1. Introduction 

Learning iabout istudents’ ilearning istyles ican ibe ivery ibeneficial ifor iboth iteachers iand istudents. iInvolving istudents iin ithe iactive ilearning iphase inecessitates irecognizing iand icomprehending ilearners’ ilearning istyles iand iteachers’ iteaching istyles. iTypes iof ilearning iplay ia iconsiderable irole iin ilearners’ ilives. iStudents imay iincorporate itheir ilearning istyle iinto itheir ilearning iprocess ias ithey ibecome imore iaware iof iit. iStudents ilearn iin ivarious iways, iand iteachers imust idesign itheir icourses iaccording ito idifferent itypes iof ilearning. iLearning iskills, icreativity iand ilife iand icareer iskills iare ievidence ithat istudents imaster ithe iprocess iof icapability iand idevelopment, iintegration iand iknowledge iassessment ifrom idifferent isubjects iand isources iof iunderstanding i[1]. iIdentifying istudents’ ilearning istyles iwill ihelp ieducators iplan itheir iteaching imethods iand iactivities ieffectively ito iachieve itheir ilearning ioutcome i[2]. iThe ilearning istyle iof istudents iis if ithe isupporting iforms iof iactive ilearning i[3]. iThe istyle iof ilearning iplays ian iimportant irole iin iensuring ithat ithe ilearning iprocess iis iperformed ieffectively. i

Students ishould ihave i21st-century iskills, iespecially isoft iskills, ito ienhance itheir iemployability iand ivalues. i[4]. iUniversities imust imake ivital ielements iof ieducation ito iconduct ilearning iby iintroducing ieffective istudent ilearning iprocesses iin ithe igrowth iof iinternational ieducation iin ithe iformulation iof iskills iin ithe itwenty-first icentury. i[5]. iTo iensure ithat iall istudents ireceive iknowledge ifrom ithe ilearning iprocess, ieducators imust iobserve iand iconsider ithe idiscrepancies iand isimilarities ibetween istudents iand iuse ithe iknowledge ito iprepare ifor ithe ilearning iprocess i[6] ito idesign ilearning iregardless iof ithe ilearning istyle iof ithe istudents i[7]. iTo icompare ilearning istyle ipreferences ibetween iengineering iand inon-engineering istudents iin iMalaysia, ithis istudy iused ia imeasurement imethod icalled ithe iKolb iLearning iStyle iInventory i(LSI) isince iLSI iis iable ito iprovide ia isimple ivalidation iof ithe iExperiential iLearning iTheory.

1.1. Kolb iLearning iStyle

The iExperiential iLearning iTheory iof iKolb iforms ithe ibasis iof ithe iparadigm iof iKolb’s ilearning istyle. iExperiential ilearning, iwhich iis idistinct ifrom iother icognitive ilearning itheories, inotes ithe iincrease iin ilearning iprocess iinteractions i[8]. iThe iKolb iLearning iStyle iInventory i(LSI) iis ione imethod ifor imeasuring ilearners’ ipreferential iteaching istyle. iKolb’s ilearning istyle, ior imore igenerally iknown ias iExperiential iLearning iTheory i(ELT), idescribes ilearning ias ia iprocess iin iwhich iinformation iis icreated iby itransforming iexperience i[9]. iLearning iis ia iprocess, iaccording ito iKolb, iand iknowledge iis ithe itransformation iof iexperience i[10]. iKolb ialso iindicates ithat, ito ihave ia icomplete ilearning iexperience, istudents imust igo ithrough iall ifour iphases iof ithe ilearning icycle, ias idepicted iin iFigure i1. iThese ifour istages inot ionly iallow istudents ito iexplore ia isubject ithrough ivarious iactivities iand iviewpoints ithoroughly, ibut ithey ialso iaccommodate idifferent ilearning istyles.

Figure i1: iThe iLearning iModel iof iExperiential iLearning iat iKolb’s iLearning iStyles

