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Comparing the effectiveness of AR training and slide-based training: the case study of metro construction safety

Authors:

Abstract

Metro construction poses significant risks and is prone to severe safety accidents. Safety training is critical to mitigate risks and reduce the number of accidents, as it allows workers to enhance their skills in risk identification, risk assessment, and risk response and ultimately reduce accidents. However, traditional training methods used today, such as slide presentations, videos, or text-based materials, provide a passive learning environment, which can limit their effectiveness in knowledge transfer. Augmented reality (AR) has emerged as a promising tool for training, allowing trainees to have an active learning environment. Nevertheless, research on assessing the effectiveness of AR safety training while comparing it with traditional methods is still limited. This study aims to compare the short-term and long-term effects on objective performance measures and subjective evaluations of both traditional and AR training. This is done by developing a new AR safety training for metro construction and comparing it with an equivalent slide-based safety training with 72 participants divided into two training groups. The selected safety case study covers the entire safety risk management process, including risk identification, risk assessment, and risk response. Results indicate that AR training is more effective than traditional training in terms of short-term knowledge acquisition of risk identification and long-term knowledge retention of risk identification, risk assessment, and risk response. These findings can have implications for the design of future safety training guidelines and recommendations.
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ComparingtheeffectivenessofARtrainingandslidebasedtraining:
thecasestudyofmetroconstructionsafety
PeizhenGong1,YingLu1*,RuggieroLovreglio2;XingguangYan g 3;YunxuanDeng2
1SchoolofCivilEngineering,SoutheastUniversity,China,*email:luying_happy@126.com
2SchoolofBuiltEnvironment,MasseyUniversity,Auckland,NewZealand
3ShanghaiJiankeEngineeringConsultingCo.,Ltd.XuhuiDistrict,Shanghai,200032,China
Abstract:Metroconstructionposessignificantrisksandispronetoseveresafetyaccidents.
Safetytrainingiscriticaltomitigaterisksandreducethenumberofaccidents,asitallows
workerstoenhancetheirskillsinriskidentification,riskassessment,andriskresponseand
ultimatelyreduceaccidents.However,traditionaltrainingmethodsusedtoday,suchasslide
presentations,videos,ortextbasedmaterials,provideapassivelearningenvironment,which
canlimittheireffectivenessinknowledgetransfer.Augmentedreality(AR)hasemergedasa
promisingtoolfortraining,allowingtraineestohaveanactivelearningenvironment.
Nevertheless,researchonassessingtheeffectivenessofARsafetytrainingwhilecomparingit
withtraditionalmethodsisstilllimited.Thisstudyaimstocomparetheshorttermandlong
termeffectsonobjectiveperformancemeasuresandsubjectiveevaluationsofbothtraditional
andARtraining.ThisisdonebydevelopinganewARsafetytrainingformetroconstruction
andcomparingitwithanequivalentslidebasedsafetytrainingwith72participantsdivided
intotwotraininggroups.Theselectedsafetycasestudycoverstheentiresafetyrisk
managementprocess,includingriskidentification,riskassessment,andriskresponse.Results
indicatethatARtrainingismoreeffectivethantraditionaltrainingintermsofshortterm
knowledgeacquisitionofriskidentificationandlongtermknowledgeretentionofrisk
identification,riskassessment,andriskresponse.Thesefindingscanhaveimplicationsforthe
designoffuturesafetytrainingguidelinesandrecommendations.
Keyword:AugmentedReality;SafetyTraining;Construction;Metro.

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1.Introduction
Toaddresstheissueofheavysurfacetrafficinmetropolitanareas,thedevelopmentof
metroinfrastructurehasexperiencedrapidgrowthworldwideinrecentyears,particularlyin
developingcountries(Anwaretal.,2023;Fangetal.,2022;Zhangetal.,2023;Zhangetal.,
2022).However,comparedtotraditionalbuildingconstruction,metroconstructionposesa
significantlyhigherriskofserioussafetyaccidentsduetoitsextendedconstructionduration,
variablegeologicalconditions,numeroushazardousfactors,andfrequenthumanmachine
interactions(Wangetal.,2021).Consequently,ensuringconstructionsafetyinmetroprojects
hasgarneredsignificantattentionfromregulators,industryprofessionals,andscholars.Major
accidentshaveunderscoredtheimportanceofconstructionsafetyinmetroprojects.For
instance,onFebruary18,2003,afireintheDaegumetroresultedinthetragiclossof192lives
and147injuries(Shietal.,2012).OnFebruary8,2018,aconstructionsafetyfailureoccurred
inFoshanmetroLine2betweenHuyongStationandLvdaohuStation,resultingin12fatalities,
8injuries,andanapproximated53.238milliondirecteconomiclosses(Dengetal.,2023).
Theseaccidentshavetriggeredwidespreadpubliccondemnationoftheinadequatesafety
performanceinmetroconstruction.
Pastconstructionexperienceshavedemonstratedthatreachingahighlevelofsafety
requiresthecollectiveeffortsofallstakeholders,includingowners,designers,construction
companies,workers,regulatoryagencies,andeducators(Baoetal.,2022;Jinetal.,2023;Liao
etal.,2015;MitropoulosandMemarian,2012;Wehbeetal.,2016;Xuetal.,2019).However,
thebehaviorofconstructionworkers,includingtheiracceptanceorrejectionofrisks,playsa
crucialroleinensuringtheirownsafety(Gohetal.,2018;Hasanzadehetal.,2018;Menget
al.,2021;Saracinoetal.,2015;Zhangetal.,2016;ZhangRitaetal.,2020).Infact,evidence
showsthatevenwhenconstructioncompaniestakeallnecessaryprecautionsconcerningsite
preparation,complianceenforcement,provisionoftraining,andpersonalprotective
equipment,workersmaystillengageinactivitiesthatputthematrisk(Choietal.,2017a,b;Li
etal.,2020;Liangetal.,2021;MengandChan,2020;Sacksetal.,2013;Shinetal.,2015).Their
abilitiestoidentify,assess,andrespondtoriskssignificantlyinfluencetheirbehaviorandsafety.
Numerousstudieshaveemphasizedthatworkerscangaintheseabilitiesusingeffectivesafety
training(Arifetal.,2021;ChoiandLee,2018;Kimetal.,2017;Panditetal.,2019;Rokooeiet
al.,2023;Wuetal.,2022;Yangetal.,2017;ZhouandGuo,2020).
Traditionaltrainingmethodsrelyonslidepresentations,videos,ortextbasedmaterials
intheconstructionindustry(Burkeetal.,2006;Dalingetal.,2023;Perlmanetal.,2014;Sacks
etal.,2013;Wuetal.,2023b).Thesetraditionalapproachesexhibitseveraldisadvantagesthat
hindereffectiveknowledgeacquisitionandretention(ButtussiandChittaro,2021;Scorgieet
al.,2024).Thiscritiquestemsfromtheirtendencytofosterapassivelearningenvironment,
whereintraineesarerequiredtopassivelylisten,read,andmemorizeinstructions(Avveduto
etal.,2017;Perlmanetal.,2014;Sacksetal.,2013).Consequently,thelimitedinteractive
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natureofthesemethodsresultsindiminishedlearnerengagementandreducedopportunities
foractiveparticipation(Cherrettetal.,2009;Gwynneetal.,2019).ARisarelativelynew
technologythatoverlaysvirtualobjects(i.e.,holograms)ontorealenvironments(Shinand
Jang,2009),anditholdspromiseforsafetytrainingpurposesindifferentfields,including
construction(Kamaletal.,2022;Lietal.,2018;ZhuandLi,2021).
ARoffersahighlyinteractiveandengaginglearningexperience,enablingtraineesto
undergosafetytrainingwithinavirtualenvironmentthataccuratelysimulateshazardous
situations.Traineescanacquireknowledgeofsafetyproceduresandoperatingtechniques,
andhavetheopportunitytopracticethem,thusenhancingtheirsafetyawarenessand
responsecapabilities(Chalhoubetal.,2021;Delgadoetal.,2020;Houetal.,2015;Lietal.,
2018;Shringietal.,2023).AlthoughARtraininghasdemonstratedpotentialeffectivenessin
theshortterm(HouandWang,2013;MurciaLopezandSteed,2018),thereislimitedresearch
availableonitslongtermtrainingeffects.Therefore,thereisaneedfornewresearchto
evaluatetheshort‐andlongtermimpactsofARsafetytrainingforconstruction,comparing
thisnewgenerationoftrainingwithtraditionaltrainingmethods.
Thepurposeofthisstudyistocomparetheshorttermandlongtermeffectsonobjective
performancemeasuresandsubjectiveevaluationsofbothtraditionalandARtraining.Thisis
achievedbydevelopinganewARbasedsafetytrainingprototypeformetroconstructionand
bycomparingitwithanequivalenttraditionaltrainingsolutionbasedonslides.TheARbased
prototypeemploys3Dmodelstovisualizehazardousscenariosassociatedwithmetro
construction,allowingforflexibletrainingonvarioustopicsinvolvingdangeroussituations.
Specifically,wefocusonsafetyknowledgeacquisitionandretentionasobjectiveperformance
measures,andontaskloadandsystemavailabilityassubjectiveevaluations.Assuch,this
studyisoneofthefirsttoconductacomprehensivecomparisonoftraditionalandARtraining
methodsinthecontextofsafetyriskmanagement,whichincludesriskidentification,risk
assessment,andriskresponse.Thiscomparativeassessmentcontributestoimprovingthe
understandingofARbasedsafetytrainingmethodsinthecontextofmetroconstruction,
providingvaluableinsightsforthedevelopmentofmoreeffectivesystemsandenhancing
workersafetyinthisfield.
Thestudyisstructuredasfollows:Section2providesaliteraturereviewoftheapplication
ofARinconstructionsafetytrainingandevaluationcriteriaforARbasedconstructionsafety
training.Section3presentsthematerialandmethods.Section4presentstheexperimental
resultsandincludesexploratoryanalyses.Section5discussestheresultsandoutlinesfuture
research.Finally,Section6concludesthestudy.
