In e ne Resea ch
Design Quali y in Building Beha io al In en ion h ough
A ec i e and Cogni i e In ol emen o E-lea ning on
Sma phones
Jou nal:
In e ne Resea ch
Manusc ip ID
INTR-05-2019-0217.R2
Manusc ip Type:
Resea ch Pape
Keywo ds:
Compu e based lea ning, Design Quali y, Cogni i e In ol emen ,
A ec i e In ol emen , In e ac ion, Con inued in en ion o use
h p://mc.manusc ip cen al.com/in
In e ne Resea ch
In e ne Resea ch
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Design Quali y in Building Beha io al In en ion h ough A ec i e and Cogni i e
In ol emen o E-lea ning on Sma phones
Abs ac
Pu pose
This s udy examines he e ec o design quali y (i.e., appea ance, na iga ion, in o ma ion, and
in e ac i i y) on cogni i e and a ec i e in ol emen leading o con inued in en ion o use he
online lea ning applica ion.
Design/Me hodology/App oach
We assume ha design quali y po en ially con ibu es o enhance he indi idual's in ol emen and
exci emen . An expe imen al p o o ype is de eloped o collec ing da a used o e i y and alida e
he p oposed esea ch model and hypo heses. A pa ial-leas -squa es app oach is used o analyze
he da a collec ed om he pa icipan s (n= 662).
Findings
Communica ion, aes he ic, and in o ma ion quali y e ealed o be s ong de e minan s o bo h
cogni i e and a ec i e in ol emen . Howe e , on quali y and use con ol posi i ely in luence
cogni i e in ol emen , while na iga ion quali y and esponsi eness we e obse ed as signi ican
indica o s o a ec i e in ol emen . Las ly, cogni i e and a ec i e in ol emen equally con ibu e
o de e mining he con inued in en ion o use.
O iginali y/Value
P e alen esea ch in he online con ex is ocused p ima ily on cogni i e and u iliza ion beha io .
Howe e , hese wo ks o e look he implica ion o design quali y on cogni i e and a ec i e
in ol emen .
Implica ions
This s udy will d aw he a en ion o designe s and p ac i ione s owa ds he pe cep ion o use s
o p o iding app op ia e and engaging lea ning esou ces.
1. In oduc ion
Technologies enhance lea ning expe iences by p o iding easy access o esou ces (Dominici and
Palumbo, 2013). Se e al academic ins i u ions ha e made subs an ial in es men s in de eloping
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digi al esou ces o deli e use ul lea ning con en (Chin e al., 2018; Wang e al., 2018). S ill, i
is a challenge o c ea e an in e ac i e en i onmen ha could engage indi iduals as o main ain
hei in ol emen and in e es (Guo e al., 2015). On he o he hand, design quali y encou ages
indi iduals o change hei le el o in ol emen (Cy e al., 2018) and plays a c ucial ole in
in o ma ion deli e ance by es ablishing e ec i e communica ion be ween he sys em and he
use s. I in luences he indi idual’s pe cep ions and inal beha io (Ou and Sia, 2010; Floh and
Madlbe ge , 2013). Thus, a good quali y websi e comp ises all he cues used o design i and a ec
he in e nal s a e o use s (Hsu e al., 2012). I in ol es he combina ion o app op ia e in o ma ion
aspec s wi h a p ecise o ganiza ion o con en s. Besides o ganiza ion, isual appea ance also
con ibu es by ini ia ing posi i e a i udes owa ds he sys em in e ace, which, in he end, leads o
heigh ened in ol emen (G eussing and Boomgaa den, 2019). Thus, imp o emen s in design
quali y os e he use ’s in ol emen , along wi h posi i e expe iences (Guo e al., 2015; Lin, 2007).
Such expe iences c ea e alue o use s; in consequence, hey spend mo e ime on a sys em, which
ul ima ely leads o a posi i e a i ude (Kim e al., 2007; Ou and Sia, 2010; Liu e al., 2016) and
in en ion o use (Ta u e e al., 2017). The e o e, consis en e o s a e equi ed o enhance he
in e ac i i y, engagemen , and usabili y o hese applica ions h ough design and appea ance
quali y (Abachi and Muhammad, 2013; Ta u e e al., 2017; Chin e al., 2018). Likewise, Hasan
(2016) a gues ha he websi es ha ing ele an in o ma ion, isually appealing and ha a e also
easy o use o na iga e seem o heigh en he indi idual’s in ol emen wi h he si e and lessen he
eelings o i i a ion. On he o he hand, poo usabili y, imp ecise design and in e ac ion discou age
use s (Hoehle e al., 2016). Besides, poo usabili y design migh cause ange and diso ien a ion in
he use s, as well as he eeling o losing con ol o e hei ac ions, hus he u ge o lea e he si e
(Faisal e al., 2018; Hasan, 2016).