In ithe iKolb iview, ilearning istyles irefer ito iprocesses iin iwhich ithe iperson iorganizes ithe iideas, irules iand iprinciples ithat iaddress ithem iin idealing iwith inew isituations. iIn ipractice, ione iof ithe imost ipowerful imethods iin ithe ilearning ianalysis iof ithe iindividual iis ithe itheory iof ithe iKolb ilearning istyle. iThe ilearning istyles ias ia icollection iof ivalues, iinterests, iand ihabits ithat ipeople iattempt ito ilearn iabout ia iparticular isituation iby iusing iit i[11]. iPrevious iresearch iput iit ianother iway: ithe ilearner ifirst iconducts ian iaction i(concrete iexperience), ithen itries ito ithink iabout iit i(reflective iobservation), ithen idevelops ia ihypothesis i(abstract iconceptualization), iand ifinally iattempts ito iexempt iit i(active iexperimentation) i[12]. iAccording ito iKolb, iexperiential ilearning ican ibe iused iin iboth iengineering iand inon-engineering ieducational ienvironments i[13]. iIt ienables istudents ito iparticipate iactively iin ithe ilearning iprocess ito idevelop iawareness, iskills, ivalues, iand iattitudes ithrough idirect iexperience. iThe ilearning istages iwill ipromote iknowledge itransfer iby iproviding idirect ipractice itailored ito istudent iexpertise’s iscope i[14].  iThis ilearning imethod ienables istudents ito icreate itheir iawareness iand iexperience iand ithe iacquisition iof inew iskills iand iknowledge. iIt istresses ithat ilearners ilearn ito iuse itheir iexpertise iand iexperience ito isolve itheir iproblems. iThis istudy iaimed ito icompare ithe ipreferential ilearning istyles iof iengineering iand inon-engineering istudents iin iMalaysia iby iusing ia iKolb iLearning iStyle iInventory i(LSI) imodel ias ia ireference imodel ibecause iit ican iprovide ia ibasic ifoundation ifor ivalidating ithe itheory iof iexperiential ilearning.

2. Learning iStyle iin iTechnical iand iVocational iEducation

Technical iand iVocational iEducation iis ian iimportant iroad ito ivocational ieducation iand ithe igrowth iof iskills. iTo imeet iMalaysia’s ieconomic ineeds, ithe icountry’s iTVET ienrollment imust ibe iincreased iby i2.5 itimes iby i2025. iTransformation iProgramme i[15]. iThe ihuman iresources ito imeet ithis idemand, ihowever iare iinadequate. iRight iat ithe itime. iMoreover, iTVET iis iregarded ito ibe iless iappealing ithan itraditional iuniversity ieducation. iThis ihas iled ito ia ishortage iof, iespecially ihighly iskilled, iTVET istudents. iMalaysia imust itherefore imove ifrom ithe icommonly iaccepted iassumption ithat ithe ionly icareer ipath ifor iMalaysian iyouth iis itraditional iuniversity ieducation, iand ialso iemphasize iTVET ias ia ivalid ihigher ieducation ichoice. i

Technical iand iVocational ieducation istudents iare iexposed ito ian ieducational isystem iaimed iat igetting ia ijob. i(1) iA icomponent iof ian ieducational iactivity iaimed iat iproviding ithe inecessary iknowledge iand iskills ito icarry iout ia ispecific ijob, ioccupation ior iprofessional iactivity iin ithe ilabour imarket ican ibe itechnical iand ivocational ieducation. iAt ithe isame itime, iother itypes iof ieducation, iby itraining ipeople inot ionly ias iworkers ibut ialso ias icitizens, iact ias ian iadditional iform; i(2) ian iactivity iassociated iwith ithe itechnology itransition, iinnovation, iand igrowth iprocesses iKnowledge iand iskills imust ibe itransferred isince ithey iform ithe ifoundation iof itechnical iprogress iand igrowth i[16]. iIn itechnical iand ivocational iteaching, ias iin imany ifields iof iknowledge, iit iis iimportant ito iidentify iand iunderstand istudents idifferences ito iadopt ithe iinstitute’s ineeds ito ibest isuit ithe istudents’ ilearning iconditions iand iskills. iA ifact iin ithe iclassroom, iwhich ican ibe iseen iin iactual iscenarios ior iin ivirtual itechniques, iis ithe ineed ito iadapt iteaching imethods ito istudent ilearning istyles iand iinterests.

If ilearning istyles iare inot iidentified, ithey imay iinfluence ithe iteaching iand ilearning iprocess i[17]. iA ilack iof iknowledge iof ithe imodes iof ilearning ican ialso ibe iproblematic. iIn ithe iimplementation iamong istudents iof ithe iacceptable iand isuccessful ilearning istyles i[18]. iAcademic isuccess iwill ibe iimpaired ias ia iresult i[19]. iUnfortunately, iteacher-centred ilearning isessions iare iheld iby imost ieducators, iallowing ifewer istudents ito iengage iin ithe iprocess iand iactivities iof ilearning i[17]. iTherefore, ifor ithe iperformance iof istudents, ilearning istyle iis ian iimportant imatter. iThe istyle iof ilearning iwill iensure ithat ia ilearner ilearns iwell i[19]. iStudents ineed ito iidentify itheir ilearning istyles ito ibuild ion itheir ilearning iskills iand iexpand itheir ilearning iskills. iBy iposing ia ichallenge ior iusing ivarious ieducation imethods, ieducators iare ialso iexpected ito iencourage itheir istudents ito iidentify itheir ilearning istyle. i[20].