2.Literaturereview
2.1.ApplicationofARinconstructionsafetytraining
ARisaportabletechnologythatcreatesimmersiveandinteractivelearningexperiences
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bysuperimposingvirtualobjectsontoactualenvironments(Alizadehsalehietal.,2020;
Babalolaetal.,2023;Houetal.,2021;Zhangetal.,2021).ByintegratingARintosafetytraining,
itispossibletoenhancetrainees'situationalawareness,hazardidentification,anddecision
makingskills,leadingtoimprovedsafetyperformanceduringtheconstructionphase.There
arethreemaincategoriesofwidelyusedARapplications(Schiavietal.,2022).
ThefirstcategoryisstationaryAR,wherevirtualcontentissuperimposedonsurveillance
videocapturedfromfixedcameras(Jiaoetal.,2013).ThistypeofARiscommonlyusedin
surveillanceprocesses.ThesecondcategoryiswearableAR,whichisachievedbyhead
mounteddisplays(HMDs)andARgoggles.Researchershavedevelopedvariouscomplex
functionsinARgogglesandHMDs(Grabowskietal.,2018).Forexample,Chenetal.(2021)
provideduserswithacompleteguidanceandvisualizationexperienceforperforming
proceduraltasksliketyingreinforcementbarsandformwork.Wuetal.(2022)createdanAR
basedalertsystemforrealtimemeasurementsofthedistancebetweenaworkerandahazard,
ensuringworkersafetyduringtheconstructionprocess.WearableARdevicesoffersuperior
interactivefeatures,buttheirhighcosthaslimitedwidespreadadoption.Thethirdcategoryis
handheldAR,whichisalightweightapplicationthatcanbedeployedonmobilephones.
HandheldARiseasytoinstallandcanprovidecontinuoussafetyinformation,makingit
suitableforindividualsinsafetytrainingprograms(Chietal.,2022;Lietal.,2018).Researchers
havedevelopedARbasedapplicationstoenhancesafetytraining,demonstratingincreased
activelearningbehaviors,engagement,participantinterest,andimprovedlearningoutcomes
andexperiences(Kamaletal.,2021).Theseapplicationsfocusonspecificsafetyelementsand
investigateusers’intentionstoadoptthetechnologyinconstructionsafetytraining(Placencio
Hidalgoetal.,2022).ResearchhasdemonstratedthatARvisualizationtechniquesareeffective
intransferringknowledge,andtheinteractivenatureofARhelpstraineesrememberwhat
theyhavelearned(Shringietal.,2023).
DespiteadvancementsinARtechnologyforconstructionsafetytraining,severalresearch
gapspersist.Firstly,moreresearchisneededtoexaminethecosteffectivenessofARsafety
trainingsolutions,particularlyconcerningwearableARapplications(Ahmed,2019;Eirisetal.,
2018;ElKassisetal.,2023).Thehighcostoftheseapplicationslimitstheirwidespread
adoption.Additionally,understandingpotentialbarriersandchallengestointegratingARinto
existingsafetytrainingpracticesiscriticalforsuccessfulimplementation.Thisnecessitatesthe
developmentofstandardizedguidelinesandbestpracticesfordesigninganddevelopingAR
applicationstailoredtoconstructionsafetytraining(Houwelingetal.,2024;Lietal.,2018).
BridgingthesegapswillfacilitatethesuccessfulimplementationofARtechnologyin
constructionsafetytrainingandenhancesafetypracticesintheindustry.
2.2.EvaluationcriteriaforARbasedconstructionsafetytraining
EvaluatingARbasedconstructionsafetytrainingcomprehensivelyrequiresthe
establishmentofappropriateevaluationcriteriathatincludebothobjectiveperformance
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measuresandsubjectiveevaluations.Objectiveperformancemeasures,suchasknowledge
acquisition(Perlmanetal.,2014;Sacksetal.,2013),arecommonlyemployedtoassessthe
shorttermimpactoftrainingontraineeperformance.Knowledgeacquisitionreferstothe
trainee’sabilitytoswiftlyacquirenewinformationandskillsrelevanttosafetytraining.Many
scholarsutilizeknowledgeacquisitionasanevaluativeindexforassessingtheeffectivenessof
ARtraining.Numerousstudieshavedemonstratedapositivecorrelationbetweenhigher
immersioninARtrainingandimprovedknowledgeacquisition(Dallasegaetal.,2023;Leetal.,
2015;Veraetal.,2018).Leetal.(2015)proposedasystemforexperientialconstructionsafety
trainingusingAR,whichconsistedofsafetyknowledgedissemination(SKD),safetyknowledge
reflection(SKR),andsafetyknowledgeassessment(SKA).Theyemployedknowledge
acquisitiontoevaluatetheeffectivenessofthesystemandfoundthatAReffectivelyenhances
safety.Alshiaretal.(2019)comparedARbasedtrainingwithtraditionalpenandpaperbased
trainingusingknowledgeacquisitionundersimulatedconstructionscenarios,andtheresults
indicatedapreferenceforARbasedassessmentamongparticipantsovertraditional
assessment.However,itisworthnotingthatsomestudieshavepresentedcontradictory
results.Liuetal.(2022)discoveredthatforsimplemaintenancetasks,traditionaltraining
methodsoutperformedARtraining.However,asthecomplexityofmaintenancetasks
increased,ARtrainingexhibitedgreaterefficiency,surpassingtraditionaltrainingbyover10%.
Moreover,researchonthelongtermeffectsofARtrainingremainslimited,specificallyin
termsofknowledgeretention,whichreferstotheabilitytorecallandapplykeysafetytraining
pointsoverdaysorweeksinadynamicconstructionenvironment(Doolanietal.,2020).In
assessingtheeffectivenessofsafetytrainingmethods,investigatingthelongtermeffectsof
safetytrainingprovesvaluableinidentifyingthedurabilityofknowledgeretentionovertime,
enablingamorenuancedexaminationofknowledgeretentionacrossextendedperiods(Huet
al.,2023;Karakostaetal.,2023;Shringietal.,2023;Somerkoskietal.,2022).Forinstance,
Dalingetal.(2023)foundnosignificantdifferencesintheshort‐andlongtermeffectsofAR
trainingandtraditionaltraining;however,allparticipantsexperiencedasubstantialyet
comparabledeclineinperformance.Paesetal.(2024)comparedanARbasedsafetytraining
methodwithavideobasedtrainingmethod.TheresultsdemonstratethattheARsystemis
equallyeffectiveastraditionalmethodsintermsofknowledgeacquisitionandretention.
Subjectiveevaluationsoftheuserexperiencearevitalindeterminingtheactual
utilizationandacceptanceofatrainingmethod,inadditiontoobjectiveperformance
measures(Jangetal.,2021;Liuetal.,2023;Xiangetal.,2023).However,currentARtraining
researchhasgivenrelativelylessattentiontosubjectiveevaluations(Hoedtetal.,2017).Tas k
loadandsystemusabilityarecommonlyusedsubjectiveevaluationindexes(AlAhmarietal.,
2018;Houetal.,2015;Koumaditisetal.,2019).Tas k loadreferstothecognitiveandphysical
demandsplacedontraineesduringARbasedsafetytraining,encompassingfactorssuchas
mentalload,attentiondemands,andtaskandscenariocomplexity(Leetal.,2015;Liuetal.,
2022;Moesletal.,2023).Assessingtaskloadcanassistinoptimizingtrainingcontentand
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deliverytoensurethattraineeseffectivelyprocessandretaininformation.Systemusability
relatestotheaccessibility,reliability,andfunctionalityoftheARtrainingsystemduring
training(Dyrdaetal.,2023;Kamaletal.,2021;Surietal.,2023).Reliableandusablesystems
ensurethattraineescanfullycomprehendtrainingmaterialswhileminimizingpotential
distractionsthatcouldhinderknowledgeacquisition.Severalstudieshavedemonstratedthat
theimplementationofARtrainingnotonlyenhancesobjectiveperformancebutalsohasa
positiveimpactonsubjectiveevaluations,indicatingimproveduserexperienceand
acceptanceofthetrainingmethod(Houetal.,2015;Koumaditisetal.,2019).
2.3.Summary
ThisreviewshowsthatthereisaneedfornewcomprehensiveassessmentsonhowAR
cansupporteffectivesafetytraining.Thereisalackofinvestigationon(a)theeffectivenessof
ARsafetytrainingcombiningobjectiveperformancemeasuresandsubjectiveevaluations;(b)
thecontributionofARtoenhancesafetyriskmanagement,includingriskidentification,risk
assessment,andriskresponseinconstruction.
Thisstudyaimstoaddressthesetworesearchgapsbyexaminingthepotentialbenefits
andeffectivenessofARinsafetytrainingformetroconstruction,aswellasitsroleinthe
broadersafetyriskmanagementprocess.To accomplishtheseobjectives,thestudyposestwo
researchquestions:
QuestionOne(Q1):AretheredifferencesbetweentraditionalandARtrainingintermsof
shorttermandlongtermobjectiveperformancemeasures,specificallysafetyknowledge
acquisitionandretention?Additionally,doestraditionaltrainingdifferfromARtrainingin
enhancingskillsrelatedtoriskidentification,riskassessment,andriskresponse?
QuestionTwo(Q2):AretheredifferencesbetweentraditionalandARtrainingintermsof
subjectiveevaluations,specificallytaskloadandsystemusability?
3.MaterialandMethods
ThisworkaimsatprototypinganewARsafetytrainingsolutionandcomparingitwith
traditionaltrainingsolutions.Todeveloptheprototype,weidentifyhighriskhazardous
scenariosthroughaccidentreportsandonsitesurveys,asreportedinSection3.1.
Subsequently,aprototypeofanARbasedmetroconstructionsafetytrainingisdeveloped
andtested.Theobjectiveofthistrainingistoprovideguidancetoconstructionworkers
regardingsafeoperationsduringmetroconstruction,encompassinggeneralsitepractices,
hazardspecificsafetypractices,andconstructionsafetyprecautions.