I is essen ial o e ain use s and o imp o e hei le el o in ol emen ia subs an ial in e ac ion
and engaging-design a i ac s (Jiang e al., 2010; Ta u e e al., 2017). In ol emen is conside ed
as a i al concep o in o ma ion and communica ion esea ch (Pe se, 1990; Celuch and Slama,
1998; Kang e al., 2015; Reycha and Wu, 2015; Cy e al., 2018) and is adop ed in echnological
s udies o obse e posi i e a i ude, u iliza ion, and in en ion (Jiang e al., 2010; Kang e al., 2015;
Reycha and Wu, 2015; Cy e al., 2018). S ill, only ew s udies ocus on his mul idimensional
cons uc due o he di icul y o concep ualizing i (DeF anco, 2016). Mo eo e , we ound ha
p io esea ch p ima ily ocused on ully unc ional desk op Web b owse s usage o de e mine he
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design implica ions and hei impac on in ol emen (Cy e al., 2018); he e is a need o
unde s and he use ’s expe ience and o al e hei usage beha io o sma phones as well. The
eason is ha sma phones ha e ela i ely small sc eens, iny inpu mechanisms, and di e se
design pa e ns as compa ed o he ull-sc een e sion o he websi e (Ribei o, 2012; Hoehle e al.,
2016). The e o e, hese de ices display he same con en in a educed space, and a e p one o
highe e o a e compa ed o lap ops (Lug ig and Toepoel, 2016). Besides he sc een size, ano he
signi ican di e ence be ween he web si es b owsed om desk op la ge sc eens compa ed o he
same si es explo ed in he ela i ely small mobile de ice sc eens is he way in which use s in e ac
wi h hem (Hoehle e al., 2016; Shin e al., 2016). Fo ins ance, websi es using desk op
en i onmen s ely on mouse-d i en in e ac ions, while sma phones ha e ouch in e aces, in
which he e is a mo e di ec manipula ion o he sc een elemen s. The human inge is a much
mo e imp ecise poin e han a mouse (Ribei o and Ca alhais, 2012; Hoehle e al., 2016). Thus, i
is c i ical o de e mine addi ional usabili y p oblems o Mobile applica ions (Shin e al., 2016;
Ta u e e al., 2017) These usabili y issues become impo an aspec s conside ing he ul illmen o
indi idual needs and encou aging mo e in ense engagemen in he u he usage o mobile
applica ions (Ta u e e al., 2017). Besides hese issues, ins an changes in consume usage beha io
also o ce new challenges on companies seeking o in luence beha io by making use o mobile
echnologies (Ta u e e al., 2017). Thus, a ca e ul design app oach is needed, conside ing he
sma phone cons ain s ha a e bound o lessen he quali y o in e ac ion (Tsiaousis and Giaglis,
2014) and le el o in ol emen (Sun and Xu, 2019). Likewise, Li le (2013) emphasized ha he
designe should p ojec he lea ning con en in a way ha can quickly be deli e ed ia small-sc een
de ices (e.g. Mobile phones).
The objec i e o he cu en s udy is o explo e he design backg ound ha a ouses he emo ions,
unde s anding, and indi ec ly in luences he con inued in en ion o use. I is c ucial because
sma phones can be a iable al e na i e o in o ma ion deli e ance and a e becoming mo e
popula due o i s high accessibili y and mobili y. Hence, his s udy makes wo essen ial
con ibu ions. Fi s , we examine he impac o design quali y (i.e., on and aes he ic quali y,
in o ma ion quali y, na iga ion quali y, and in e ac i i y) on in ol emen dimensions, including
cogni i e and a ec i e in ol emen , ul ima ely leading o con inued in en ion o use; since limi ed
esea ch has been conduc ed o assess he ole o design quali y o use in ol emen (Cy e al.,
2018). Second, his s udy p oposes he guidelines ela ed o use in e ace design elemen s o
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p omo e he indi idual’s in ol emen . These guidelines enable designe s o ha e a clea
unde s anding o essen ial design ea u es while de eloping lea ning esou ces o sma phones.
The es o he a icle is o ganized as ollows: Sec ion 2 p esen s ela ed s udies, including design,
in ol emen , esea ch model, and hypo heses. Sec ion 3 p o ides de ails abou he adop ed
me hodology, expe imen a ion, da a ga he ing, and s a is ical analysis. Sec ion 4 p esen s he
esul s, while sec ion 5 is ela ed o implica ions ollowed by he conclusion, limi a ions, and u u e
scope o he cu en esea ch.