3. Material iand iMethod

The survey research design iwith ia iquantitative iapproach iwas iapplied iin ithis iresearch. iA iset iof iquestions iwas idesigned ibased ion ithe icollected ilearning istyle iand iactivities ifound iin iliterature ibased ion ithe iKolb iLearning iStyle iInventory. iA itotal iof i300 irespondents iwere irandomly iselected ifrom iall ifaculties iin iUniversiti iTun iHussein iOnn iMalaysia, iUTHM i(i.e. iFaculty iof iCivil iEngineering iand iBuilt iEnvironment, iFaculty iof iTechnology iManagement iand iBusiness, iFaculty iof iTechnical iand iVocational iEducation, iFaculty iof iElectrical iand iElectronic iEngineering, iFaculty iof iComputer iScience iand iInformation iTechnology, iFaculty iof iApplied iSciences iand iTechnology iand iFaculty iof iEngineering iTechnology). iThe isurvey iquestionnaire iconsisted iof itwo imain isections irepresenting ithe iLearning iGoals, iLearning iStyle iand iLearning iActivities. iThis iquestionnaire iwas ideployed ionline ifrom ithe iuniversity’s ionline iforum iand iplatform. iRespondents iwere iable ito icomplete ithe iquestionnaire iin iapproximately i10-15 iminutes.

4. Finding iand iDiscussion

The ifindings idiscussed iare ibased ion ithe idata iof ithe iLearning iGoals, iLearning iStyle iand iLearning iActivities iitems ithat iwere iconstructed. iData ithat ihad ibeen icollected iwere iused ito ianalyze iin ithe icontext iof iLearning iStyle icharacteristics, iand iT-test iwas iconducted ito idetermine iwhether ithere iare iany ivariations ibetween ithe itwo igroups iof ifields, ias iwell ias idescriptive istatistics isuch ias ifrequency iand ipercentage, ito ievaluate iand iinterpret ithe iresults iin ithis ireport. iThe iinterpretation iin ithe iresearch iinstrument iwas iused ito iexplain ithe ifrequencies iand ipercentages. iThe iagreement ilevel iwas iused ito iassess ithe istudents’ iperceptions iin iboth iareas, iwhich iwere ieither iYes ior iNo.

4.1. The iLearning iStyle iBetween iEngineering iand iNon-Engineering iStudents i(Descriptive iResults)

Based ion ia isurvey iconducted, ithe idifferent ilearning istyles iof iengineering iand inon-engineering istudents iwere igathered iand idivided iinto ifour iforms iof ilearning istyle idefined iby iKolb, ifollowing ithe ilearning istyle iDiverger, iAssimilator, iConverger iand iAccommodator. iTo ibetter iunderstand iboth iof ithese ilearning istyles, iit ishould ibe iunderstood ithat ithe iAssimilator ilearning istyle i(think iand iwatch) iis ia ivariation iof iReflective iObservation i(RO) iand iAbstract iConceptualization i(AC).Converger ilearning i(think iand ido) iis ia isynthesis iof iAbstract iConceptualization i(AC) iand iActive iExploration i(AE) i(AE). i iAccommodation ilearning istyle i(feel iand ido) iis ia icombination iof iActive iExperimentation i(AE) iand iConcrete iExperience i(CE) iand iDiverger ilearning istyle i(feel iand iwatch) iis ia icombination iof iConcrete iExperience i(CE) iand iReflective iObservation i(RO) i[21]. iThe ipercentage iof istudents’ idata idistribution ion ieach iKolb ilearning istyle idetermined iby iThe iKolb iLearning iStyle iInventory iis ishown iin iTable i1 iand iillustrated iin iFigure i2 ibelow.