Followingthedevelopmentphase,testingisconductedthroughacontrolledbetween
subjectsexperiment.The72participantsaredividedintotwogroups,eachassignedtoa
differenttrainingcondition:slidebasedorARbased.Thepurposeofthisexperimentisto
comparetheimpactofthetraditionalslidebasedtrainingmethodwiththeARbasedtraining
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methodonparticipantknowledge,taskload,andsystemusability.
3.1.Selectionofhazardscenarios
Theprocessofselectinghazardscenariosinvolvestwoparts:analyzingstatisticalaccident
reportstoidentifyhighriskaccidenttypes,andconductingonsiteresearchtodetermine
specifichazardscenariosassociatedwiththesehighriskaccidenttypes.Sincethisstudyis
carriedoutinChina,wefocusontheanalysisofaccidentreportsinthiscountryonlyfocusing
onmetroconstructionsites,whichareamongthemostdangerousintheconstructionsector.
Thecollectionofmetroconstructionaccidentreportsforthisstudyencompassestwosources.
Thefirstsourceconsistsofaccidentreportsissuedbynationalorlocalgovernmentsandnon
governmentalorganizations(Shaoetal.,2019;Zhouetal.,2021).Thesecondsourceisthe
Internet(Rissolaetal.,2022),wheremetroconstructionaccidentreportscanbeaccessed
fromavarietyofwebsites,includingmediawebsitessuchasTence n t andXinhuaNet,aswell
asinformationwebsiteslikeWikipediaandBaiduEncyclopedia.Atotalof207accidentreports
relatedtometroconstructioninChinabetween2016and2023havebeencollected.Ta b l e 1
presentsasummaryofthenumberofdeathsandnonfatalinjuriesforeachaccidenttype.
Statisticalanalysesindicatethatthefollowingsixaccidenttypesposearelativelyhighrisk:
collapse,fallfromheight,vehicleinjury,objectstrike,cranerelatedaccident,andmechanical
injury.ThesefindingsareconsistentwiththeassessmentconductedbyQietal.(2023).
Onthisbasis,specifichazardscenarioscorrespondingtotheaforementionedhighrisk
accidenttypesareidentifiedthroughonsiteresearchconductedatrepresentativemetro
constructionprojects.Thesehazardscenarios,detailedinTable2,willbeutilizedforboth
traditionaltrainingandARtraininginthecontextofmetroconstruction.
Onthisbasis,specifichazardscenarioscorrespondingtotheaforementionedhighrisk
accidenttypesareidentifiedthroughonsiteresearchconductedatrepresentativemetro
constructionprojects.Theonsiteresearchencompassedathoroughinvestigationofametro
constructionprojectlocatedinSuzhou,China,acityrenownedforitsrobusteconomyand
rankingamongthetop10.Thisparticularmetroprojectspansover40kilometers,comprising
atotalof28stations,andentailsaninvestmentexceeding20billionyuan.Itconstitutesa
significantendeavorintherealmofregionalinfrastructureconstruction.Ourinteractionswith
keystakeholdersattheconstructionsite,includingprojectmanagers,technicalleaders,and
onsiteworkers,aimedtoextractcrucialinformationandinsightsfromtheirfirsthand
experiences.Theseinvaluablediscussionsfacilitatedtheidentificationanddocumentationof
precisedisasterscenariosassociatedwithhighriskaccidenttypes,subsequentlysummarized
inTab l e 2.ThistablewillbeutilizedforbothtraditionaltrainingandARtraininginthecontext
ofmetroconstruction.Furthermore,wecapturedphotographsofcertainhazardscenarioson
site.Itisimportanttonotethatincaseswherespecificscenarioswereinaccessibleonsite,
alternativemeasureswereemployed,suchasobtainingrelevantimagesfromreputableonline
sources.Thisapproachensuredtheinclusionofacomprehensivearrayofhazardscenariosin
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ouranalysis,therebyupholdingthevalidityandintegrityofourstudy.
Tab l e 1‐Statisticsoninjuriesinmetroconstructionaccidentsbytype.
AccidenttypeNumberofdeathsNumberofinjuriesTot a l
Vehicleinjury151429
Electricshock718
Fallfromheight35540
Fire617
Mechanicalinjury17118
Cranerelatedaccident15823
Collapse603191
Objectstrike26329
Poisoning437
Undergroundwaterdamage000
Cablebreakage000
Pipelinerupture000
Otherdamage11011
Otheraccidents404
Asphyxiation101
Struckby101
Tab l e 2‐Highriskaccidenttypesandhazardscenariosidentifiedinarepresentativemetro
project.
No.Highriskaccident
types
Hazardscenarios
1Vehicle injuryRolloverwhiletransportingheavyloads.
2Constructionworkersindriver’sblindspot.
3FallfromheightHoleswithoutwarningsignsorprotection.
4Unprotectedouteredgesofupperfloors.
5Workingatheightwithoutproperuseofpersonalsafety
equipment.
6Vent uring intodangerousplacesbyclimbingoversafetyguardrails.
7Fixedscaffoldingwithoutadequatefallprotection.
8ObjectstrikeStrikingagainstfixedorstationaryobjects.
9Improperplacementofmaterialsandequipmentonsiteor
configurationofoperatinglines.
10Cranerelated
accident
Movingcraneswithloadswhereworkersarepresent.
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11CollapseImproperlysupportedwallformwork.
12Failuretousepersonalsafetyequipmentproperly.
13Failuretofollowprescribedstepsinconstructionwork.
14MechanicalinjuryFailuretoobservetheconstructionsiteandsurroundingscarefully.
15Failuretousepersonalsafetyequipmentproperly.
3.2.Trainingdesign
BothtraditionalandARtrainingincludethreemainparts,eachwithahalfhourtraining
session:
(1)Generalsitespecifications:Thissectioncoverssafetyinstructionsforworkersupon
enteringtheconstructionsite,constructiondresscodes,constructionelectricitycodes,
commonvehicleandmachineryoperationcodes,constructionmaterialstackingcodes,and
workatheightprotectioncodes.
(2)Hazardspecificsafetypractices:Thissectionfocusesonspecificsafetypractices
relatedtohazardssuchasvehicleinjury,fallfromheight,objectstrike,cranerelatedaccident,
collapse,andmechanicalinjury.Safetypracticesandproceduresspecifictoeachhazardare
explainedindetail.
(3)Constructionsafetyprotection:Thissectionemphasizestheimportanceofusing
safetyequipment,includingsafetybelts,safetyhelmets,andsafetyshoes.
Itshouldbenotedthatinthesectionsongeneralsitespecificationsandconstruction
safetyprotection,thesametextcontentandpresentationslidesareusedforbothtraditional
andARtraining.Theseslidescontaininformationcompiledfromsafetycodes.However,inthe
hazardspecificsafetypracticessection,therearedifferencesbetweenthetwotrainings.The
objectiveofthetrainingistoenhancethetrainees’abilitiesinriskidentification,risk
assessment,andriskresponse.Inthetraditionaltraining,thepresentationslidescreatedfor
thehazardspecificsafetypracticessectionareenrichedwith15setsofpicturesandvideos
fromconstructionsitesandtheInternet,correspondingtoeachofthe15hazardscenariosin
Table2.Thesevisualmaterialswererequiredtobehighdefinitionandfeatureeyecatching
hazardousbehaviors.Thevisualmaterialsaimtoenhancetheunderstandingandengagement
oftrainees.Traineesreceivepassivelearningthroughtrainerpresentations,involvingactivities
suchaslistening,reading,andmemorizingsafetypracticepoints.
InARtraining,thetextcontentandpresentationslidesremainthesameasintraditional
training.However,thevisualmaterialsarereplacedby15ARhazardscenarios,aligningwith
Table2.ThisstudyadoptstheARQRcodemethodforpresentinghazardscenarios.TheAR
QRcodemethodcombinesARandQuickResponse(QR)codestoeffectivelydeliverhazard
scenarioinformation.ThisapproachwasinitiallyproposedbyForoughiSabzevaretal.(2023)
withtheobjectiveofenhancingtheacquisitionofinformationrelatedtobuildingdesignand
constructionprocesses.ThisstudyadaptstheARQRcodemethodforsafetytraininginmetro
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construction.
Topresentthehazardousscenariosduringthesafetytraining,thesescenariosareinitially
3DmodeledusingSketchup.Subsequently,thescenesareexportedto.daeformatand
integratedintotheselectedARplatform.ThechosenARplatformisAUGMENT,aversatile
platformthatsupportsvariousapplications,includingecommerce,marketing,andfieldsales
(AUGMENT,2023).Itshowsgreatpotentialasatooltosupportsafetytrainingcontent.The
platformautomaticallygeneratesQRcodesthattraineescanscanusingtheirmobilephones
ortabletstoaccessstoredARhazardscenariossuperimposedontherealenvironment.It
shouldbenotedthattheseARhazardscenariosonlyillustratevariouspotentiallyunsafe
situationsanddonotdepicttheconsequencesofaccidents.ARhazardscenesarecreatedfor
eachofthehazardscenariosidentifiedinSection3.1.Fig.1depictstheprototypeofthe
developedARsystem.Fig.2showsexamplesoftraineesreceivingtraditionalandARtraining.
InARtraining,traineescanplacetheARhazardscenariosonanyflatsurface,suchasthe
groundordesktop.Whilethetrainerusesslidestoteach,theycanfreelyinteractwiththeAR
hazardscenariosbyrotating,zoominginorout,exploringfromdifferentperspectivesand
learningactively.Thisisdifferentfromtraditionaltrainingwhereonlypicturesandvideoscan
beviewed.
Fig.1.PrototypeofthedevelopedARsystem.
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Fig.2.Examplesoftraineesreceivingtraditional(left)andARtraining(right):a)
construction
workersindriver’sblindspot;b)workingatheightwithoutproperuseofpersonalsafety
equipment;c)movingcraneswithloadswhereworkersarepresent;d)failuretouse
personalsafetyequipmentproperly.
