Jou nal o Technology and Science Educa ion
JOTSE, 2022 – 12(1): 83-95 – Online ISSN: 2013-6374 – P in ISSN: 2014-5349
h ps://doi.o g/10.3926/jo se.1422
ANALYZING FACTORS OF GUI SIMULATION AS LEARNING MEDIA
TOWARD STUDENTS’ LEARNING OUTCOMES
I Gus i Pu u As o Budi jahjan o
Uni e si as Nege i Su abaya (Indonesia)
[email p o ec ed]
Recei ed May 2021
Accep ed Sep embe 2021
Abs ac
The use o simula ion ools has been widely used o lea n some hing. Simula ion ools ha e he ad an age
o imi a ing a p ocess simila o he ac ual si ua ion. Bu he e a e only a ew esea ches ha examine he
s uden s' engagemen in using simula ion ools in he lea ning p ocess so ha i a ec s he s uden
lea ning ou comes. This esea ch aims o analyze he ac o s o G aphical Use In e ace (GUI) simula ion
as lea ning media o lea ning signal coding echniques. The Pa ial Leas Squa e – S uc u al Equa ion
Modeling (PLS-SEM) me hod was used o in es iga e he impac and he ela ionship o ac o s o GUI
simula ion such as Easiness o Use (EU), Media A ac i eness (MA), and Lea ning Con en (LC) owa d
Lea ning Ou come (LO). The esul s showed ha he lea ning con en ac o ga e a la ge and signi ican
con ibu ion owa d lea ning ou comes, while easiness o use and media a ac i eness made a small
con ibu ion o he lea ning ou come.
Keywo ds –
Simula ion, Lea ning media, PLS-SEM, Lea ning ou come.
To ci e his a icle:
Budi jahjan o, I.G.P.A. (2022). Analyzing c o s o GUI simula ion as lea ning media owa d s uden s’
lea ning ou comes. Jou nal o Technology and Science Educa ion, 12(1), 83-95. h ps://doi.o g/10.3926/jo se.1317
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1. In oduc ion
U ilizing simula ion has been used in he ields o enginee ing. Simula ion has a ole o be able o illus a e
he wo k p ocess o a sys em. The simula ion p ocedu e is o p o ide inpu o a simula ed sys em hen
obse e he simula ion p ocess and measu e he simula ion ou pu as a esponse o he inpu ha has been
gi en. Simula ion has he capabili y o imi a ing si ua ions and condi ions acco ding o eal ci cums ances.
The ad an age o imi a ing condi ions in eal ci cums ances, he use o he simula ion can be engaged in
p oblems ha a e simila o he ac ual si ua ion.
Compa ing wi h eal si ua ions, simula ion has ewe isks han implemen ing he p oblem di ec ly in he
eal condi ion. To sol e he p oblem in eal condi ions, i needs a high-cos condi ion, ex ensi e e o ,
and long- ime implemen a ion. The e o e, simula ion is needed as a pe o mance e alua ion echnique.
Simula ion has he capabili y o i s speed, cos -e ec i eness, ease o implemen a ion o use, lexibili y,
epea abili y, and scalabili y (Sha i & Sadeghi-Nia aki, 2017). The easiness o use, simplici y, and
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excellence o simula ion is also e ealed by (Jakkhupan, A ch-in & Li, 2011) which s a ed ha companies
can use simula ion wi h i s easiness o use o unde s and he p ac ical implica ions o he echnology,
meanwhile, esea ch academics use a simula ion o lea n and explain he new ans igu e p ocess wi hou
aking a long- ime consump ion and a high-cos consump ion. Th ough he lea ning con en o
simula ion, he simula ion use s can p ac ice making he igh decision om se e al al e na i e solu ions
a ailable om he simula ion scena io. E e y decision aken will ha e a ce ain impac on he sys em ha
has been simula ed (Budi jahjan o & Miyauchi, 2011). In line wi h ha Adams and Singh (2018) indica ed
ha some simula ion ools wi h hei lea ning con en could be applied o e alua e decisions o beha io s
o be e supply in o ma ion o decision-make s owa d he po en ial impac s o hei decisions.