Table i1: iResults iof iLearning iStyle iin iVocational iEducation ibetween iMalaysian iengineering iand inon-engineering istudents

Field	Kolb iLearning iStyle
	Converger		Assimilator		Accomodator		Diverger		Total
	f	%	f	%	f	%	f	%	f	%
Engineering	42	28	29	19.3	51	34	28	18.7	150	100
Non-Engineering	51	34	21	14	60	40	18	12	150	100

The iresults ishow ithat iAccommodator ilearning istyle iin iengineering istudents iis ithe ihighest ipercentage ithan iothers ilearning istyle iwith ivalue i(f i= i51, i34%) ifollowed iby iConverger i(f i= i42, i28%) iand iAssimilator i(f i= i29, i19.3%). iWhile iDiverger ilearning istyles ishows ithe ilowest ipercentage iwithin iengineering istudents iwith ivalues i(f i= i28, i18.7%). iOther ithan ithat, ia isimilar icondition iwas ishown iby inon-engineering istudents iwhere ithe iAccommodator ilearning istyle ishows ithe ihighest iworth ipercentage i(f i= i60, i40%) ifollowed iby iConverger i(f i= i51, i34%) iand iAssimilator i(f i= i21, i14%). iWhile ithe ilowest ivalue iof ipercentage iis iDiverger iwhich iis i(f i= i18, i12%).

Figure i2: iResults iof iLearning iStyle iin iVocational iEducation ibetween iMalaysian iengineering iand inon-engineering istudents

The findings of the study can be seen imore iclearly by referring to figure i3 ibelow iwhere iyou ican isee ithe isignificant idifferences ibetween ithe ifour ilearning istyles. iAlthough ithere iis ia ipercentage idifference ibetween ithe itwo ifields, iit ishows ithat imost iof ithe iengineering iand inon-engineering istudents ican ibe idescribed ias ian iaccommodator, iwhich iindicates ithey iare imost ipotent iin iConcrete iExperience iand iActive iExperimentation. i iInstead iof ilogic, ithey irely ion iintuition iwhich iprefers ilearning ifrom ipersonal iexperience, irelies ion igiven iknowledge irather ithan icarrying iout ihis/her iresearch, irequires ia iclear iexplanation ibefore istarting iwork i[22]. iIt ialso ishows ithat iboth iengineering iand inon-engineering istudents ihave istrengths ithat ilie iin itheir idesire ito iexecute iplans iand itasks ito itake ipart iin inew ievents i[23]. iThis iresult iis iin iline iwith ithe iKolb iLearning iStyles itrend, iwhich istates ithat istudents iwho iuse ithe iDoer iand iFeeler ilearning istyles iare ibest isuited ifor iteaching, itechnician, iand iengineering ijobs iand ihave ia ibackground iin ieducation, itechnical istudies, iand iengineering i[24]. i

Other ithan ithat, ithe ioverall iresult ishows iConverger iis ithe isecond-highest ipercentage ifor iboth ifields. iIn icontrast ito iengineering istudents, inon-engineering istudents iprefer itechnical itasks iand ibetter iinterpret icomplex iconcepts iand ihypotheses. iThey ialso ienjoy iexperimenting. iThis itype iof ilearning istyle’s istrengths ilie iin itheir iability ito iset igoals, isolve iproblems, iand imake idecisions i[23]. i

Apart ifrom ithat, iAssimilator ishows ithe ithird-highest ipercentage ifor iboth iengineering iand inon-engineering ifields. iThe iresults ishow ithat iengineering istudents ihave ia ihigher ipercentage ithan inon-engineering istudents. iThis imeans ithat iengineering istudent iwho ilearns iin ithis istyle ihas ia iwide irange iof iknowledge iand iarrange iit iin ithe imost ilogical iway i[22] icompared ito inon-engineering istudents. iIt ialso iindicates ithat ithese istudents iprefer irational, ifactual, iand iwell-thought-through iknowledge i[24]. iThe istrengths iof ithis ilearning istyle ilie iin itheir iability ito ischedule, icoordinate, ievaluate iand iengage iin iinductive ireasoning isystematically. iThe iresults iof ithis istudy iare iconfirmed iby ia istudy iconducted iby i[25] iin iwhich iengineering istudents ineed imore idiverse iknowledge igathered ifrom idifferent isources isince ithey imust iobserve ihow ito iexecute ithe itask ibefore ibeginning ito iperform iit. iThe iknowledge iis ipresented ifrom idifferent iangles iand iconcluded iin ia ilogical, isimple, iand iconcise imanner. iFinally, ithe itype iof ilearning ithat ishows ithe ifourth-highest ipercentage ifor iboth iengineering iand inon-engineering iis iDiverger. iThe ifindings ishowed ithat ithere iwas ia ihigher iproportion iof iengineering istudents icompare ito inon-engineering istudents. iIt iindicates ithat iengineering istudents iwith ia iparticular istyle iof ilearning iobserve ia isituation iand ithen ilook iat ithe isituation ilater ifrom imultiple iviewpoints, ilearning ifrom ieach ione i[22]. iBesides, iit ialso ishows ithat iengineering istudents ihave imore ieffective iat iseeing ia iparticular isituation ifrom idifferent iperspectives ithan inon-engineering istudents i[26].