3.3.Experimentaldesign
Thestudyemploysabetweensubjectsexperimentaldesigntocomparetheeffectiveness
oftwotrainingmethods:traditionaltrainingandARtraining.Thiswasdonebyrandomly
assigningparticipantsinourstudytotwogroups:TraditionalGroupandARGroup.This
methodisalignedwithmanypreviousstudiesfocusingoncomparingtheeffectivenessof
differentsafetytrainingsolutions(Scorgieetal.,2024).
Theindependentvariableinthestudyisthemodeoftraining,resultingintwo
experimentalconditions.Inthetraditionaltraining,participantsreceivedinstructionfrom
trainersandviewedslidesonaconventionaldisplay.Theseslidesaresupplementedwith
photosandvideosfrommetroconstructionsites,followingamethodcommonlyusedinprior
trainingstudies
(Dalingetal.,2023;Sacksetal.,2013;Wuetal.,2023a).Incontrast,intheAR
training,participantsalsoreceivedguidancefromatrainerandviewedslidesona
conventionalmonitor.However,insteadofviewingphotosandvideos,theyutilizeARto
visualizehazardousscenarios.Bothtrainingsareconductedinagroupsetting.
Thedependentvariableinthisstudyistheparticipants’learningperformance,
specificallyknowledgeacquisitionandretentioninthreeareas:riskidentification,risk
assessment,andriskresponse.TheknowledgedataofthetraditionalgroupandARgroupis
collectedatthreedifferentstages:pretraining,immediatelyaftertraining,andfourweeks
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aftertraining.
Toassessknowledgeacquisition,wecomparetheparticipants’pretrainingand
immediateposttrainingknowledgelevels.Knowledgeretentionisevaluatedbycomparing
knowledgelevelsimmediatelyaftertrainingwiththosemeasuredfourweekslater.Thechoice
ofafourweekintervalalignswithindustrypracticesforassessinglongtermretentionof
training.Similartimeframeshavebeenusedinpreviousstudiesontrainingretention
(Lovreglioetal.,2021;Sacksetal.,2013).
Fig.3illustratestheexperimentprocess.
Theexperimentconsistsoffoursteps.InStep1,demographicdataandpriorexperience
arecollectedfromparticipants,aswellasobjectiveperformanceassessments(risk
identification,riskassessment,andriskresponseknowledge).Step2involvedproviding
traditionalandARtrainingtobothgroups.Immediatelyaftertraining,inStep3,bothgroups
undergosubjectiveassessmentsregardingtaskloadandsystemusability,aswellasobjective
performanceassessments.Finally,inStep4,objectiveperformanceassessmentsare
administeredtobothgroupsofparticipantsfourweeksafterthetraining.Thedecisionto
measuretaskloadandsystemavailabilityonlyinStep3isbasedonthefactthat,immediately
afterthetraining,participantshaveaclearperceptionofthesubjectiveassessmentsofthe
trainingmethod.Ifthesemeasurementswererepeatedatthefourweekmark,participants’
perceptionofthetrainingmethodmayhavediminishedorevenbeenforgotten,whichwould
hinderamoredefinitiveassessmentofthetaskloadandsystemusabilityassociatedwiththe
twotrainingmethods.
Fig.3.Experimentprocess.
3.4.DataCollectionInstruments
Thedatacollectioninstrumentcomprisedthreequestionnairesadministeredatdifferent
periodsoftheexperiment:pretraining,immediatelyaftertraining,andfourweeksafter
training.Eachquestionnaireisdesignedtogatherspecificinformationandresponsesfromthe
participants.Thecategoriescoveredinthiseffortincludethefollowing:1)demographics,2)
13 / 40
priorexperience,3)knowledge,4)taskload,and5)systemusability.Thepretraining
questionnaireincludescategories1and2.Thequestionnaireimmediatelyaftertraining
encompassescategories3to5.Thequestionnairefourweeksaftertrainingfocuseson
category3.Thedetailsofeachcategoryaredescribedbelow:
1)Thedemographicssectionconsistsoftwoitemstocollectparticipants’characteristics,
namelygenderandeducationlevel.
2)Thepreviousexperiencesectionincludestwoitemstogatherinformationabout
participants’workexperienceinmetroconstructionandtheirexperiencereceivingsafety
training.Thisisdonetoensurethatbothgroupshavesimilarpriorexperiencesandtoavoid
anybiasesrelatedtoexperience.
3)Theknowledgesectionencompassesthreeitems,eachcontaining10questionsto
assessparticipants’abilitiesinriskidentification,riskassessment,andriskresponse,
respectively.Specifically:
RiskIdentification:Participantsareprovidedwith10riskscenepicturesandasked
toidentifyvariouspotentialhazardsbymarkingthecorrespondingnumbersinTab l e
2.Eachcorrectidentificationearnsonepoint,andthetotalpossiblescoreforthis
taskis10points.
RiskAssessment:Participantsarepresentedwiththesame10riskscenariopictures
andrequiredtoevaluatetherisklevelofeachscenario,categorizingitasverylow,
low,medium,high,orveryhigh.Toassessthecorrectrisklevelsforthesescenarios,
agroupofmetroconstructionsafetyexpertsisaskedtoestablishnormativevalues,
followingthecommonlyusedmethod(Sacksetal.,2013).Subsequently,safety
managersarealsoinvitedtoevaluatetheestablishednormativevaluesbasedon
actualconsequences,andtheoutcomesalignedconsistentlywithrealworldrisk
scenarios.Participantsreceiveonepointforeachcorrectassessment,resultingina
totalscoreof10pointsforthistask.
RiskResponse:Participantsaregiventhesame10riskscenariopicturesandasked
tomakebehavioraljudgmentsbyselectingthemostappropriateresponseoption
fromtheprovidedchoices.Theresponseoptionsinclude:(a)continueworkingas
normal;(b)notifythesafetysupervisorandcontinueworkingasnormal;(c)handle
thehazardoussituationindependently;or(d)refusetoworkinthespecificsituation.
Eachcorrectresponseearnsonepoint,andthetotalpossiblescoreforthistaskis
10points.
4)ThetaskloadsectionincludessixitemsderivedfromtheNASATa s k LoadIndex(TLX),
aselfreporttoolthatmeasuresparticipants’perceivedtaskloadacrosssixaspects:mental
workload,physicalworkload,temporalworkload,trainingeffort,trainingdifficulty,and
stressed/annoyed(Hart,2006;HartandStaveland,1988).Eachdimensionisrepresentedbya
horizontallinewithendpointslabeled“low”(=1)and“high”(=21).Participantsindicatetheir
perceivedtaskloadoneachdimensionbymarkingapoint.
14 / 40
5)Thesystemusabilitysectioncomprisestenitemstoassessparticipants’perceived
abilitytoreceivetrainingandtheirevaluationoftheusabilityofthetrainingmethod.This
sectionemploysawidelyadoptedandvalidatedtoolforassessingtheusabilityofvarious
systems,includingtrainingprograms(Gaoetal.,2020;JohnandBeaconsfield,1996).Afive
pointLikertscaleisemployed,with“stronglydisagree”(=1)and“stronglyagree”(=5)asthe
options.Participantsratestatementsrelatedtosystemusability,indicatingwhetherornot
theyagreewiththem.
3.5.ParticipantsandExperimentSession
Thestudycomprisedasampleof72participantswhometthequalificationcriteriaof
beingatleast18yearsoldandpossessingatleastahighschooleducation.Todeterminethe
requiredsamplesize,theSuccessRuntheorem(Durivage,2016;Wuetal.,2023a)wasutilized:
𝑛𝑙𝑛 󰇛1𝐶󰇜
𝑙𝑛 󰇛𝑅󰇜 (1)
where𝑛 denotesthesamplesize,𝐶 denotestheconfidencelevel,and𝑅 denotesthe
reliability.Thisstudyemployscommonlyusedstatisticalthresholds,namely,95%confidence
and90%reliability(Wuetal.,2023a).Theminimumrequiredsamplesizewascalculatedtobe
29participants,whichalignswiththeseminalworkofCohen(1992).Inthisstudy,thesample
sizewastwicetherequiredamount,consistentwithsimilarstudiesinthefieldthatinvolved
twoexperimentalconditions.Forinstance,Wuetal.(2023a)conductedtworoundsof
experiments,eachwithasamplesizeof16participants.Sacksetal.(2013)conductedtwo
experiments,onewith20participantsandtheotherwith25participants.Seeligeretal.(2023)
recruited35participants.Yipetal.(2019)recruited46participants.Jeelanietal.(2020)
recruited53participants.Abbasetal.(2023)andPerlmanetal.(2014)hadlargersamplesizes
of60and62participants,respectively.
Participantconsentandethicalapprovalwereobtainedpriortothetestpreparation
phase.Participantswereexplicitlyinstructedtorefrainfromconsumingalcoholontheday
precedingtheexperiment.Atotalof72participantswererandomlyassignedtooneoftwo
experimentalconditions,with36participantsineachgroup.
Duringtheformaltestphase,bothgroupsreceivedtheirtraininginasoundproofed
conferenceroom,wherethebrightnesswasadjustedto300to500luxandthetemperature
wasadjustedto20to22°Cinordertoprovideanequallysuitableenvironmentfortraining.
Overall,theexperimentalconditionswereidenticalandconducivetotrainingforbothgroups.
Participantswereaskedtorefrainfromcommunicatingwitheachotherthroughoutthe
training,andgrouptrainingdidnotaffecttheresults.
Inthedatacollectionandprocessingstage,thetestswereadministeredintheformof
questionnaires,asdescribedinSection3.4.
