdevelopment,aswellasstudytheuseandpredictivepower of other wellͲknown models for user acceptance of technology. This study uses this informationtodevelopanewmodel.
2.3.1.1 InnovationDiffusionTheory
InnovationDiffusionTheoryexplainstheinnovationͲdecisionprocess(Kripanont,2007),being theeventsleadinguptotheacceptanceorrejectionofusinganinnovation.Rogers(1995) developedandimplementedthistheoreticalmodel.Itistheprocessofadaptinginnovation bypredictinghowusersadoptit,haveanattitudetowardit,decidetoacceptorrefuseit,put ittoeffectiveuseandvalidatetheirreasontouseit(Rogers,1995;Kripanont,2007).The
Innovationdiffusioncansucceedusingaprocessoffivestepsovertime,resultinginadecision makingprocessasshowninFigure5.Rogers(1995)cameupwiththefollowingelementsin theprocess: 1. KnowledgeͲauser’sunderstandingoracquaintancewithaninnovation 2. PersuasionͲanindividual’spositiveornegativeattitudetowardsinnovation 3. DecisionͲanindividualweighsadvantagesanddisadvantagesofacceptingorrejecting aninnovation 4. Implementation–auserstartsusingtheinnovationͲithelpstheindividualrealisethe usefulnessoftheinnovation
5. Confirmation Ͳwhentherelationbetweenaninnovationandauser'sdecisionis verified
Figure5:TheInnovationͲDecisionProcessCommunicationChannels,reproducedfrom
Rogers(1995)
Venkatesh(2003)presentedtheapplicationofInnovationDiffusionTheorywithsevencore constructs,basedonMooreandBenbasat’s(1991)studyofindividualtechnologyacceptance
1. RelativeAdvantage–howmuchitisperceivedasbeingbetterthanpresentorpast technology
2. EaseofUseͲhowmuchitisperceivedasbeingdifficulttouse
3. Image Ͳhowmuchtheuseofitisperceivedtoenhanceone’sreputationorsocial status 4. VisibilityͲhowmuchawarenessthereisofothersusingit 5. CompatibilityͲhowmuchitisperceivedasbeingconsistentwiththeexistingvalues, needs,andpastexperiencesofpotentialusers 6. ResultsDemonstrabilityͲthetangibilityoftheresultstouseit,includingtheirability toobserveandcommunicate
7. VoluntarinessofUseͲhowmuchtheuseofitisperceivedasbeingvoluntary,orof freewill
InnovationDiffusionTheoryhasbeenusedtounderstandthelinearandtimedependent connectionbetweenaninnovationandthedecisionprocessesassociatedtothatnew technologyoridea.Rogers(1995)initiallyputtheprocessintoalinearformat.Thenthe propertiesoftheinnovationͲdecisionprocesswerecategorisedbyVenkatesh(2003)into sevencoreconstructsforstudyingindividualtechnologyacceptance.Itisusefultocategorise behaviouralpropertiesofusers,becauseitisaninitialstepindevelopingatheoreticalmodel. TosumupInnovationDiffusionTheoryhasbeenusedtoaidthedevelopmentofother theoriesandmodels,shownbelow,whichhavetheabilitytounderstandthefundamentaland coreconstructsofhownewtechnologiesorideascanbeadoptedbyusers.
2.3.1.2 TheoryofReasonedAction
TheTheoryofReasonedAction(TRA)isamodelthathasbeenusedtopredictthebehaviour ofindividuals,whentheywanttoaccomplishavoluntarypreͲdeterminedtaskorobjective (Sheppard,etal.,1988).FishbeinandAjzen(1975)havedevelopedit;ithasalsocontributed totheinitialdevelopmentoftheTAM,(asdiscussedinSection2.3.1.5).TRAhasbeenusedin studiestoidentifytherelationshipsbetweenbehaviouralintention(BI),attitude(A)and subjectivenorm(SN),where“BI=A+SN”,wherethisequationpredictsauser’sbehaviourin doingavoluntaryaction(Davis,1986).