Simula ions ha e been used in s udying and sol ing p oblems i ually be o e acing he p oblem in eal
si ua ions. Wolke s o e , Schweigho e , Weglei e , S a o ci, Schwaige and Lackne (2016) used simula ion
wi h i s lea ning con en o es ima e he low ope a ional cos s o sma g id communica ions in he
low- ol age g id. In his g id sys em, he e a e some unp edic able phenomena o powe -line channels
such as equency selec i i y, na owband noise sou ces, obse able impulsi e, and ime- a iance.
The e o e, simula ion u iliza ion can help hese p oblems. He ea e , o lea n supply chain i ms,
Jakkhupan e al. (2011) used simula ions wi h i s lea ning con en o s udy and illus a e he la es
emodeled p ocess and o e alua e he impac o echnology in p ac ical implica ions.
Simula ion as one ype o lea ning media has an impo an ole in he eaching and lea ning p ocess in a
class wi h i s a ac i eness. This is because simula ion can help s uden s o be e unde s and he ma e ial
p o ided. B a o, Redondo, O ega and Ve dejo (2006) s a ed ha he use o simula ion wi h i s
a ac i eness can be used in class o eaching pu poses because simula ion has he ad an age o being
able o suppo collabo a i e lea ning p ocesses. Simula ion can be used o he eaching and lea ning
p ocess by adap ing simula ion in o an educa ional simula ion ool by in using lea ning ma e ials and
p oblems in o he simula ion. As esea ch conduc ed by Ga cía-Díaz, Salcedo-Sanz, Po illa-Figue as and
Núñez-Clemen e (2009) s a ed ha a simula ion ool o educa ion can be embedded lea ning con en on
how o lea n cha ac e is ics o GSM echnology, such as he simula ion o calls, hando s, and a ic. So
he s uden s can simula e he cha ac e is ics o ne wo k co e age o di e en scena ios simula ing a
small, medium, and la ge ci y. Zamo a-Cá denas, Pizano-Ma ínez, Lozano-Ga cía, Gu ié ez-Ma ínez
and Cisne os-Magaña (2018), Ža ko ić and S ojko ić (2015), and Al in as (2011) used a p ac ical
educa ional ool o lea n s a e es ima ion o elec ic powe sys ems. Shanka (2016) s a ed he media
a ac i eness o simula ions in he lea ning p ocess o wi eless ading channels can enable s uden
pa icipa ion in class. Meanwhile, o s udy Techniques o Chaos-Based Digi al Modula ion, Oğ aş and
Tü k (2013) used so wa e simula ion in Modelling and Simula ion.
Based on ha desc ip ion abo e, so he ob ained esea ch gap is as ollows: only a ew ypes o esea ch
in es iga e he s uden s' engagemen in using compu e simula ion in he lea ning p ocess so ha i a ec s
he s uden lea ning ou comes. Mos o he esea ches ela ed o compu e simula ion s ill discuss he
use ulness o he compu e simula ion o sol e he p oblem a hand and s ill has no discussed he
suppo ing ac o s ha exis in he usage o compu e simula ion ha is pe cei ed by he s uden s in he
lea ning p ocess. This esea ch gap becomes he basis o conduc his esea ch.