15 / 40
4.Results
Thedataanalysisaimstoexaminewhethertherearesignificantdifferencesbetweenthe
twogroupsofexperimentsinthreeindicators:a)knowledgeinpretraining,immediatelyafter
training,andfourweeksaftertraining(Section4.2);b)taskload(Section4.3);andc)system
usability(Section4.4).Throughoutthestudy,thenumberofparticipantsremainedconstant
duringallthreedatacollectionphases,includingpretraining,immediatelyaftertraining,and
fourweeksaftertraining.Therewerenodropouts,andbothgroupsconsistedof36
participantsacrossthethreedatacollectionphases.Itisworthnotingthatnoparticipants
reportedexperiencingmotionsicknessoranydiscomfortwhileusingtheARsystemprototype.
Furthermore,participantswereinstructednottoengageinanyotherrelatedsafetytraining
withinfourweeksaftertraining.
4.1ParticipantDemographics
Thestudyrecruitedatotalof72participants,consistingof21metroconstructionworkers,
19metroconstructionsafetymanagers,and32civilengineeringstudents.Toassessthe
significanceofthedifferencebetweentheARgroupandtheslidegroup,thechisquaretest
wasconducted.Theparticipantcharacteristicsandtheresultsofthesignificancetestare
summarizedinTable3.Thechisquaretestconfirmedthattherewasnosignificantdifference
(p>0.05)foundbetweenthetwogroupswithrespecttogender,educationlevel,previous
workexperienceinmetroconstruction,andpreviousmetroconstructionsafetytraining
experience.Thisindicatesthatthedistributionoftheseparameterswasrelativelybalanced
acrossthetwogroups.
Tab l e 3ParticipantDemographics.
Parameter
Slidetraininggroup(n=36)ARtraininggroup(n=36)
Significance
test
Construction
workers
(n=11)
Safety
directors
(n=9)
Students
(n=16)
Construction
workers
(n=10)
Safety
directors
(n=10)
Students
(n=16)
Gender
𝜒
0,
p=1.000
Woman336435
Man86106711
Educationlevel
𝜒
0.237,
p=0.971
Highschooldegree900800
Undergraduatedegree2692710
Masterdegree035034
Doctoraldegree002002
Previousworkexperienceinmetroconstruction
𝜒
0.090,
16 / 40
Meannumberofyearsatwork51105.210.90p=0.956
Numberofparticipants
injuredatwork
4(36.4%)1(11.1%)0(0%)3(30%)1(10%)0(0%)
Meannumberofworkrelated
accidentswitnessed
11.900.71.80
Previousmetroconstructionsafetytrainingexperience
𝜒
0.001,
p=0.972
Numberofparticipantswho
receivedformalsafetytraining
8(72.7%)9(100%)0(0%)7(70%)10(100%)0(0%)
Meannumberofprevious
safetytraininghours
67006.2690
Theresultsrevealthatconstructionworkersmostlyhavehighschooldegrees,while
safetydirectorsandcivilengineeringstudentspossessundergraduatedegreesorhigher.None
ofthestudentshavepriorexperienceinmetroconstructionorsafetytraining.Safetydirectors
exhibitahighermeannumberofyearsatworkcomparedtoconstructionworkers.Specifically,
theentirepopulationofsafetydirectorshasanaverageof10.9yearsatwork,whereas
constructionworkershaveanaverageof5.1years.Allsafetydirectorshaveundergoneformal
safetytraining,whileonly71.4%ofconstructionworkershavereceivedthesametraining.
Safetydirectorsreceivesafetytrainingforanaverageof11.4timeslongerthanconstruction
workers,with69.5hoursand6.1hours,respectively.Moreover,twosafetydirectorsandseven
constructionworkersexperiencedinjuriesinpreviousconstructionoperations.
4.2AnalysisofKnowledge
Inthissection,wepresenttheknowledgescoresforriskidentificationobtainedby
participantsintheslidegroupandARgroupatdifferenttimepoints:pretraining,immediately
aftertraining,andfourweeksaftertraining(Section4.2.1).Thescoresforriskassessmentare
reportedinSection4.2.2.Finally,scoresregardingriskresponsesarepresentedinSection4.2.3.
Thefiguresrepresentingtheknowledgescoresforeachsectionuserectanglestoindicatethe
meanscore,withdotsrepresentingindividualdatapoints.Incaseswheredifferent
participantsreceivedthesamescore,thedotsoverlap.
Toanalyzethesignificantstatisticaldifferencesbetweenthetwoexperimentalgroups,
wefirstconductedanormalitytestandahomogeneityofvariancetest.Ifbothtestsyielded
pvaluesgreaterthan0.05,indicatingthatthenormalityandhomogeneityassumptionswere
met,weusedtheindependentsamplettestforsignificanceanalysis.Otherwise,weemployed
theMannWhitneyUtest.Itisimportanttonotethatinboththeindependentsamplettest
andtheMannWhitneyUtest,apvaluelessthan0.05indicatesasignificantdifference,while
apvaluegreaterthanorequalto0.05suggestsnosignificantdifference.
4.2.1RiskIdentification
17 / 40
Fig.4andTable4presenttheresultsoftheriskidentificationknowledgescores.The
scoresdidnotpassthenormalitytest(p<0.05),necessitatingtheuseoftheMannWhitney
Utesttodeterminesignificantdifferencesbetweenthetwoexperimentalgroups.Comparing
theriskidentificationknowledgescorespretrainingandimmediatelyaftertraining,both
groupsdemonstratedasignificantincrease.Thissuggeststhatbothtrainingmethods
effectivelyenhancedparticipants’riskidentificationknowledge.Whencomparingscores
immediatelyaftertrainingandfourweeksaftertraining,onlytheslidegroupexhibiteda
significantdecrease,whiletherewasnoevidenceofasignificantdeclineintheARgroup.In
fact,whiletheslidegrouphaddecreasedvaluesof0.78,theARgrouphadalowerdecrease
valueof0.67.ThedatapresentedinTable4indicatethatparticipantsinthetwogroupsdid
notsignificantlydifferintheirriskidentificationknowledge.Thissuggeststhatbothgroups
hadthesamelevelofriskidentificationknowledgeatthestartoftheexperiment.Additionally,
thescoresoftheARgroupimmediatelyaftertrainingandfourweeksaftertrainingwere
significantlyhigherthanthoseoftheslidegroup.
Fig.4.RiskidentificationknowledgescoreforslidetrainingandARtraining.
Tab l e 4‐Comparisonofriskidentificationknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginARandslidetrainingconditions.
TimepointsParameterARSlideARvsSlide
Pretraining
N3636MannWhitneyU=615.500
Z=‐0.372
p=0.710
M4.7204.830
SD1.8301.682
18 / 40
Immediatelyaftertraining
N3636MannWhitneyU=456.000
Z=‐2.231
p=0.026*
M7.3606.810
SD1.0991.238
Fourweeksaftertraining
N3636MannWhitneyU=415.500
Z=‐2.727
p=0.006**
M6.6906.030
SD1.6001.134
Pretrainingvs
Immediatelyaftertraining
MannWhitneyU147.500256.500/
Z‐5.703‐4.491/
p<0.001***<0.001***/
Immediatelyaftertraining
vsFourweeksafter
training
MannWhitneyU504.000466.000/
Z‐1.690‐2.130/
p0.0910.033*/
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.Twoasterisks(**)indicatestatistically
significantresultswithp<0.01.Threeasterisks(***)indicatestatisticallysignificantresultswithp<0.001.
Table5displaystheresultsofriskidentificationknowledgescoreswithintheARgroup.
Comparingthepretrainingandimmediatelyaftertrainingscores,allthreecategoriesof
participants(constructionworkers,safetydirectorsandstudents)showedsignificant
improvements.Whencomparingscoresimmediatelyaftertrainingandfourweeksafter
training,noneofthethreecategoriesofparticipantsshowedsignificantdecreases.Moreover,
thedatarevealedsignificantdifferencesinthescoresofsafetydirectorsandstudentsboth
pretrainingandimmediatelyaftertraining.Table6presentstheresultsofriskidentification
knowledgescoreswithintheslidegroup.Comparingthepretrainingandimmediatelyafter
trainingscores,exceptforsafetydirectors,allothercategoriesofparticipants(construction
workersandstudents)exhibitedsignificantimprovements.Whencomparingscores
immediatelyaftertrainingandfourweeksaftertraining,noneofthethreecategoriesof
participantsshowedsignificantdecreases.Furthermore,thedataalsoindicatedsignificant
differencesinthepretrainingscoresbetweenconstructionworkersandsafetydirectors,as
wellasbetweensafetydirectorsandstudents.
Tab l e 5‐Comparisonofriskidentificationknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginARtrainingconditions.
TimepointsParameter
Construction
workers
Safety
directors
Students
Construction
workersvs
Construction
workersvs
Safetydirectors
vsStudents
19 / 40
SafetydirectorsStudents
Pretraining
N101016MannWhitney
U=25.000
Z=‐1.929
p=0.054
MannWhitney
U=77.000
Z=‐0.161
p=0.872
MannWhitney
U=36.000
Z=‐2.368
p=0.018*
M4.2006.1004.188
SD1.6871.9691.424
Immediately
aftertraining
N101016MannWhitney
U=26.000
Z=‐1.874
p=0.061
MannWhitney
U=72.500
Z=‐0.418
p=0.676
MannWhitney
U=38.500
Z=‐2.314
p=0.021*
M7.1008.0007.125
SD1.3700.9430.885
Fourweeks
aftertraining
N101016MannWhitney
U=36.000
Z=‐1.119
p=0.263
MannWhitney
U=71.000
Z=‐0.490
p=0.624
MannWhitney
U=73.000
Z=‐0.384
p=0.701
M6.6007.2006.438
SD1.0750.9192.128
Pretrainingvs
Immediately
aftertraining
Mann
WhitneyU
7.00023.00012.000///
Z‐3.299‐2.096‐4.439///
p<0.001***0.036*<0.001***///
Immediately
aftertraining
vsFourweeks
aftertraining
Mann
WhitneyU
41.00026.000116.000///
Z‐0.710‐1.890‐0.475///
p0.4780.0590.635///
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.Threeasterisks(***)indicate
statisticallysignificantresultswithp<0.001.