FishbeinandAjzen(1975)andAjzenandFishbein(1980)definedbehaviouralintention, attitude,beliefandsubjectivenormasfollows:Behaviourcanbecommonlydescribedas beingunpredictableandaseitherrebellingorconformingtosocialacceptance.Forexample, culture,attitudes,emotions,values,ethics,authority,rapport,persuasionandcoercioncan influencehumanbehaviour.Intentionistheactionofapersonthatdrivesthemtodo somethingspecific,itistherelationbetweenapersonandtheiraction.Anattitudeisan individual’sstateofmindorperceptionthateitherfavoursordisfavourssomething.Itcanbe atypeofbiasforevaluativeresponse,whichispositiveornegative.Beliefisaformof connectionthatpeopleassumebetweentheattitudesofeachotherortoinanimateobjects. Subjectivenormistheinfluencefromotherpeopleonones’behaviour.Italsoshowsthe impactotherpeoplehaveonone’sbeliefs,whichhasaconsequentialeffectonbehavioural intention.Moreinformationregardingbehaviouralintentionandattitudecanbefoundin Section2.3.1.5.
AsoutlinedbyVenkatesh(2003),thecoreconstructsofTRAareattitudetowardbehaviour andsubjectivenorm,whichhaveadirectinfluenceontheuser’sbehaviouralintentiontodo atask.ThiscomplementsSheppard’s(1988)explanationofhowauser’sbehaviouralintention toaccomplishacertaintaskisverydependentontheirattitudeorbehaviourtowardthe necessaryprocessesindoingthattaskandhowmuchtheyregarditasasubjectivenorm.As illustratedinFigure6,whenauserhasastrongattitudeorbehaviourtowarddoingataskand ahighregardoftheirtaskbeingasubjectivenorm,theywillultimatelyhaveastrong behaviouralintentiontocarryouttheirtask.TRAhasbeenasuccessfulmodelinpredicting theuserintentionsandbehaviourwhenwantingtocarryoutavoluntaryaction(Sheppard,et al.,1988). Figure6:OriginalversionofTheoryofReasonedAction(TRA),reproducedfromAjzen& Madden(1986) AjzenandFishbein(1980)includednewtheoriestothemodelshowninFigure6,andfurther expandedandillustrateditasshowninFigure7.Asthefigureillustrates,auserhasabelief andevaluationaboutcarryingoutabehaviour,whichhasadirectinfluenceonattitude.The userwouldalsohaveanormativebelieffromtheirsociety,i.e.beliefsthatfollowthoseof peopleclosetothem,suchasfamilyorfriends,andadegreeofmotivationtobehavein accordancewiththeirsociety’sbeliefs.Thesetwofactorscombinedhaveaneffectonthe intentionsoftheuser,whichdependsonhowmuchtheuserfeelstheirsocialgroupis
pressurizingthemͲpeerpressure.Theattitudeorbehaviourtowarduseoftechnologyand subjectivenormaredirectlyrelatedtoauser’sbehaviouralintention.Meaningtheuser’s belief,subjectivenormandevaluationonhowtoactaswellasmotivationtocomplyhavean overalleffectonthebehaviouralintentionofausertodotheirvoluntaryaction. Thismodelpresentsthepositiveornegativeoutcomeofasystem.Theoutcomeispositiveif thebehaviourofapersondevelopsintoapositiveattitudeaboutthebehaviourandifitisa negativeoutcome,itisviceversa(Kripanont,2007). Figure7:TheoryofReasonedAction(TRA),reproducedfromAjzen&Fishbein(1980) TRAiswellknownasbeingthebackboneforthemajorityofstudiesassociatedtotherelation ofattitudeandbehaviour.However,Bagozzietal.(1992)identifiedaweaknessofTRAinthe determinantsofattitudesandpredictedintentions,statingthatdeterminantscloselylinkto actualbehaviour.SunandZhang(2006)alsoidentifiedaweaknessofTRAinitsabilitytoassess fullythetechnologyacceptanceofusers.Theyreachedthisconclusionbycomparingthe
Beliefs and Evaluations Attitude Toward Behaviour Normative Beliefs& Motivation tocomply Subjective Norm (SN) Behaviour Intention (BI) Behaviour (Actual Usage) Relativeimportance ofattitudinal& normative considerations