The objec i e o he esea ch is o analyze he ac o s o G aphical Use In e ace (GUI) simula ion ha
applied as lea ning media in lea ning ma e ial o signal coding echniques. The ac o s o GUI simula ion
such as Easiness o Use (EU), Media A ac i eness (MA), and Lea ning Con en (LC) and, Lea ning
Ou come (LO). The de ini ion o each ac o o he GUI simula ion is as ollows: Easiness o Use (EU)
is he easiness o ope a e GUI simula ion, Media A ac i eness (MA) is he display a ac i eness o GUI
simula ion which includes he a ailabili y o in o ma ion, he p esen a ion o images and ables, Lea ning
Con en (LC) is he a ailabili y and he comple eness o he lea ning ma e ials s udied and he
in e ac i eness o he GUI simula ion and, Lea ning Ou come (LO) is he esul o s uden lea ning a e
using GUI simula ion. GUI ac s as an in e ace be ween he use and he compu e o ease he use in
ope a ing a compu e applica ion. The GUI simula ion can isualize he p ocess o signal coding
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echniques. By using GUI simula ion, he s uden s can obse e and unde s and he p ocess o signal
coding echniques in he lea ning p ocess. S uden s can in e ac wi h he GUI simula ion by p o iding
inpu in he o m o analog o digi al signals and hen obse e he esponse in he o m o ou pu signals
coming ou o he esul s o he simula ion p ocess.
Fu he mo e, o analyze he model, his esea ch used The Pa ial Leas Squa e – S uc u al Equa ion
Modeling (PLS-SEM) o es he alida ion and eliabili y o he ou e model and o measu e and e alua e
he impac o each la en a iable o he inne model. The Pa ial Leas Squa e – S uc u al Equa ion
Modeling (PLS-SEM) is a me hod o s uc u al equa ion modeling ha p esen s es ima ing complex
cause-e ec ela ionship models o la en a iables. The esea ch hypo heses include: The ac o o
easiness o use has a posi i e e ec on lea ning ou come; The ac o o media a ac i eness has a posi i e
e ec on lea ning ou come; The ac o o lea ning con en has a posi i e e ec on lea ning ou come.
2. Li e a u e Re iew
2.1. Modeling
Modeling a sys em is needed o desc ibe he condi ion o s a e o he p oblem obse ed by he use . The
use o he model can p o ide many bene i s o use s be o e implemen ing he sys em in he eal s a e.
Modeling makes i easy o esea che s o make models a o dable because hey p o ide cons ain s and
assump ions made (Kong, Shi, Yu, Liu & Xia, 2019). By using modeling, he eliabili y o a
communica ion ne wo k can be known and measu ed. Because modeling p o ides con enience in
de e mining wha pa ame e s can be used in he calcula ion o eliabili y ha a ec s he communica ion
ne wo k (Ahmad, Hasan, Pe ez & Qadi , 2017; Cogoni, Busone a, Anedda & Zane i, 2017). In line wi h
ha modeling can help o imp o e he eliabili y o a compu e communica ion ne wo k in o de mo e
eliable. The model in he mani es a ion o a simula ed mobile agen ne wo k can make i easie o help in
de ec ing ne wo k p oblems and ix hem so ha ne wo k eliabili y is inc eased (Daoud & Mahmoud,
2008).
Villalba and Zambonelli (2011) s a ed ha modeling he compu a ional elemen s o agen s in he
pe asi e se ice amewo k and hei in e ac ions wi h ecosys ems is o p o ide pa ame e s o hei
cha ac e by ge ing inspi a ion om ecological sys ems. Meanwhile, acco ding o Dez ouli, Radi, Razak,
Hwee-Pink and Baka (2015) ha modeling o design and implemen low-powe wi eless communica ion
is needed. Because h ough modeling wi h he use o pa ame e s in building a low-powe wi eless
communica ion, he essen ials o accu a e modeling and e alua ion o low-powe wi eless
communica ions can be es ablished. Acco ding o Ibáñez, Ga cía-Rueda, Ma o o and Delgado-Kloos
(2013), a model can use in he lea ning p ocess. By egula ing in e ac ions, he model is used o a ange
collabo a i e lea ning ac i i ies and also used in he sca olding o lea ning wo k lows. A simula ion ool
was de eloped o he model o suppo and es ablish collabo a i e lea ning modules.