Tab l e 6‐Comparisonofriskidentificationknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginslidetrainingconditions.
TimepointsParameter
Construction
workers
Safety
directors
Students
Construction
workersvs
Safetydirectors
Construction
workersvs
Students
Safetydirectors
vsStudents
Pretraining
N11916MannWhitney
U=21.000
Z=‐2.222
p=0.026*
MannWhitney
U=85.000
Z=‐0.152
p=0.879
MannWhitney
U=12.000
Z=‐3.457
p<0.001***
M4.3646.4444.250
SD2.0141.0141.125
Immediately
aftertraining
N11916MannWhitney
U=34.000
MannWhitney
U=87.000
MannWhitney
U=53.500
M6.6367.2226.688
20 / 40
SD1.1201.2021.352
Z=‐1.245
p=0.213
Z=‐0.051
p=0.959
Z=‐1.080
p=0.280
Fourweeks
aftertraining
N11916MannWhitney
U=40.500
Z=‐0.720
p=0.472
MannWhitney
U=81.000
Z=‐0.363
p=0.717
MannWhitney
U=56.000
Z=‐0.956
p=0.339
M6.0916.3335.813
SD0.8311.2251.276
Pretrainingvs
Immediately
aftertraining
Mann
WhitneyU
26.00027.50022.500///
Z‐2.316‐1.235‐4.052///
p0.021*0.217<0.001***///
Immediately
aftertraining
vsFourweeks
aftertraining
Mann
WhitneyU
45.50027.50091.000///
Z‐1.041‐1.234‐1.431///
p0.2980.2170.152///
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.Threeasterisks(***)indicate
statisticallysignificantresultswithp<0.001.
4.2.2RiskAssessment
TheresultsofriskassessmentknowledgescoresaredepictedinFig.5andTable7.Since
thenormalitytestyieldedapvaluelessthan0.05,indicatingthatthescoresdidnotpassthe
normalitytest,weemployedtheMannWhitneyUtesttodeterminesignificantdifferences
betweentheexperimentalgroups.Bothgroupsshowedasignificantincreaseinrisk
assessmentknowledgescoresaftertraining,indicatingtheeffectivenessofbothtraining
methodsinimprovingparticipants’riskassessmentknowledge.Whenresultswerecompared
immediatelyaftertrainingandfourweeksaftertraining,onlytheslidegroupshoweda
significantdrop;theARgroupdidnotexhibitanysignificantdeclineinscores.Accordingto
Tab l e 7,therewerenosignificantdifferencesinriskassessmentknowledgebetweenthetwo
groups,indicatingthatbothgroups’knowledgebaseswerecomparable.Furthermore,there
werenosignificantdifferencesinscoresbetweenthetwogroupsimmediatelyaftertraining
andfourweeksaftertraining.
21 / 40
Fig.5.RiskassessmentknowledgescoreforslidetrainingandARtraining.
Tab l e 7‐Comparisonofriskassessmentknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginARandslidetrainingconditions.
TimepointsParameterARSlideARvsSlide
Pretraining
N3636MannWhitneyU
=624.500
Z=‐0.276
p=0.783
M4.314.25
SD1.2831.204
Immediatelyafter
training
N3636MannWhitneyU
=620.000
Z=‐0.322
p=0.747
M6.866.81
SD1.3971.411
Fourweeksafter
training
N3636MannWhitneyU
=567.500
Z=‐0.933
p=0.351
M6.335.97
SD1.6211.158
Pretrainingvs
Immediatelyafter
training
MannWhitneyU131.500108.000/
Z‐5.922‐6.212/
p<0.001***<0.001***/
Immediatelyafter
trainingvsFourweeks
MannWhitneyU524.500443.500/
Z‐1.416‐2.362/
22 / 40
aftertrainingp0.1570.018*/
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.Threeasterisks(***)indicate
statisticallysignificantresultswithp<0.001.
WithintheARgroup,Table8presentstheresultsofriskassessmentknowledgescores.
Participantsinallthreecategoriesshowedsignificantimprovementswhencomparingpre
trainingandimmediatelyaftertrainingscores.Whencomparingscoresimmediatelyafter
trainingandfourweeksaftertraining,noneofthethreecategoriesshowedsignificant
decreases.Moreover,thedatashowedsignificantdifferencesinthepretrainingscores
betweenconstructionworkersandsafetydirectors,aswellasbetweensafetydirectorsand
students.Table9displaystheresultsofriskassessmentknowledgescoreswithintheslide
group.Whencomparingpretrainingandimmediatelyposttrainingresults,participantsinall
threecategoriesdemonstratedstatisticallysignificantgains.Therewerenosignificant
decreasesinanyofthethreecategorieswhencomparingscoresimmediatelyaftertraining
andfourweeksaftertraining.Additionally,theresultsshowedstatisticallysignificant
differencesinthepretrainingandfourweeksaftertrainingscoresofconstructionworkers
andsafetydirectors,aswellassafetydirectorsandstudents.
23 / 40
Tab l e 8‐Comparisonofriskassessmentknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginARtrainingconditions.
TimepointsParameter
Construction
workers
Safety
directors
Students
Construction
workersvs
Safetydirectors
Construction
workersvs
Students
Safetydirectors
vsStudents
Pretraining
N101016MannWhitney
U=12.000
Z=‐3.089
p=0.002**
MannWhitney
U=78.000
Z=‐0.109
p=0.913
MannWhitney
U=28.000
Z=‐2.859
p=0.004**
M3.9005.4003.875
SD1.1970.5161.310
Immediately
aftertraining
N101016MannWhitney
U=29.000
Z=‐1.628
p=0.103
MannWhitney
U=78.500
Z=‐0.082
p=0.935
MannWhitney
U=46.500
Z=‐1.810
p=0.070
M6.6007.6006.563
SD1.1741.5061.365
Fourweeks
aftertraining
N101016MannWhitney
U=32.000
Z=‐1.388
p=0.165
MannWhitney
U=78.500
Z=‐0.083
p=0.934
MannWhitney
U=53.000
Z=‐1.447
p=0.148
M6.1007.0006.063
SD1.4491.6331.692
Pretrainingvs
Immediately
aftertraining
Mann
WhitneyU
6.00011.00023.000///
Z‐3.434‐3.068‐4.019///
p<0.001***0.002**<0.001***///
Immediately
aftertraining
vsFourweeks
aftertraining
Mann
WhitneyU
37.00039.000105.000///
Z‐1.007‐0.851‐0.888///
p0.3140.3950.375///
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Twoasterisks(**)indicatestatisticallysignificantresultswithp<0.01.Threeasterisks(***)indicate
statisticallysignificantresultswithp<0.001.
Tab l e 9‐Comparisonofriskassessmentknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginslidetrainingconditions.
TimepointsParameter
Construction
workers
Safety
directors
Students
Construction
workersvs
Safetydirectors
Construction
workersvs
Students
Safetydirectors
vsStudents
Pretraining
N11916MannWhitney
U=5.000
MannWhitney
U=79.000
MannWhitney
U=20.000
M3.8185.4443.875
24 / 40
SD0.7510.5271.310
Z=‐3.510
p<0.001***
Z=‐0.463
p=0.643
Z=‐3.190
p=0.001**
Immediately
aftertraining
N11916MannWhitney
U=31.000
Z=‐1.432
p=0.152
MannWhitney
U=81.000
Z=‐0.356
p=0.721
MannWhitney
U=33.000
Z=‐2.258
p=0.024
M6.7277.6676.375
SD1.6181.4141.088
Fourweeks
aftertraining
N11916MannWhitney
U=19.000
Z=‐2.426
p=0.015*
MannWhitney
U=69.500
Z=‐0.967
p=0.334
MannWhitney
U=27.500
Z=‐2.582
p=0.010*
M5.8186.8895.563
SD0.8740.9281.209
Pretrainingvs
Immediately
aftertraining
Mann
WhitneyU
3.0008.50016.000///
Z‐3.842‐2.922‐4.356///
p<0.001***0.003**<0.001***///
Immediately
aftertraining
vsFourweeks
aftertraining
Mann
WhitneyU
41.00023.50078.000///
Z‐1.334‐1.551‐1.953///
p0.1820.1210.051///
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.Twoasterisks(**)indicatestatistically
significantresultswithp<0.01.Threeasterisks(***)indicatestatisticallysignificantresultswithp<0.001.
4.2.3RiskResponse
TheresultsoftheriskresponseknowledgescoresarepresentedinFig.6andTabl e 10.
Asthenormalitytestyieldedapvaluelessthan0.05,indicatingafailuretopassthenormality
test,theMannWhitneyUtestwasemployedtodeterminestatisticallysignificantdifferences
betweentheexperimentalgroups.Whencomparingpretrainingandimmediatelyafter
trainingriskresponseknowledgeratings,bothgroupsshowedstatisticallysignificantgains.
Onlytheslidegrouphadasignificantlossinscoreswhencomparingimmediatelyaftertraining
andfourweeksaftertraining;theARgroupdidnotexhibitanysignificantdecline.According
toTable10,therewerenosignificantdifferencesinthetwogroups’scoresofriskresponse
knowledge,indicatingthattheirstartingpointsfortheexperimentwereaboutthesame.
Additionally,therewerenosignificantdifferencesinthetwogroups’resultsimmediatelyafter
trainingandfourweeksaftertraining.
25 / 40
Fig.6.RiskresponseknowledgescoreforslidetrainingandARtraining.
Tab l e 10‐Comparisonofriskresponseknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginARandslidetrainingconditions.