explainedvarianceofexplanatorypowersoftheTechnologyAcceptanceModelwithTRA(Sun &Zhang,2006). Since1975,whenTRAwasfirstintroducedbyFishbeinandAjzen(1975),thismodelhasbeen analysedanddevelopedtoimproveitsabilityofpredictingauser’sbehaviouralintentionto carryoutavoluntaryaction.Davis(1986)addressedsomechallengesoftheTRAinassessing auser’sbehaviouralintentionandtherebydevelopeditintoanewtheoreticalmodel,which helatervalidated,asshowninSection8.1. Modellingbehaviouralintention,attitudeandsubjectivenorm,aswellasotherbeliefsinthe TRAmodel,hasprovidedinsightintoauser’sintentiontoperformavoluntaryaction. Section2.3.1.1discussedhowstudiesusedinnovationdiffusiontheory,whichsimilartoTRA explainshowauser’sperceptionoftechnologyhasaneffectonitsadoption.Asshownin Section2.3.1.5,Davis(1986)consideredthecoreconstructsofTRAtodevelophistechnology acceptance model. Background information on innovation diffusion theory and TRA representsthebasisofthecoreconstructsofDavis’model,whichwasneededforthisthesis tounderstandanddevelopDavis’modelintotheeͲTAM.Thefollowingparagraphsreport furthertheoriesandassociatedmodelstodistinguishadvantagesfromdisadvantagesanduse themforimplementingthisthesis’model.
2.3.1.3 SocialCognitiveTheory
Theuser’sbehaviouralintentiontocarryoutavoluntaryactionmaychangedependingonthe influencefromtheirsituation,societyandgovernmentlegislation.Thiscanhappenifaperson hasachangeintheirlives,whichhasadirectimpactontheirvoluntaryaction,suchaswhen
wantingtouseaneͲlearningsystem,buttheirInternetserviceproviderdecreasestheirusage allowanceandthereforecreatingabarriertousingeͲlearning.
SocialCognitiveTheoryprovidesamodeltopredictthehumanbehaviouralchanges,as introducedbyBandura(1986).Heassumedthattheperson,behaviour,andenvironmentare allcombinedtocreatelearninginanindividual.ThemodelshowninFigure8representsthe linkbetweenapersonandtheirbehaviour,thisrelationincludestheperson’sthoughtsand actions. Figure8:SocialCognitiveTheory,reproducedfromBandura(1986)
Peoplelearnbyobservingothers,wheretheenvironment,behaviour,andcognitionare factorsthatinfluencetheirdevelopment.Venkateshetal.(2003)studiedthetheoriesrelated toanindividual’sacceptanceoftechnology.HestatedthatSocialCognitiveTheoryisoneof themostpowerfultheoriesthatcandescribethebehaviourofpeople.Inaddition,he commentedonhowresearchersusedSocialCognitiveTheoryinthecontextofcomputer
Behaviour
Environmental Factors
Personal Factors: Cognitive, Affective, and Biological Events
Personalorperformanceexpectationsarewhattheuserassumestogetasanoutcomeof achievingapersonalorjobͲrelatedgoal.Auser’sselfͲefficacyistheirabilityandskillinusing technology.Venkatesh(2003)describedtheuser’semotionstousingtechnologyas“liking”it, astheaffect,andhavingdoubtstowarditsuse,astheanxiety.
2.3.1.4 TheoryofPlannedBehaviour
Auser’sbehaviourtocarryingoutavoluntaryactionisrelatedtotheinfluentialeffectoftheir surroundingsandtheirabilityandmotivationforadoptingthatbehaviour.TheTheoryof PlannedBehaviour(TPB)hastheabilitytoassesstheuser’sbehaviouralintention,basedon theirattitude,socialcognitionandintentionalmotivation,forspecificactivitiesorvoluntary actions(Ajzen,1985).Thisbeingusefulbecause,asstatedbyAjzen(1985),theuser’s behaviouralintentiondiffersdependingonthevoluntaryaction,theyalsorecommend avoidingassessingtheuser’sbehaviouralintentioningeneralvoluntaryactivities.