2. Li e a u e and Resea ch Model
Va ious echnologies, such as sma phones, able s, compu e s, and in e ne access, ha e become
nea ly ubiqui ous in e e yday li e (Golonka e al., 2014). Especially he sma phones, ha ha e
become g adually sophis ica ed; hey ha e a highe po en ial o heigh en use engagemen and
le el o in ol emen , which, in u n, can esul in excessi e usage (Reycha and Wu, 2015; Ta u e
e al., 2017; Ba nes e al., 2019).
Howe e , due o eme gen equi emen s and di e si ica ion in se ices and applica ions, he
in e ac ion wi h sma phones has become highly complex (Choi and Lee, 2012), which may
nega i ely in luence he con inued in en ion o use. Use in en ion and posi i e a i ude a e
associa ed wi h design quali y and le el o in ol emen and engagemen (Cy e al., 2018; Kang
e al., 2015; Ta u e e al., 2017). Acco dingly, se e al esea che s also emphasized he need o
explo e he ole o in e ace design o in en ion o use (Joo e al., 2014; Kang e al., 2015; Nikou
and Economides, 2017; Ta u e e al., 2017). So, o e ain he use s and o con inuously use a sys em
can only be made possible wi h subs an ial in e ac ion and engaging-design a i ac s (Ta u e e al.,
2017).
Use in e ace e e s o he deg ee o which an indi idual eels ha a sys em o a websi e is well
designed, and i includes he app op ia e ea u es, i.e., na iga ion, in o ma ion, isual appea ance,
and unc ions o con ol he sys ems (Nikou and Economides, 2017). In simila s udies, Hasan
(2016) and Fo in and Dholakia (2005) a gue ha isually appealing, in o ma i e, and con enien
o na iga e in e aces seem o enhance websi e in ol emen . The design quali y o an in e ace
a ec s he indi idual’s pe cep ion o he websi e as i is he po al h ough which he ac i i ies a e
conduc ed. Cy and Head (2013) a gue ha he design quali y o a websi e s ongly in luences he
use ’s adop ion beha io . Pele e al., (2017) a gue ha design helps o a ouse he indi idual's
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emo ions, which leads o s imula ing in en ion, e isi websi es, and ecommenda ion. Ahn e al.,
(2007) obse ed he posi i e impac o websi e quali y on a i ude and beha io al in en ion.
Fu he mo e, au ho s a gue ha use ulness plays a c ucial ole in enhancing he a i ude and
beha io al in en ion o use a websi e. I-Fan e al., (2010) a gue ha he quali y o he design is
impe a i e o online applica ions because he use eels mo e com o able wi h a use - iendly
in e ace. Sal ado e al., (2015) obse ed he s ong impac o design on in en ion o use. The
au ho s a gue ha he use o d ag and d op in e ac ion and a good o ganiza ion con ibu e o
dec ease he cogni i e complexi y; consequen ly, indi iduals pe cei e he sys ems as mo e
e icien and eliable.
In se e al o he s udies (Nikou and Economides, 2017; Ta u e e al., 2017; Cy e al., 2018), he
esea che s obse ed he posi i e impac o web design and i s quali y on a i ude, beha io al
in en ion o use, engagemen , and se ice quali y. The au ho s emphasize he need o u he
esea ch because he e ec o hese elemen s may be di e en o sma phones. Sma phones ha e
a as po en ial o deli e e ec i e se ices (Keengwe and Bha ga a, 2013); s ill, i is c i ical o
de e mine addi ional usabili y p oblems o such de ices (Ta u e e al., 2017) o design an in e ace
ha is easy o use wi h a simple and s aigh o wa d design, and isually appealing, and ha
equi es ewe ac ions be o e a goal is achie ed. This is because use -con olled in o ma ion, isual
aspec s (e.g., shape, size, ex u e, colo , labels), s anda dized layou s and symme y help use s o
be mo e a en i e and in luence he use 's psychological p ocesses as well (Moshagen and
Thielsch, 2010; Tuch e al., 2010). The ole o layou and symme y o isual appea ance has
been iden i ied by he Ges al laws o pe cep ual o ganiza ion (Seckle e al., 2015). I e e s o
isual pe cep ion ha ocus on he o ganiza ion a he han on beau y, and i a emp s o explain
ha people pe cei e objec s as a whole ins ead o indi idual pa s (A nheim, 1974; Moshagen and
Thielsch, 2010). Acco ding o he heo y, s imulus elemen s a e pe cei ed and o ganized in o
g oups ha make sense o us. The g ouping p inciples such as closu e, p oximi y, and simila i y
a e used in design o a ange he in o ma ion and o c ea e he isual hie a chy (Hoehle e al.,
2016). In se e al s udies (Bhanda i e al., 2017; La ie and T ac insky, 2004; Moshagen and
Thielsch, 2010), he impac o isual design is discussed in e ms o unde s anding, sense-making,
in ol emen , and a ousal.