2.2. G aphical Use In e ace (GUI) Simula ion
Simula ion can be mani es ed in compu e applica ions known as a compu e simula ions. The
de elopmen o compu e simula ions has been g owing apidly ollowing he needs o i s use s.
The e o e, he ypes o compu e simula ions o simula o s being de eloped a e also inc easing. Each
simula ion is de eloped acco ding o he p oblems aced by i s use s. Bho , Angappan and Si alingam
(2016) used OpenDSS o powe sys ems and OMNET o ++ communica ion ne wo ks simula ion.
Naga juna, Lakshmi and Neh u (2019) used LabVIEW so wa e o build a sys em model o s udy
equency di ision mul iplexing. Abuelmaa i, Abuelma’a i, Thayne and Beaumon , (2010) used Simulink
o s udy complex modula ion schemes such as QPSK. Meanwhile, A allone & Di S asi (2016) used
WiMesh, a so wa e ool ha is used o lea n mul i- adio wi eless mesh ne wo ks. MATLAB is ano he
compu e p og amming ha is o en used o simula ion. Ál a ez-Gál ez (2017) applied i o s udy
high-speed backsca e based on an HS Mille modula ed subca ie and ‐Zunge u, Ang and Seng (2012)
employed i o lea n ou ing modeling applica ion simula ion en i onmen .
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Simula ion in he ield o enginee ing has been applied o sol ing a p oblem ha a ises in he lea ning
p ocess. The lea ning p ocess by u ilizing G aphical Use In e ace (GUI) simula ions can enhance s uden
lea ning o educa ional pu poses. Simula ion can con ibu e o imp o ing s uden s' unde s anding o he
phenomena ha occu in a sys em (Oğ aş & Tü k, 2013; Budi jahjan o, Nu laela, Ekoha iadi & Riduwan,
2017). Fo educa ional pu poses, simula ion has he capabili y o an easy- o-use and use - iendly isual
ins uc ion ool. Zamo a-Cá denas e al. (2018) used a p ac ical educa ional ool o s a e es ima ion o
elec ic powe sys ems. This simula ion ool helps s uden s o enhance lea ning, unde s anding and sa ing
he ime o implemen a ion and de elopmen o labo a o y expe imen s. Acco ding o Del Ba io,
Manzano, Ma o o, Villa ín, Pagán, Zapa e e al. (2019) ha he use o simula ions o s udy
communica ion heo y can help imp o e s uden unde s anding compa ed o using a adi ional
equa ion-based en i onmen . This is also suppo ed by Al in as (2011) ela ed o he use o GUI
MATLAB, which is used o eaching and lea ning powe elec onics cou ses, can beha e as a on -end
in e ace. This GUI simula ion can be used as use ul lea ning media o as a i ual labo a o y. A e he
lea ning ha uses GUI simula ion is done, he s uden s gi e a posi i e esponse o powe elec onics
cou ses. This designa es ha he u iliza ion o GUI simula ion is e y help ul o lea ning he subjec o
powe elec onics.
3. Me hod
This esea ch used MATLAB p og amming o es ablishing G aphical Use In e ace (GUI) simula ion o
lea n he signal coding echnique. MATLAB was chosen because i has a de elopmen acili y in he o m
o a GUI so ha i can acili a e he planning and making o he simula ion ool as lea ning media,
especially in he o m o simula ion in e ac ions. MATLAB also has ad an ages in e ms o ma hema ics.
I is e y sui able o use in he de elopmen o lea ning media in he o m o simula ion o signal
coding echnique ma e ial in he da a communica ion cou se in he depa men o elec ical enginee ing,
The S a e Uni e si y o Su abaya-Indonesia. Figu e 1 shows he display esul s o using he MATLAB
GUI o simula e he PCM signal.