TPBwasintroducedbyAjzen(1985)anditcompletestheTRAmodelbyaddingperceived behaviourcontrolasafactor.Thelatterisdefinedashowpeopleseetheirbehaviourtotheir intendedactionaseasyordifficult(Ajzen,1991).Inaddition,AjzenandCote(2008)identified itasthepotentialthatapersonhastocompleteaspecificbehaviour.Theperceivedbehaviour controlsectionwasaddedtoTPBtosolvetheapparentchallengeswiththeTRA,suchaswhen dealingwithbehavioursoverwhichpeoplehaveincompletefreedomofcontrol(Kripanont, 2007).
TPB explains human behaviourasan actionthatisinfluencedbybehaviouralbeliefs, normativebeliefsandcontrolbeliefs,whichasFigure9illustratesarepredictorsforattitude towardthebehaviour,subjectivenormandperceivedbehaviourcontrolrespectively.There
was an assumption that supporting those user constructs will increase the person’s acceptanceofthevoluntaryactionandwillconvincethepersontoperformthatvoluntary action(Kripanont,2007).
Figure9:TheoryofPlannedBehaviour,reproducedfromAjzenandCote(2008)
Behaviouralbeliefsarethosethatareproducedfrompositiveornegativeattitudestowards thebehaviour(Kripanont,2007).Normativebeliefsarethoseofindividualsorgroupsthat comefromperceivedbehaviouralexpectations(Kripanont,2007).Controlbeliefsarethose thatarisefromtheexistenceoffactorsthatcaninfluencethebehaviourandspecifypeople’s feelingsofbeingincontrol.Thiscouldincreasethepowerofperceivedbehaviourcontrol (Kripanont,2007).Attitudetowardthebehaviourisidentifiedasananalysisoftheuser behaviourthatisbiasedeithertoencourageortodiscourageanaction(Ajzen&Cote,2008). Thesubjectivenormisidentifiedastheinfluencethatsocietyhasonthebehaviourofa person.Theinfluenceofsocietycanchangetheuser’soriginalplanorbehaviourtothat voluntaryactionnegativelyorpositively(Ajzen&Cote,2008).
TPBisknownasthemostpopulatedsocialͲpsychologicalmodelforbehaviouralstudies(Ajzen &Cote,2008).However,Mathieson(1991),ChauandHu(2001;2002)evaluatedtheTPB modelandfoundthatperceivedbehaviourcontrol,oneofitsfactors,isgenerallyweakerthan thefactorsoftheTAMintheirabilitytopredicttheuseracceptanceoftechnology.Moreon theTAMandthereasonsbehinditschoiceasthebasetodevelopthethesis’modelfollows.
2.3.1.5 TechnologyAcceptanceModel
TheTechnologyAcceptanceModel(TAM),establishedasanempiricalmodel,isalsoa theoreticalframeworkthatdesignersusetopredicttheuser’sbehaviouralintentiontoward newtechnology.TAMcanbeappliedtoevaluatedatacollectedfromaquestionnaireorsurvey ofatargetgroupofusersofasystem;themodeloutputsanassessmentoftheusers’ acceptanceoftechnologyandidentifiesthemostinfluentialtechnologyacceptancefactor, representedasthecoreconstructsoftheuser.TheTAMhasbeenwidelyusedandstudied, thefollowingreviewshowitdevelopedincludingitsstrengthsandweaknessesasabasisfor itsdevelopmentintothethesis’smodel,theeͲTAM.
TheTAMwasderivedfromTRAtomodeltheuseracceptanceofITsystems(Davis,1986).This modelhasenableddesignerstounderstandtheadvantagesanddisadvantagesofdesign elements oftechnology, while the technology is in early implementation stages, and thereaftertheycanimprovethesystems’design.