S ill, consensus p e ails among he esea che s on he design ac o s ha cons i u e he use
in e ace. Kim and Lee (2002) ca ego ized he design in o wo impo an aspec s: p ocess and
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in o ma ion a chi ec u e. The p ocess e e s o ansac ions, while he a chi ec u e e e s o web-
page elemen s. The a chi ec u e also ela es o he ules and a angemen o i ems in o a pleasing
design. Howe e , he ea u es a e ex ensi e; he e o e, p ecise classi ica ion o hese design
elemen s would be mo e help ul o unde s and and de e mine how hese aspec s in luence he
con inued in en ion o use. Acco dingly, Palme (2002) ca ego ized hese elemen s in o
in o ma ion, esponsi eness, in e ac i i y, na iga ion, and speed o assess websi e accep ance and
success. Cy and Head (2013) discussed websi e in e ace design in e ms o in o ma ion quali y,
na iga ion, and isual design o de e mine a posi i e a i ude. Faisal e al., (2017) conside ed
design cha ac e is ics including aes he ic, na iga ion, in o ma ion, and in e ac ion o imp o e he
quali y o a websi e. Hoehle e al., (2016) obse ed he di ec ela ionship be ween design
guidelines (i.e., g aphics, anima ion, colo , en y poin , inge ip-sized con ols, ex , ges al
s anda ds, o de , and ansi ion) and con inued in en ion o use.
In he p io esea ch (Ali 2016; É hie e al., 2008; Hsu e al., 2012; Ta u e e al., 2017), se e al
esea che s adop ed s imulus-o ganism- esponse (SOR) o explain he design implica ions. In
hese s udies, he design a ibu es and websi e quali y a e ega ded as s imuli. The SOR
amewo k p oposes ha s imuli on beha io a e media ed h ough an o ganism (Albe and
Russell, 1974). The heo y sugges s ha en i onmen al cue can impac an indi idual's in e nal
s a es (i.e., cogni i e and a ec i e eac ions), which in u n p oduce ei he a oidance o app oach
beha io s (Liu e al., 2016). In he online con ex , he s imulus e e s o he websi e quali y ha
a ec s he in e nal s a e o he use s (Ali 2016; Hsu e al., 2012; Liu e al., 2016) In se e al o he
s udies, he design ea u es –including na iga ion (É hie e al., 2008; Floh and Madlbe ge , 2013;
Rod íguez-To ico e al., 2019), pe cei ed isual appea ance (Bhanda i e al., 2017; É hie e al.,
2008; Koo and Ju, 2010; Liu e al., 2016; Liu e al., 2013; Peng e al., 2017; Rod íguez- o ico e
al., 2019; Shu-Hao e al., 2014), in o ma ion quali y (Ca lson e al., 2018; E oglu e al., 2001;
É hie e al., 2008; Floh and Madlbe ge , 2013; Hsu e al., 2012; Ta u e e al., 2017), and
in e ac i i y including use con ol, esponsi eness, and communica ion (Jiang e al., 2010; Hsu e
al., 2012; Ca lson e al., 2018; Rod íguez-To ico e al., 2019)– we e employed as s imuli o
en i onmen al cues o de e mine he indi idual’s pe cep ion (see Table 1), because hey play an
impo an ole in p omo ing posi i e a i ude and use in en ions (Hausman and Siekpe, 2009; Koo
and Ju, 2010). Howe e , majo i y o hese s udies we e conduc ed in he con ex o he websi e,
only ew among hem discussed he design conside a ion o mobile bu in di e en usage con ex s.
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Jiang e al., (2010) adop ed design in e ac i i y as en i onmen al s imuli o de e mine he in en ion
ia in ol emen , whe e in ol emen a ouses om a wide a ie y o s imuli: quali y o design
including na iga ion, con en , isual appea ance, in e ac i i y, download speed, iendliness,
mul imedia capabili y, and p esen a ion s yle (San osa e al., 2005). Thus, design quali y is an
essen ial aspec ha inc eases he indi idual’s in ol emen (Cy e al., 2018). In he cu en s udy,
whe e S-O-R is applied, we a gue ha design ea u es a e en i onmen cues, which a e likely o
a ec he indi idual’s con inued in en ion o use ia cogni i e and a ec i e in ol emen .
Table 1 Se e al ela ed s udies based on S-O-R heo y
Au ho s
S imulus
O ganism
Response
E oglu e al. (2001)
High and low ask- ele an in o ma ion
A ec and cogni ion
App oach and a oidance
Mummalaneni (2005)
Ambience and design ac o
Pleasu e and a ousal
Sa is ac ion and loyal y
É hie e al. (2008)
In o ma ion, na iga ion, ex , and
isual aspec s
Cogni i e p ocesses
Beha io s
Mangana i e al.