Figu e 1. PCM signal simula ion
3.1. P ocedu e
The p ocedu e o his esea ch consis ed o wo s ages: he modeling s age and he analysis s age. A he
modeling s age, cons uc s o la en a iables a e de e mined o e alua e he model o u ilizing signal
coding echnique simula ion. The cons uc consis s o 4 cons uc s, namely: Easiness o Use (EU),
Media A ac i eness (MA), Lea ning Con en (LC), and Lea ning Ou come (LO). The modeling s age
models he ela ionship be ween he cons uc s o he EU, he MA, and he LC o he LO in he use o
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signal coding echnique simula ions. The model p edic ion o he signal coding echnique simula ion is
shown in Figu e 2.
The EU, MA, LC, and LO a e cons uc s ha canno ye be measu ed because hey a e la en . The e o e,
hey need se e al indica o s o desc ibe hese la en a iables. Fu he mo e, o he indica o s ha ha e
been made can be measu ed, i needs an ins umen in he o m o a ques ione ha uses a Like scale in
i s measu emen . Table 1 shows he la en a iables wi h hei cons i uen indica o s.
The analyzing s age consis s o wo sub-s eps, which a e he measu emen model and he e alua ion o
s uc u al models. The measu emen model e alua es indica o s, la en a iables, and ela ionships
be ween indica o s and la en a iables.
Figu e 2. Modeling o u ilizing signal coding echnique based on GUI Simula ion
Cons uc /La en Va iable Indica o
Easiness o Use (EU) The ins uc ions a e clea (EU1)
Language is easy o unde s and (EU2)
Ease o ope a ion (EU3)
Ease o en e ing da a inpu s and displaying esul s (EU4)
Media A ac i eness (MA) The in o ma ion p esen ed is eadable (MA1)
The o de o images and ex a e in e ela ed (MA2)
The images a e clea (MA3)
The desc ip ions o pic u es and ables a e clea (MA4)
The sc ip is easy o unde s and (MA5)
Fon size is p opo ional and legible (MA6)
The eaching ma e ial ha e conside ed economic aspec s (MA7)
Lea ning Con en (LC) The en e ed da a ma ches wi h he coding esul s (LC1)
The esul s o he encoding signal a e a ma ch and clea (LC2)
Suppo he implemen a ion o eaching and lea ning ac i i ies (LC3)
Facili a e s uden s in lea ning signal coding echniques (LC4)
Sui abili y o he media wi h lea ning ma e ial (LC5)
The u hness le el o he ma e ial concep in eaching ma e ial (LC6)
The lea ning ma e ial con en s ma ch he cu iculum (LC7)
In o ma ion in eaching ma e ials is su iced (LC8)
The assignmen s om ma e ial lea ning encou age s uden ac i i y (LC9)
Wo kshee s on lea ning ma e ials ma ch lea ning media (LC 10)
Lea ning Ou come (LO) Lea ning Ou come Resul
Table 1. La en a iable and i s indica o
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The e alua ion o he measu emen model consis s o con e gen alidi y measu emen and indica o
eliabili y measu emen . The con e gen alidi y pa ame e is a loading ac o wi h a alid condi ion i i is
g ea e han 0.7 and he A e age Va iance Ex ac ed (AVE) pa ame e wi h a alid condi ion i i is g ea e
han 0.5. Nex , he indica o eliabili y pa ame e is C onbach’s Alpha wi h a eliable condi ion i i is
g ea e han 0.7. In he e alua ion s ep o he s uc u al model e alua e la en a iables and ela ionships
be ween la en a iables. The e alua ion measu emen calcula es he coe icien o de e mina ion (R2),
pa h coe icien (β), and hypo hesis analysis ( - es ).
3.2. Pa icipan s
The esea ch pa icipan s a e 30 unde g adua e s uden s o elec ical enginee ing a The S a e Uni e si y
o Su abaya-Indonesia. All esea ch pa icipan s ollowed he cou se o da a communica ion.