Davis(1986) initially tested the characteristics of user acceptance of computerͲbased informationsystems.TheTRAasstudiedinSection2.3.1.2andtheTAMshowninFigure10 havesimilarities,becauseDavisusedtheTRAasabasisformodeldevelopment.Thecore constructsoftheTAMarePerceivedUsefulnessandPerceivedEaseofUse,whiletheother
coreconceptsofBehaviouralIntentionandAttitudeTowardUsehavebeenadaptedfromthe TRAmodel.Theirgenericmeaningsareasfollows.
x PerceivedEaseofUse(PEOU),auser’spointofviewofhowhardoreasydoingan actionis(Davis,1989)
x PerceivedUsefulness(PU),auser’sconfidencethatusingasystemwillimprovetheir jobperformance(Davis,1989)
x BehaviouralIntention(BI),auser’smotivationtostart,continueandcompletean action(Fishbein&Ajzen,1975)
x AttitudeTowardUse(ATU),auser’spositiveornegativeinteresttousingthesystem (Fishbein&Ajzen,1975)
Figure10showstheconnectionbetweenthefourfactorsoftheTAM;theyhavearrowsto indicateacorrelationbetweeneachofthem.Eacharrowrepresentsatheoreticalrelationship, orhypothesis,thatpredictsonefactorwillhaveaneffectontheother.TheTAMoutputsa magnitudeanddirectionforeachhypothesis,moreinformationonhypothesesinSection3.3.
Figure10:TheTAMmodelbasedon(Davis,1989)
representedwithsolidlines1to6inFigure11,andpredictedtheinfluenceofexternalfactors, designfeaturesandperformanceimpact,onthemainfactors,whicharehypothesesshown bydashedlines7to9inFigure11. Figure11:TAMwithnumberedlinksbetweenthefactorsandexternalfactors,reproduced fromDavis(1986) Initially,itwaspopulartousetheTAMintheareasofInformationSystemsandIT(Information Technology)however,uptonowithasbeenusedinseveralotherareas.TheTAMispopular amongresearchersformodellingauser’sintentiontouseinnovativesystems,wheretheir researchoutcomeshaveindicatedhowtomotivateindividualstoadoptandusetechnology. TheseincludeusingeͲlearning(Ngai,etal.,2007;Moon&Kim,2001;Zhang,etal.,2008)(see Section2.2.1),healthcareeventreportingsystems(Wu,etal.,2008;Chau&Hu,2002; Goetzinger,etal.,2007),personalcomputers(Igbaria,etal.,1997),wordprocessorsand spreadsheets(Chau,1996),knowledgemanagementinagriculture(Folorunso&Ogunseye, 2008)andpredictingintranetandportalusage(Chang,2004).
SincetheTAM’sintroductionin1986,Davisandotherresearchershavebeenevaluatingthe predictiveabilityoftheTAMtoexpanditsabilityinpredictinguserintentionandthereby proposingimprovementsforassessinguseracceptanceoftechnology.Davis(1993)stated thatimprovementstotheTAMshouldbeabletoexplainauser’smotivationtouseasystem becauseoftheinfluencefrommanagementorhierarchicalstructuresintheirsociety.
ResearchershaveimprovedtheTAM’scapabilitytopredictuserbehaviouralintentiontoward usingtechnology.VenkateshandDavis(2000b)didthisbyintroducingadevelopmentofthe TAM,calledtheTAM2.TheTAM2isasignificantadvancementinpredictinguserbehavioural intentionandacceptanceoftechnology(Venkatesh&Davis,2000b);moreonTAM2in Section2.3.1.6.MoonandKim(2001)havealsomadedevelopmentsfromtheoriginalTAM. They extended the TAM model through the addition of a predictor called Perceived Playfulness,whichsignifieshowmuchauserbelievesthesystemasplayful;associatedtofun activitieslikegames.Withhypotheses,MoonandKim’smodelconnectsPEOUtoPerceived PlayfulnessandPerceivedPlayfulnesstoATUandBI.Theirstudyincludedananalysisof152 graduatestudentsusingtheworldwideweb(Moon&Kim,2001).Aftercomparinganalysis resultsoftheirextendedTAMwiththeoriginalTAM,theyfoundthattheirextendedTAMhad a5%greaterexplanationofthevarianceinattitudeand4%greaterexplanationofthevariance ofbehaviouralintentionfromthegroup. InChapter4ofthisstudytheabilityoftheTAMisassessedinmodellingEBMtrainersasusers oftheTTTͲEBMeͲlearningsystem,providingasbasisfortheTAM’sdevelopmentintotheeͲ TAMbyaddingfactorsthatexplainthevarianceoftheTAM’scoreconstructs.