(2009)
Vi ual layou and design
A ec i e and cogni ion
App oach and a oidance
Deng and Poole
(2010)
O de and isual complexi y
Pleasu e and a ousal
App oach and a oidance
Jiang e al. (2010)
In e ac i i y (con ol and
communica ion)
A ec i e and Cogni i e
Pu chase in en ion
Koo and Ju (2010)
G aphics, colo s, links, and menus
Pleasu e and a ousal
In en ion
Lee e al. (2010)
In e ac i i y
Enjoymen and isk
A i ude
Hsu e al. (2012)
In o ma ion, sys em, and se ice
quali y
Pe cei ed low and
pe cei ed play ulness
Sa is ac ion and pu chase
in en ion
Floh and Madlbe ge
(2013)
con en , design, and na iga ion
Shopping enjoymen and
impulsi eness
Impulse buying beha io
Liu e al. (2013)
Visual appeal
Impulsi eness and ins an
g a i ica ion
U ge o buy impulsi ely
Gao and Bai (2014)
In o ma i eness, e ec i eness, and
en e ainmen
Flow
Pu chase in en ion and
sa is ac ion
Lou ei o and Roschk
(2014)
G aphic design and in o ma ion design
Posi i e emo ions
In en ions o e- isi e-
use
Shu-Hao e al. (2014)
Web aes he ics
Con ol and pleasu e
Pu chase beha io
Ali (2016)
Usabili y and unc ionali y
Pe cei ed low
Sa is ac ion and pu chase
in en ion
Liu e al. (2016)
Aes he ic appeal
Pleasu e and ease o use
Sa is ac ion
Bhanda i e al. (2017)
Aes he ics
Emo ion
Quali y pe cep ion
Fang e al. (2017)
App design and pe o mance
U ili a ian, hedonic, and
social bene i s
Beha io al engagemen
in en ion
Peng e al. (2017)
Aes he ic and design
Flow and use ulness
A ec i e and cogni i e
a i ude
Ta u e e al. (2017)
Func ionali y, design, in o ma ion
quali y, and in e ac ion
Engagemen
Con inued in en ion o
use
Ca lson e al. (2018)
Con en quali y, in e ac i i y, and
con ac quali y
Cus ome -pe cei ed alue
Cus ome engagemen
beha io s
Rod íguez e al.
(2019)
Visual appeal, in e ac i i y, and
Pe sonaliza ion
Sa is ac ion, us
Pu chase in en ion
2.1 In ol emen
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In ol emen is “based on inhe en needs, alues, and in e es s ha mo i a e one owa d he objec ”
(Zaichkowsky, 1985). P e iously, i was discussed in e ms o engagemen (Lee and Koza , 2009;
Hen ie e al., 2015; Kim and Baek, 2017; Pa iha e al., 2019), play ulness (La ie and T ac insky,
2004), as a s ong de e minan o sa is ac ion (Jiménez-Za co e al., 2014), a i ude (Cy e al.,
2018), loyal y (Din e al., 2016), in en ion (Kang e al., 2015; Yang e al., 2019), and pe cei ed
usabili y (Sun e al., 2015) ia posi i e expe iences (Guo e al., 2015). Posi i e pe cep ion o
expe iences inc ease he sense o in ol emen , which ul ima ely leads owa d in en ion o use
(DeF anco, 2016). Thus, i is essen ial o c ea e an engaging en i onmen o p omo e use s’
in ol emen and ac i e pa icipa ion in online ac i i ies (Lin, 2007; Guo e al., 2015; Reycha and
Wu, 2015). The design wi h mass hedonic aspec s heigh ens indi iduals’ emo ional esponse
(Zhou e al., 2014) and in en ion (Kim e al., 2007). An indi idual's le el o in ol emen wi h
s imulus a i ac s, e.g., objec s, si ua ions, o ac i i ies, is assessed by he ex en o which he use
pe cei es ha objec o concep o be app op ia e and ele an . In his s udy, in ol emen e e s o
he deg ee o which a use eels ha he in e ac ion wi h he con en s du ing in o ma ion-seeking
ac i i y is bo h necessa y and app op ia e. I is discussed as a need-based cogni ion, o goal-
di ec ed s imula ion, con olled by cogni i e and a ec i e mo i es and conside ed as a c i ical
cons uc in communica ion and in o ma ion esea ch. I is a cen al amewo k o unde s and he
use ’s inal beha io (Chak a a i e al., 2003). This is because, while eeling mo e in ol ed, he
use s a e mo e mo i a ed o explo e he con en s and likely o u ilize he in e ac i e ea u es o
acili a e he p ocess o explo a ion. This p ocess o explo a ion d i es he use ’s mo i a ion and
leads owa d inal beha io . Use s’ in o ma ion p ocessing is in luenced by he s a e o
in ol emen (Wu and Hsiao, 2017). This implies ha he le el o abso p ion and pleasu e o he
use , associa ed wi h he websi e design, may be conside ed as emo ional eac ion. Digi al media,
wi h a mo e engaging en i onmen , ha e a posi i e impac on use in ol emen wi h he websi e
con en s (Hausman and Siekpe, 2009). Kim e al., (2007) a gue ha in ol emen in design is
impo an o de e mine beha io al in en ion. Mo eo e , he au ho s (Pe se, 1990; Jiang e al., 2010;
Kang e al., 2015; Reycha and Wu, 2015), sugges ha in ol emen should be s udied by
sepa a ing hem in o cogni i e and a ec i e componen s as bo h ha e a disc e e in luence on use
beha io .