Figure i3:Comparison iof iLearning iStyle iin iVocational iEducation ibetween iMalaysian iengineering iand inon-engineering istudents

Because iof ithe iinterest iin idesigning ithe ilearning iprocess, ieducators ihave ito iconsider ithe istyle iof ilearning iof idifferent istudents. iOther ithan ithat, ito imaximize ilearning ieffectiveness, ithe ilearning imethod ithat irelates ito ieach ilearning istyle iis imore iimportant ibecause ithe ilearning imethod ihas ia ilearning istyle irelated ito iit i[27]. iThe idifference ibetween ithe iway iinformation iwas iobtained iand iinterpreted iwas imore irelated ito ithe istyle iof ilearning ithat istudents ihad. iOne iof ithe ikey ireasons ifor igathering ilearning iefficacy iis ithe itype iof ilearning i[21]. iiThe suggest ithat iknowledge iof ithe ilearning istyles iof ilearners ican ibe iimportant ifor icurriculum iand iteaching iimprovement. iSimilarly, i[28] istate ithat iIf ithe ilearning istyles iof istudents iare ievaluated, iit iis ipossible ito isystematically iplan ilearning iactivities ithat ifurther istrengthen istrengths ior idevelop iweaker iphases ito imaximize ithinking iand iproblem-solving iskills.”

4.2. Comparison iof iLearning iStyle iBetween iEngineering iand iNon-Engineering iStudents i(Inferential iResults)

As ifor ithe icomparison ibetween iEngineering iand iNon-Engineering istudents, ithe iinference ianalysis ihad ishown ia inon-significant ivalue ibetween iboth igroups iin ipractising ilearning istyle iin itheir ilearning iprocess iwith imean iand isignificant ivalue i(Engineering i= i0.538, iNon-Engineering i= i0.562, ip=0.543). iAlthough ithere iis ia idifference iin ipercentage iand ifrequency ivalues, ithe iinference ivalue iindicates ino isignificant ivalue ifor iengineering iand inon-engineering istudents ilearning istyle. iThis ishows ithat iboth igroups iof istudents ihave iapproximately ithe isame ilearning istyle ibetween iengineering iand inon-engineering istudents.

Table i2: iThe iDifferences iof iLearning iStyle iBetween iEngineering iand iNon-Engineering iStudents

Field	Mean	Std iDeviation	Significant
Engineering	0.538	0.133	0.543
Non-Engineering	0.562	0.130

5. Conclusion

The istudy ishowed ithat ilearning istyles iare inecessary ifor ia icourse ito iachieve itotal ivalue ifrom ilearning. iWhile isharing icertain icharacteristics, imay ishow imajor idifferences iin iother iaspects ithat iaffect ilearning. iEducators iwho iare imindful iof ithese idifferences iand ican iarticulate ithese icharacteristics ihave ia ibetter ichance iof icreating igood iinstruction ifor ia iwide irange iof ilearners. iIn iknowing itheir istrengths iand iinterests iand iutilizing ithe ilearning icycle, iall ilearning istyles iwill ibecome istronger ifor istudents iexposed ito ilearning istyle imodels iand iKolb’s iLearning iStyle iInventory i(LSI), iwhich iwill ienable ithem ito ibecome imore iactive ilearners. iThis iresearch ican ibe ivery ibeneficial ifor ieducators iwho iwant ito iincrease ithe ieffectiveness iof ithe ilearning iprocess. iRecognizing iand ireacting ito iindividual ilearning istyles imay iimprove istudents’ iability ito iaccept iand iretrain icontent iand ihelp ito iavoid ipossible ilearning idifficulties iby iselecting ithe iappropriate iteaching imethod. iThis imay ialso iaid iin iselecting ithe imost isuitable imaterials iand iactivities ifor ithe iindividual istudents.

Acknowledgement

We iwould ilike ito ithank ithe iteam iof iProject iMatching iGrant iK135 iwho iparticipated iin ithis istudy iconsisting iof iexperts ifrom itwo iuniversities, iTun iHussein iOnn iUniversity, inamely iMaizam iAlias, iTee iTze iKiong, iLee iMing iFoong iand iFaizal iAmin iNur iYunus iand iUniversitas iNegeri iPaandg, inamely iGanefri, iNizwardi iJalinus, iSyahril, iSukardi, i iRisfendra iand iRahmat iAzis iNabawi ifor itheir icontribution. iFinally, iwe iwould ilike ito ithank ithe iTun iHussein iOnn iUniversity iof iMalaysia ifor ithe ifinancial isupport iunder iUTHM iGrant iVot iU940.

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