3.3. Ins umen s
The esea ch da a we e collec ed h ough ques ionnai es o ge s uden esponses. Ques ionnai es we e
c ea ed acco ding o he indica o s o each GUI simula ion la en a iable. The ques ionnai es we e gi en
o s uden s a e hey ha e inished lea ning all he ma e ial on he signal coding echnique using a GUI
simula ion. Meanwhile, he s uden s' lea ning ou comes we e ob ained om he s uden s' exam esul s
ela ed o he signal coding echnique ma e ial ha s uden s ha e lea ned using GUI simula ion. Some
ins umen s a e de eloped o measu e he la en a iables. The de eloped ins umen s a e based on
indica o s ha desc ibe each o he la en a iables. In he model, all la en a iable indica o s a e
measu ed using a 5-poin Like scale. Because his esea ch de elops a p edic i e model, hus his
esea ch used he Pa ial Leas Squa e – S uc u al Equa ion Modeling (PLS-SEM) me hod o analyze he
models. Acco ding o Komiak and Benbasa (2006), one o he ad an ages o he PLS-SEM me hod is
capable o analyzing p edic i e models e en wi h small da a. The o he ad an age o he PLS-SEM is
capable o analyzing all o he pa hs in one analysis (Hai , Hul , Ringle & Sa s ed , 2014).
The e o e, he pa h analysis o PLS-SEM was used o analyze he ela ionship be ween independen
a iables (EU, MA, and LC) owa d dependen a iables (LO). Mo eo e , PLS-SEM can wo k e icien ly
wi h complex models and small sample sizes (Rezaei & Ghodsi, 2014). As men ioned be o e ha ou
esea ch only used 30 pa icipan s (small sample sizes).
Figu e 3. Resul o modeling o u ilizing signal coding echnique based on GUI simula ion
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4. Resul
4.1. Simula ion Resul s
To analyze esea ch da a, s a is ical so wa e XLSTAT was used. XLSTAT was used o de e mine he
ela ionship be ween in e la en a iables and he ela ionship be ween la en a iables and hei
indica o s. Figu e 3 indica es he unning esul s o XLSTAT om he modeling o he signal coding
echnique wi h hei la en a iables. In he measu emen model which was he alidi y and eliabili y es
o he model. The esul s o XLSTAT showed ha he loading ac o alues o all indica o s in he
Easiness o Use (EU), Media A ac i eness (MA), and Lea ning Con en (LC) cons uc we e g ea e
han 0.70. This showed ha all o he loading ac o s ha e ul illed he condi ion o alidi y. Table 2
shows he loading ac o alue o he indica o in each cons uc . Meanwhile, he AVE alues o all
cons uc s we e g ea e han 0.50 as seen in Table 3. I shows ha all o he AVE alues ha e ul illed he
condi ion o alidi y.
The simula ion esul s show as seen in Table 3 ha he alues o C onbach's Alpha a e g ea e han 0.7.
So, he alues o C onbach's Alpha ha e ul illed he eliabili y condi ion. As all condi ions o alidi y and
eliabili y ha e been ul illed, so in his s age, he model o u ilizing signal coding echnique based on GUI
simula ion is alid and eliable.