TimepointsParameterARSlideARvsSlide
Pretraining
N3636MannWhitneyU
=610.000
Z=‐0.436
p=0.663
M6.366.31
SD2.1931.721
Immediatelyafter
training
N3636MannWhitneyU
=582.500
Z=‐0.751
p=0.452
M7.837.64
SD1.6481.437
Fourweeksafter
training
N3636MannWhitneyU
=532.500
Z=‐1.325
p=0.185
M7.256.72
SD1.5921.892
Pretrainingvs
Immediatelyafter
training
MannWhitneyU384.500368.000/
Z‐3.005‐3.230/
p0.003**0.001**/
Immediatelyafter
trainingvsFourweeks
MannWhitneyU503.000447.000/
Z‐1.659‐2.300/
26 / 40
aftertrainingp0.0970.021*/
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.Twoasterisks(**)indicatestatistically
significantresultswithp<0.01.
Table11displaystheriskresponseknowledgescoreswithintheARgroup.Onlythe
studentsshowedsignificantimprovementwhencomparingpretrainingandimmediatelyafter
trainingscores.Furthermore,nosignificantdeclineswereobservedinanyofthethree
participantcategorieswhencomparingscoresimmediatelyaftertrainingandfourweeksafter
training.Furthermore,thedataindicatednosignificantdifferencesinthescoresofthethree
typesofparticipantsatthethreetimepointsintheirrespectivepairwisecomparisons.The
findingsoftheslidegroup’sriskresponseknowledgescoresareshowninTable12.Participants
inallthreecategoriesdisplayedsignificantimprovementswhencomparingpretrainingand
immediatelyaftertrainingscores.Similarly,whencomparingscoresimmediatelyaftertraining
andfourweeksaftertraining,noneofthethreecategoriesofparticipantsshowedsignificant
decreases.Additionally,thedatarevealednosignificantdifferencesinthescoresofthethree
typesofparticipantsatthethreetimepointsintheirrespectivepairwisecomparisons.
Tab l e 11‐Comparisonofriskresponseknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginARtrainingconditions.
TimepointsParameter
Construction
workers
Safety
directors
Students
Construction
workersvs
Safetydirectors
Construction
workersvs
Students
Safetydirectors
vsStudents
Pretraining
N101016MannWhitney
U=36.500
Z=‐1.044
p=0.296
MannWhitney
U=71.000
Z=‐0.481
p=0.631
MannWhitney
U=47.000
Z=‐1.757
p=0.079
M6.3007.0006.000
SD2.0032.5822.098
Immediately
aftertraining
N101016MannWhitney
U=39.000
Z=‐0.876
p=0.381
MannWhitney
U=77.500
Z=‐0.134
p=0.893
MannWhitney
U=68.500
Z=‐0.618
p=0.537
M7.7008.2007.688
SD1.4181.3981.957
Fourweeks
aftertraining
N101016MannWhitney
U=33.000
Z=‐1.361
p=0.174
MannWhitney
U=67.500
Z=‐0.683
p=0.494
MannWhitney
U=54.000
Z=‐1.397
p=0.162
M7.1007.8007.000
SD0.9941.2292.033
Pretrainingvs
Immediately
aftertraining
Mann
WhitneyU
28.50033.50071.000///
Z‐1.656‐1.290‐2.183///
27 / 40
p0.0980.1970.029*///
Immediately
aftertraining
vsFourweeks
aftertraining
Mann
WhitneyU
34.00038.000101.500///
Z‐1.249‐0.936‐1.021///
p0.2120.3490.307///
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.
Tab l e 12‐Comparisonofriskresponseknowledgescorespretraining,immediatelyafter
training,and4weeksaftertraininginslidetrainingconditions.
TimepointsParameter
Construction
workers
Safety
directors
Students
Construction
workersvs
Safetydirectors
Construction
workersvs
Students
Safetydirectors
vsStudents
Pretraining
N11916MannWhitney
U=39.500
Z=‐0.814
p=0.416
MannWhitney
U=71.000
Z=‐0.874
p=0.382
MannWhitney
U=46.500
Z=‐1.513
p=0.130
M6.3647.0005.875
SD1.4331.1182.094
Immediately
aftertraining
N11916MannWhitney
U=40.500
Z=‐0.713
p=0.476
MannWhitney
U=86.500
Z=‐0.075
p=0.940
MannWhitney
U=57.500
Z=‐0.839
p=0.402
M7.5468.0007.500
SD1.2141.1181.751
Fourweeks
aftertraining
N11916MannWhitney
U=31.500
Z=‐1.402
p=0.161
MannWhitney
U=88.000
Z=0
p=1.000
MannWhitney
U=53.000
Z=‐1.094
p=0.274
M6.5467.3336.500
SD1.5081.2252.394
Pretrainingvs
Immediately
aftertraining
Mann
WhitneyU
34.50020.00070.500///
Z‐1.753‐1.881‐2.220///
p0.080*0.060*0.026*///
Immediately
aftertraining
vsFourweeks
aftertraining
Mann
WhitneyU
34.00028.50095.000///
Z‐1.777‐1.103‐1.262///
p0.0760.2700.207///
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.Anasterisk(*)indicatesstatisticallysignificantresultswithp<0.05.
28 / 40
4.3AnalysisofTaskLoad
Inthissection,thetaskloadexperiencedbytheparticipantswasanalyzed.Fig.7displays
thescoresobtainedforthesixitemsassessedinthetaskload.Thedatadidnotpassthe
normalitytest(p<0.05),andtheMannWhitneyUtestwasusedtodeterminestatistically
significantdifferencesbetweenthetwoexperimentalgroups.TheresultspresentedinTable
13indicatethattherewerenosignificantdifferencesinthetaskloadobservedacrossthe
differenttrainingconditions.
Fig.7.Tas kloadforARtrainingandslidetraining.
Tab l e 13‐Ta s kloadscoresimmediatelyaftertraininginARandslidetrainingconditions.
ARvsSlide
Mental
Workload
Physical
Workload
Tempora l
Workload
Training
Effort
Training
Difficulty
Stressed/An
noyed
MannWhitneyU550.000617.000608.000635.500645.000647.000
Z‐1.111‐0.351‐0.453‐0.142‐0.034‐0.011
p0.2670.7250.6510.8870.9730.991
4.4AnalysisofSystemUsability
TheanalysisofsystemusabilityisdepictedinFig.8.Thedatapassedthenormalitytest
(p>0.05)andhomogeneityofvariancetest(p>0.05),andtheindependentsamplettestwas
usedtoanalyzesignificantstatisticaldifferencesbetweenthetwoexperimentalgroups.The
analysispresentedinTab l e14demonstratesthattherearenosignificantdifferencesinthe
systemusabilityobservedacrossdifferenttrainingconditions.
29 / 40
Fig.8.SystemusabilityforARtrainingandslidetraining.
Tab l e 14‐SystemusabilityscoresimmediatelyaftertraininginARandslidetrainingconditions.
ARvsSlideNMSD95%CItdfp
SystemUsability
363.9000.529
[0.263,0.302]0.137700.891
363.8810.666
Note:Nindicatesthesamplesize.Mindicatesthemeanofthescores.SDindicatesthestandarddeviationofthe
scores.CIindicatestheconfidenceinterval.
5.Discussions
ThisstudyaimstocomparetheeffectsofslidebasedtrainingandARbasedtrainingon
objectiveperformancemeasuresandsubjectiveevaluations.Twoposttrainingtestswere
carriedout,separatedbyfourweeks,toevaluatetheeffectsoftrainingovertimeand
comparetheshort‐andlongtermtrainingeffects.Theresultsofthisstudyprovideevidence
supportingtheeffectivenessofARindeliveringmetroconstructionsafetyrelatedknowledge.
Thesefindingsareconsistentwithpriorresearch,demonstratingthatARhasamoderately
positiveinfluenceonbothknowledgeacquisitionandretention(GarzónandAcevedo,2019).
Thefindingsofthisstudyshowthat,intermsofshorttermacquisitionofrisk
identificationknowledge,theARgroupexhibitedasignificantlyhighertrainingeffect
comparedtotheslidegroup.ThissuggeststhatARtechnologyisparticularlybeneficialforrisk
identificationtraining.Previousstudieshaverevealedsimilarfindings,whichhaveshownthat
ARtrainingenhancestrainingefficiency(HouandWang,2013;Koumaditisetal.,2019)and
30 / 40
improvesperformanceinmaintenancetasks,withthepositiveeffectsofARtraining
increasingastaskcomplexityrises(Liuetal.,2022;ZhangandRobb,2021).Onepossible
explanationforthisdifferenceisthatAR,comparedtotraditionalmethods,enhances
informationclarity,facilitatesfasterknowledgeacquisition,providesgreaterstimulation,and
offersadequateguidance(Wolfetal.,2021).However,intermsofshorttermacquisitionof
riskassessmentandriskresponseknowledge,thisstudyfoundnosignificantdifference
betweentheARgroupandslidegroup.Thissuggeststhatextendedreality(XR)technologyis
notnecessarilysuperiortotraditionalmethodsforshorttermknowledgeacquisitioninrisk
assessmentandriskresponse(Kaplanetal.,2020;Theesetal.,2020).Thisobservationmay
alsobeattributedtothefactthattheARvisualizationusedinthisstudysolelyconsistedof
staticmodels.Futureresearchcouldinvestigatewhetherdynamicmodelscontributetothe
shorttermacquisitionofriskassessmentandriskresponseknowledge.Nevertheless,itis
importanttonotethatbothgroupsdemonstratedasignificantimprovementinshortterm
safetyknowledgefollowingthetraining,highlightingtheimportanceofsafetytraining.This
emphasizesthatsafetytrainingpriortoengaginginmetroconstructionoperationscan
effectivelyenhanceriskidentification,riskassessment,andriskresponsecapabilities,thereby
reducingonsiteaccidents(Sacksetal.,2013;Shringietal.,2023).