Cogni i e in ol emen explains he a ional hinking de i ed om u ili a ian, p agma ic, o
cogni i e mo i es (Jiang e al., 2010). I is conside ed an essen ial aspec o in o ma ion p ocessing
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be ween he con inued in en ion o use, cogni i e and a ec i e in ol emen . We assume ha
in ol emen dimensions equally and posi i ely in luence he con inued in en ion o use as he
p o ound in ol emen wi h con en s and in e ac i e p ocedu e keep use s in con ol, which leads
o con inued in en ion o use. Es ablishing he heo e ical g ound and ela ionship be ween
in ol emen (i.e., cogni i e and a ec i e) and con inued in en ion o use, we hypo hesize he
ollowing:
H5a: Cogni i e in ol emen in luences he con inued in en ion o use online lea ning on
sma phones.
H5b: A ec i e in ol emen in luences he con inued in en ion o use online lea ning on
sma phones.
3. Me hodology and Da a Analysis
The objec i e o his esea ch is o unde s and how he design quali y and in e ac i e ea u es a ec
he con inued in en ion o use ia cogni i e and a ec i e in ol emen . The esea ch me hodology
adop ed o his s udy is p ima ily based on da a collec ion h ough a su ey om i e highe
educa ion ins i u ions. The popula ion in he cu en s udy a e bo h unde g adua e and pos g adua e
s uden s. An expe imen al p o o ype o Cou se a (MOOC pla o m) was de eloped o be es ed by
he pa icipan s. Thus, he employed design ea u es (e.g., isual appea ance, in o ma ion,
na iga ion quali y, and in e ac i i y) o he expe imen al p o o ype was qui e simila o Cou se a
and used o en oll in a Human-compu e in e ac ion cou se (see Figu e 2). The colo scheme (i.e.,
blue-whi e, g ey-black and blue) was used in he design o links, sea ch bu ons, and ale s. The
on ea u es used on he expe imen al p o o ype include sans-se i ype ace wi h a size anging
om 14 o 22 px. The colo s employed o he ex we e he black (one o he mos equen ) as
well blue and whi e (less equen ). The na iga ion was suppo ed h ough links, bu ons, and lis
iews along wi h a s uc u ed pa h. To enhance he le el o in e ac i i y, a sea ch ba , messaging
se ice, discussion po al, p og ess ba , help, language change, and o he suppo i e ea u es we e
also inco po a ed in he expe imen al p o o ype. The de eloped expe imen al p o o ype con ains
lec u es, no es and, o he cou se- ela ed ac i i ies. The pa icipan s can download he ideos and
lec u e no es and discuss he lea ning opics wi h o he pa icipan s and eache s on a cha and a
discussion po al.
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Figu e 2 Expe imen al p o o ype
3.1 Su ey Ins umen
A su ey ool was designed o alida e he p oposed hypo heses, and i was ca ego ized in o wo
main sec ions. The i s sec ion aimed a ob aining he pa icipan 's demog aphic in o ma ion,
while he second sec ion was used o assess he p oposed esea ch model and hypo heses o he
expe imen al p o o ype. The measu es o cu en wo k a e adop ed om p io s udies. This sec ion
includes 32 quan i a i e i ems based on a se en-poin Like -scale (1 = s ongly disag ee and 7 =
s ongly ag ee) used o assess each obse ed i em. The scale ocuses on he indi idual’s esponse
ela ing o (1) on quali y, (2) aes he ic quali y, (3) in o ma ion quali y, (4) na iga ion quali y, (5)
esponsi eness, (6) use con ol, (7) communica ion, (8) cogni i e in ol emen , (9) a ec i e
in ol emen , and (10) con inued in en ion o use. I was assumed ha a highe sco e agains he
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adop ed i ems indica es mo e posi i e and a o able pe cep ions. The measu es o his s udy a e
shown in he Appendix. Su ey eliabili y and alida ion a e discussed in he da a analysis sec ion.