Fac o s Easiness o Use Media A ac i eness Lea ning Con en Lea ning Ou come
EU1 0.9277 0.9268 0.8860 0.8693
EU2 0.9277 0.9268 0.8860 0.8693
EU3 0.9555 0.8950 0.9082 0.8953
EO4 0.9093 0.8547 0.8537 0.8521
MA1 0.8410 0.9037 0.8636 0.8476
MA2 0.9153 0.8932 0.8551 0.8378
MA3 0.8960 0.8943 0.8452 0.8387
MA4 0.9212 0.9047 0.8592 0.8485
MA5 0.7772 0.8665 0.8314 0.8127
MA6 0.8600 0.8732 0.8430 0.8189
MA7 0.9277 0.9268 0.8860 0.8693
LC1 0.7979 0.7909 0.7267 0.7111
LC2 0.9392 0.8819 0.8928 0.8736
LC3 0.9502 0.8995 0.9234 0.9035
LC4 0.9494 0.9267 0.9470 0.9267
LC5 0.9534 0.9042 0.9310 0.9110
LC6 0.8482 0.8444 0.8093 0.7919
LC7 0.8841 0.8736 0.8373 0.8193
LC8 0.8771 0.8890 0.8245 0.8068
LC9 0.8255 0.8920 0.9041 0.8847
LC10 0.9395 0.8840 0.8992 0.8799
LO 0.9370 0.9379 0.9785 1.0000
Table 2. Loading Fac o o Signal Coding Technique simula ion model
Cons uc AVE C onbach’s Alpha
Easiness o Use 0.8653 0.9502
Media A ac i eness 0.8007 0.9697
Lea ning Con en 0.7603 0.9812
Table 3. The AVE & C onbach’s Alpha o Signal Coding Technique simula ion model
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The s ep o he e alua ion o s uc u al models was o e alua e he pa h coe icien , he coe icien o
de e mina ion, and hypo hesis analysis. Table 4 shows he simula ion esul s o he de eloped model
which consis s o he pa h coe icien , s anda d e o , - alue o each la en a iable. F om simula ion
esul o pa h coe icien can be o mula ed he equa ion model as ollows:
LO = 0.02544 * EU + 0.08948 * MA + 0.86956 * LC
The equa ion model shows ha all he pa h coe icien s alue a e posi i e, bu only he pa h coe icien
alue o LC is close o 1 so ha i can be said o make a signi ican con ibu ion o LO compa ed o EU
and MA whe e he alues o pa h coe icien a e oo small.
Table 5 indica es he coe icien o de e mina ion (R2) o he Model. I is known ha Lea ning Ou come
is signi ican ly de e mined by he h ee exogenous a iables (EU, MA & LC) wi h he alue o R2 a e
0.9586. This means ha he h ee exogenous a iables capable o explain 95% o he a iance in lea ning
ou comes.
Fu he mo e, he esul s o his simula ion we e used o answe he esea ch hypo heses. F om Table 6, i
can be shown ha H1 was no suppo ed. Because he simula ion esul s showed he pa h coe icien
alue o he EU only 0.0254 ha indica ed i has a low con ibu ion o he LO and also he - alue was
0.1580 lowe han he c i ical - alue a 1.65 o a signi icance le el o 10%. So i is wi h H2 was no
suppo ed. Since he simula ion esul s showed he pa h coe icien alue o he MA only 0.0895 ha
indica ed i has a low con ibu ion owa d he LO and also he - alue was 0.5654 lowe han he c i ical
- alue a 1.65 o a signi icance le el o 10%. F om he simula ion, only H3 was suppo ed. Because he
simula ion esul s showed he pa h coe icien alue o he LC a 0.8696 ha indica ed i has a high
con ibu ion agains he LO and he - alue was 6.2654 highe han he c i ical - alue a 2.58 o a
signi icance le el o 1%. F om he h ee hypo heses, only H3 is suppo ed.
La en a iable Value S anda d e o P > | | ²
Easiness o Use 0.0254 0.1610 0.1580 0.8757 0.0010
Media A ac i eness 0.0895 0.1583 0.5654 0.5767 0.0123
Lea ning Con en 0.8696 0.1388 6.2654 0.0000 1.5098
Table 4. Pa h coe icien s o la en a iables
R² F P > F R² S anda d e o C i ical a io (CR)
0.9586 200.8561 0.0000 0.9618 0.0179 53.4395
Table 5. Coe icien De e mina ion (R2) o Model
Hypo hesis Hypo hesized Pa h β alues - alue Resul
H1 Easiness o Use → Lea ning Ou come 0.0254 0.1580 No Suppo ed
H2 Media A ac i eness → Lea ning Ou come 0.0895 0.5654 No Suppo ed
H3 Lea ning Con en → Lea ning Ou come 0.8696 6.2654* Suppo ed
Table 6. Hypo hesized Pa h
4.2. Discussion
This esea ch used da a wi h 30 s uden s as pa icipan s. Howe e , acco ding o Rezaei and Ghodsi (2014)
and Hai e al. (2014) ha he Pa ial Leas Squa e – S uc u al Equa ion Modeling (PLS-SEM) me hod
p oceeds e icien ly wi h complica ed models and small sample sizes. The e o e, his esea ch da a s ill can
be analyzed and also con ibu e o i s esea ch esul s ollowing he p inciples o he PLS-SEM me hod.