Intermsoflongtermretentionofriskidentification,riskassessment,andriskresponse
knowledge,theslidegroupexhibitedsignificantdecreasesinknowledgefourweeksafter
training.Severalfactorscouldcontributetothisdecline,includingthecomplexityofthe
knowledgebeingretained,naturalforgetfulnessovertime,orthelackofexplicitinformation
providedtoparticipantsregardingthefollowuptestafterfourweeks.However,theARgroup
didnotshowasignificantdecrease.Thisshowsthat,incontrasttotraditionalslidebased
training,individualsmaybelesslikelytoforgetinformationafterreceivingARtraining.AR
trainingmayofferadvantagesintermsofknowledgeretention.Thismaybeduetothefact
thatARtrainingcanprovideimmersiveandinteractivelearningexperiences,enhance
engagementandimproveknowledgeretention,helpingtopromotebettermemory.Dalinget
al.(2023)conductedastudycomparingtheshort‐andlongtermeffectsofARtrainingand
traditionaltrainingandfoundnosignificantdifferencesbetweenthetwoapproaches.
However,whencontrollingfortheparticipants’age,ARtrainingyieldedrelativelybetter
outcomes.Furthermore,thetimeintervalforassessingthelongtermeffectivenessofthe
trainingswasonlytwoweeksintheirstudy,whichmayexplainthelackofsignificant
differencesinknowledgeretentionbetweenthetwoapproachesandtheinconsistencywith
theresultspresentedinthispaper.Thefindingsofthispaperareconsistentwithevidencefrom
otherpreviousstudies(Gargrishetal.,2021;Lametal.,2021).Therefore,Q1hasbeen
answered.
Intermsofsubjectiveevaluations,specificallytaskloadandsystemusability,thisstudy
didnotfindsignificantdifferencesbetweenthetwotrainingconditions.Thisindicatesthat
theARapplicationwaswelldesigned,andparticipantsexpressedquiteconfidenceinbeing
31 / 40
trainedusingthetechnology.Thetaskloadresultsindicatethatneithertrainingmethod
imposedsignificantphysicalormentaldemandsandthatbothwereequallyeffectivein
promotinglearning.Additionally,participantsdidnotexperiencestressordistressduringthe
training,whichmayexplaintheirsimilarperformanceintermsofshorttermknowledge
acquisition.ThesefindingsdifferfrompreviousresearchthatreportedparticipantsinAR
trainingexperiencedlessfrustrationcomparedtotraditionaltraining,withasignificant
differenceobserved(Wuetal.,2023b).Thesystemusabilityscoreswerehighforbothtraining
groups,indicatingthatparticipantsfoundboththeslidesandARtrainingtobeefficientand
useful.Furthermore,thedatapresentedinthispaperdemonstratethattheARapplication
receivedhighersystemusabilityscoresthantraditionaltraining,whilealsoyieldinglowertask
loadscores.Thisfindingsuggests,tosomeextent,thattheARapplicationoffersimproved
usabilityandreducedtaskload.Therefore,Q2hasbeenanswered.
Thisstudyoffersseveralsignificantcontributions.Firstly,itdevelopedanovelprototype
ofanARsafetytrainingsolutiontailoredspecificallyformetroconstruction.Theeffectiveness
ofthissolutionwasevaluatedthroughausercenteredcomparativeassessment,providing
valuableinsightsintoitssuitabilityandefficacy.Importantly,theproposedARsystemutilizes
commonlyavailablemobilephonesandtablets,makingitacosteffectivetrainingtool.This
allowsforARbasedgrouptrainingwithoutthelimitationsimposedbytheavailabilityof
specializedARequipment,suchasHMDs.Thisaccessibilityenhancesthefeasibilityand
scalabilityofimplementingARtraininginthemetroconstructionenvironment.TheARsystem
employs3DmodelscreatedinSketchupandimportedintotheARplatformtovisualize
hazardousscenariosrelatedtovarioustopics,includingmetroconstruction.Thisflexibility
facilitateseffectivetrainingondifferentsubjectsinvolvingdangeroussituations,extending
thepotentialapplicationsofthedevelopedARsystembeyondmetroconstruction.Secondly,
thisstudyevaluatesobjectiveperformancemeasuresandsubjectiveevaluationsatthree
stages:pretraining,immediatelyaftertraining,andfourweeksaftertraining.Itcoversthe
entiresafetyriskmanagementprocess,includingriskidentification,riskassessment,andrisk
response.Byevaluatingknowledgeacquisition,retention,andsubjectiveperception,this
studyprovidesacomprehensiveunderstandingoftheeffectivenessofARbasedmetro
constructionsafetytraining.Incorporatingriskidentification,riskassessment,andrisk
responseintotheevaluationprocessfurtherenhancesthepracticalrelevanceofthe
evaluationresults.Thisstudyexpandstheunderstandingoftheapplicabilityandeffectiveness
ofARbasedmetroconstructionsafetytrainingfrombothuserandsafetyriskmanagement
perspectives.Itprovidesvaluableinsightsforthedevelopmentandimplementationofmore
effectivesystemsaimedatenhancingworkersafetyinmetroconstruction,contributingtothe
existingbodyofknowledgeinthisfield.Byincreasingtrainees’awarenessandunderstanding
ofsafetymeasuresandimprovingtheirperformance,theseARbasedtrainingsystemshave
thepotentialtoenhanceoverallsafetyandincreasethelikelihoodofsurvivalinemergency
situations.Ultimately,researchonusercenteredARbasedmetroconstructionsafetytraining
32 / 40
systemshasthepotentialtodrivetheadvancementofincreasinglyeffectivetoolsforspecific
usersandsafetyriskmanagement.Thefindingsandrecommendationspresentedinthisstudy
canguidefutureresearchanddevelopmenteffortstowardcreatingmoreeffectiveand
customizedARtrainingsolutionstailoredtothespecificneedsofusersandsafetyrisk
managementrequirements.
Thisstudyhasseverallimitationsthatcouldbeaddressedinfutureresearch.Firstly,the
limitedsamplesizemayrestricttheabilitytofullyinvestigatethepotentialadvantagesofAR
trainingfordifferenttypesofusers.Futurestudiescouldaimtoincreasethesamplesize,
diversity,andreliabilityofparticipantstoobtainmorerobustfindingsandgeneralizethe
resultstoabroaderpopulation.Secondly,theARtraininginthisstudyonlypresentedstatic
unsafescenariosthroughmobilephonesandtablets,withoutillustratingtheconsequencesof
accidents.FutureresearchcouldincorporatedynamicARscenariosthatdemonstratethe
severeconsequencesofunsafebehavioraswellasuseimmersiveopticalseethrough
solutions(Lovreglioetal.,2024).BycomparingtheeffectivenessofstaticARtraining(without
accidentconsequences)anddynamicARtraining(withaccidentconsequences),researchers
canevaluatetheimpactofincorporatingconsequencesonimprovingriskidentification,risk
assessment,andriskresponsecapabilities.Additionally,investigatingpotentialdifferences
betweenusingARimmersivesolutions(e.g.,opticalseethough)andmobilephones/tablets
wouldbeworthwhile.Furthermore,thisstudyfallsshortofadequatelyaddressingthe
hierarchyofhazardcontrol,includingelimination,isolation,engineeringcontrols,
administrativecontrols,andpersonalprotectiveequipment,withinthecontextofrisk
responseduringtrainingandassessment.Futureresearchcouldincorporatethiscontentinto
trainingandassessment.Afinallimitationofthisstudyisthatitreliessolelyonsubjective
ratingstoassesstaskloadandsystemusabilitymaylimittherobustnessoftheresults.Future
researchcouldincludeincorporatingadditionalphysiologicaldatasources,suchaseye
tracking,electroencephalography(EEG)measurements,andcomputervisiontechniques
(BlaesingandBornewasser,2021;Drouotetal.,2022;Shietal.,2020).
6.Conclusion
Thisstudyaimstocomparetheshorttermandlongtermeffectsonobjective
performancemeasuresandsubjectiveevaluationsofbothtraditionalandARtraining.To
achievethis,anovelARsafetytrainingprototypewasdevelopedformetroconstruction,and
itwascomparedtoanequivalentslidebasedsafetytraining.Atotalof72participantswere
separatedintotwotraininggroupsfortheinvestigation.Thesafetycasestudychosen
encompassedtheentiresafetyriskmanagementprocess,includingriskidentification,risk
assessment,andriskresponse.
TheresultsdemonstratethatARtrainingismoreeffectivethantraditionaltrainingin
regardstoshorttermknowledgeacquisitionofriskidentification,aswellaslongterm
33 / 40
knowledgeretentionofriskidentification,riskassessment,andriskresponse.Regarding
acquiringriskassessmentandriskresponseknowledgeintheshortterm,aswellastheoverall
learningexperience,ARtrainingperformssimilarlytotraditionaltraining.Thesefindings
highlighttheeffectivenessofARtraininginenhancingknowledgeacquisitionandretentionin
safetytraining.Whileitmaynotexhibitsignificantadvantagesovertraditionalmethodsinall
aspectsofassessment,itstilloffersavaluablealternativethatcanimprovetrainees’learning
experienceandoutcomes.Thesefindingshaveimplicationsforthedesignoffuturesafety
trainingguidelinesandrecommendations.
DataAvailabilityStatement
Alldatathatsupportthefindingsofthisstudyareavailablefromthecorresponding
authoruponreasonablerequest.
Acknowledgements
ThisresearchwassupportedbytheMinistryofEducationofHumanitiesandSocial
ScienceprojectofChina(GrantNo.23YJA630069)andtheJiangsuProvinceConstruction
SystemScienceandTech n o log y Project(GrantNo.2023JH04004).
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AR- and VR-based training is increasingly being used in the industry to train workers safely and effectively for new tasks. In this study, we investigated and compared the effects of AR-, VR- and video-based training on short- and long-term objective performance measures and subjective evaluations in a manual assembly task. Our results showed that there was no difference between AR-, VR- and video-based training concerning the objective performance measures task completion time and error count. However, in the subjective evaluations VR-based training showed a significantly higher perceived task load and a lower usability rating than the AR- and video-based training regimes. An exploratory analysis additionally revealed partially better results for AR than for VR after adjusting the data for the age of the participants. Future research should further investigate the advantage of AR- and video-based methods over VR when the age and technology experience of participants are taken into account.