Table 2 Demog aphic desc ip ion o he pa icipan s
P o ile ca ego y
F equency
Pe cen age
Gende
Male
423
63.9
Female
239
36.1
Age
Less han 25
196
29.6
Be ween 25 and 30
413
62.4
Abo e 30
53
8.0
Quali ica ion
G adua e le el
500
75.5
Pos g adua e le el
162
24.5
Online lea ning expe ience
Beginne s
235
35.5
In e media e
299
45.2
Ad ance
128
19.3
To al
662
100.0
3.2 Pa icipan s and Da a Collec ion
The de eloped p o o ype was in oduced o he s uden s a he s a o he semes e wi h he help
o uni e si y eache s. The s uden s we e asked o use he applica ion designed o cou se- ela ed
ac i i ies on hei sma phone. They we e p o ided wi h he guidelines ela ed o he usage o he
expe imen al p o o ype in he di e en class sessions by he ins uc o s. These guidelines
inco po a ed he speci ic asks and ac i i ies ha he s uden had o pe o m using he expe imen al
p o o ype (e.g., sea ching, en ollmen , and downloading lec u es). Besides lea ning, hey we e also
ins uc ed o use he p o o ype o o he academic ac i i ies such as quizzes, assignmen s
submission and g oup discussions. A he end o he semes e , he s uden s we e eques ed o sha e
hei pe cep ion by comple ing he ques ionnai e ha co e ed all he measu es o he cons uc s.
The e we e abou 2,100 s uden s ini ially in ol ed; howe e , only 662 pa icipan s ac i ely
comple ed he su ey. The demog aphic desc ip ion o he pa icipan s is gi en in Table 2.
3.3 Da a Analysis
In his analysis sec ion, he au ho s p esen he desc ip i e s a is ics o he indica o s. Table 3
ou lines he compu ed alues o mean and s anda d de ia ion. All means a e abo e midpoin 5.0.
Fu he , he p oposed hypo heses we e es ed using pa ial-leas -squa es, s uc u al equa ion
modeling (PLS-SEM). I is a comple e mul i a ia e-analysis me hod ha can concu en ly e alua e
he ela ionships among all he indica o s in he concep ual model, i.e., measu emen and s uc u al
componen s o de elop he heo ies (Chin, 1998; Joseph e al., 2011; Kock, 2014). PLS-SEM also
p o ides s able weigh s wi h no in la ed measu emen (Kock, 2014). I p o ides a lexible way o
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de e mine he key cons uc s and helps o execu e he complex s uc u ed model. Ini ially, he
communali ies show he a iance explained by he i ems. I is ecommended ha he i ems wi h
communali ies unde 0.70 should be elimina ed o ob ain he sugges ed con e gen alidi y (Chin,
1998; Joseph e al., 2011; Kock, 2014).
Table 3: Cons uc eliabili y, alidi y, and Unidimensionali y
No e: SD = S anda d de ia ion; α = C onbach's alpha; CR = Composi e eliabili y; AVE = A e age a iance ex ac ed; 1s Comp = i s Componen ; 1s (%) = % o
Va iance.