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Jou nal o Technology and Science Educa ion – h ps://doi.o g/10.3926/jo se.1317
The modeling o u ilizing signal coding echniques based on G aphical Use In e ace (GUI) simula ion
has ul illed he equi emen o alidi y and eliabili y. As men ion be o e ha , all loading ac o alues o
all la en a iables ha e achie ed he alidi y equi emen s. This is ollowing he esea ch esul o Hai e
al. (2014) s a ed ha he loading ac o is decla ed alid i i has a alue > 0.7. In Table 2 i can be seen
ha he lowes alue o he loading ac o is LC1 (The en e ed da a ma ches wi h he coding esul s) o
0.7267 and he highes loading ac o o EU3 (Ease o ope a ion) which is 0.9555. So, i is wi h he alues
o AVE o he Easiness o Use (EU), Media A ac i eness (MA), and Lea ning Con en (LC) ha e
ul illed he alidi y equi emen . As s a ed by Fo nell and La cke (1981) he model is alid i he AVE
alue is g ea e han 0.50. The e o e, i shows ha all indica o s can wo k on he measu emen model, so
he alidi y o he ou e model can be said o be alid. C onbach’s Alpha is one o he pa ame e s o
measu e he eliabili y o a model. Acco ding o Hai e al. (2014) s a ed ha he model is conside ed
eliable i he alue o C onbach’s Alpha is > 0.70. Meanwhile, he eliabili y es esul s in his s udy
indica e ha he C onbach's Alpha alue on all la en a iables is g ea e han 0.70 as shown in Table 3.
The e o e, he eliabili y o his model is eliable.
The a iables ha a e used o analyze he s uc u al model a e pa h coe icien (β alues) and coe icien
o de e mina ion (R2). The pa h coe icien o he LC shows a posi i e alue wi h he highes β alues o
0.8696 as shown in Figu e 3. This alue app oaches he alue o 1 which means ha he ela ionship
be ween he LC o he LO plays a majo ole. While he β alues o he EU and he MA a iables a e
0.0254 and 0.08950 espec i ely. These alues a e oo small o gi e a ela ionship owa d he LO.
Acco ding o Wein u (1995) s a ed ha he bigge o alue R2, he mo e he p edic i e powe o he
model can be de eloped. F om Table 7 can be known ha he bigges alue o R2 is he LC a 88.7587,
hen he R2 alue o he MA a 8.7546 and he EU a 2.4866. Based on he alue o R2, i indica es ha
he a iance amoun o LC con ibu es owa d LO a 88.7587 % in his model. The MA a iable
con ibu es a 8.7546 % and he EU a iable con ibu es a 2.4866 owa d he LO a iable. Figu e 4 shows
he impac and con ibu ion o he a iables o he Lea ning Ou come. Hai e al. (2014) s a ed i he R2
alue o endogenous la en a iables is > 0.75, so i is ca ego ized as subs an ial. The e o e, only he LC in
his s udy p o ides he p edic i e powe o he model ha is de eloped in he subs an ial ca ego y
meanwhile he MA and he EU only p o ide he weak ca ego y.
Figu e 4. Impac and con ibu ion o he a iables o Lea ning Ou come
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