Reliabili y in his s udy was compu ed acco ding o he c i e ia sugges ed by Fo nell and La cke
(1981), Chin (1998), and Hai e al., (2015) which consis s in de e mining he ou e -loadings
pa e n o he adop ed i ems (Fo nell and La cke , 1981). The alue o loadings in his s udy
Cons uc s
Unidimensionali y
Eigen alues
Va iance explained
Fac o
loadings
Mean
SD
α
CR
AVE
ho A
1s Comp
2nd Comp
1s (%)
2nd (%)
Fon quali y
0.77
0.87
0.689
0.79
2.066
.565
68.857
18.839
FQ1
0.857
4.79
1.66
FQ2
0.856
4.81
1.69
FQ3
0.774
5.13
1.66
Aes he ic quali y
0.86
0.91
0.780
0.86
2.339
.453
77.954
15.113
AQ1
0.828
5.33
1.60
AQ2
0.924
5.40
1.60
AQ3
0.894
5.28
1.58
In o ma ion quali y
0.79
0.88
0.710
0.80
2.129
.517
70.967
17.227
IQ1
0.867
5.13
1.66
IQ2
0.860
5.41
1.64
IQ3
0.799
5.28
1.55
Na iga ion quali y
0.74
0.85
0.662
0.75
1.987
.593
66.234
19.765
NQ1
0.849
5.03
1.64
NQ2
0.824
5.17
1.53
NQ3
0.766
5.32
1.79
Responsi eness
0.80
0.88
0.712
0.80
2.135
.536
71.168
17.871
RS1
0.852
4.86
1.65
RS2
0.883
4.98
1.59
RS3
0.793
5.25
1.69
Use con ol
0.80
0.88
0.720
0.81
2.155
.500
71.842
16.666
UC1
0.876
4.93
1.60
UC2
0.855
5.19
1.63
UC3
0.810
5.21
1.62
Communica ion
0.80
0.88
0.713
0.80
2.138
.581
71.257
19.372
CC1
0.867
5.14
1.57
CC2
0.896
5.23
1.56
CC3
0.763
5.24
1.78
Cogni i e in ol emen
0.86
0.92
0.785
0.86
2.354
.361
78.470
12.036
CI1
0.883
5.32
1.63
CI2
0.901
5.30
1.59
CI3
0.873
5.30
1.59
A ec i e in ol emen
0.88
0.92
0.733
0.88
2.932
.409
73.296
10.236
AI1
0.832
5.26
1.57
AI2
0.871
5.50
1.60
AI3
0.877
5.45
1.61
AI4
0.843
5.31
1.61
Con inued in en ion o use
0.86
0.91
0.709
0.86
2.835
.581
70.887
14.517
CIU1
0.876
4.82
1.89
CIU2
0.885
4.94
1.72
CIU3
0.868
4.93
1.79
CIU4
0.730
4.94
1.81
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exceeded 0.7 and anged om 0.730 o 0.901 (see Tables 3 and 4) wi h signi icance le els (≤ 0.05)
along wi h alues (≥ 1.96). The in e nal consis ency is also impo an o examine he eliabili y
o he employed ac o s h ough C onbach's alpha (α), which is based on he a e age in e -
co ela ion o i ems (Joseph e al., 2011). The app op ia e alue o C onbach's alpha α depends on
he na u e o he s udy. The e a e no s anda dized c i e ia o he alue o C onbach's α. Howe e ,
he minimum alue o α is gene ally ag eed a abou 0.70 (Joseph e al., 2011). I he esea ch is
no explo a o y, hen he lowes accep ed alue should be 0.80, whe e a ule-o - humb o α alue
e e s o “α ≥ 0.9 = excellen , α ≥ 0.8 = good, α ≥ 0.7 = accep able, α ≥ 0.6 = ques ionable, α ≥ 0.5
= poo , and α ≥ 0.4 = unaccep able” espec i ely (Geo ge and Malle y, 2003). The ange o
C onbach's α in his s udy is obse ed om 0.74 o 0.88 (see Table 3). The agg ega e alue o α is
equal o 0.81, which shows ha he cu en su ey ool could be conside ed as a eliable ool wi h
good in e nal consis ency. The o he ype o in e nal consis ency is composi e eliabili y (CR). I
is also simila o C onbach's α bu compu ed di e en ly as α assumes ha all he obse ed i ems
weigh equally. On he o he hand, CR weighs each i em depending on he weigh s o he single
i ems. Howe e , “CR is conside ed a mo e accu a e app oach o assessing eliabili y” (Richa d
and Youjae, 1988). The c i e ion o assess he CR speci ies ha i s alue should be equal o o
g ea e han 0.70 (Richa d and Youjae, 1988). In his s udy, all he CR alues exceeded 0.7 and
anged om 0.85 o 0.92 (see Table 3). The CR is conside ed as an app op ia e app oach o
e alua e he eliabili y. Fu he mo e, Dijks a Hensele 's ho (2015) was also used o measu e
eliabili y. In his s udy, he ho alues exceeded 0.7 and anged om 0.75 o 0.88 (see Table 3).
Las ly, eliabili y was also analyzed by measu ing he loadings o he i ems wi h he ac o s o
which hey a e hypo he ically associa ed (see Table 4).
The ou e model was also assessed using addi ional me hods, i.e., unidimensionali y, con e gen
alidi y (CV), and disc iminan alidi y (DV). Fi s , i is c ucial o analyze he unidimensionali y
o he scale. Fo his, we used a p incipal componen analysis (i.e., ac o ial explo a o y analysis)
wi h a imax o a ion. Acco ding o Kaise 's c i e ion (1960), unidimensionali y holds i an
eigen alue abo e one is achie ed o he i s p incipal componen (Faisal e al., 2017). All he
adop ed cons uc s o his wo k mee he Kaise 's c i e ion; mo eo e , he i s p incipal componen
ex ac ed p o ides a signi ican ly highe a iance han he second componen . Thus, he esul s
ob ained sa is y he sugges ed c i e ia (see Table 3).
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Table 4 Disc iminan alidi y: Combined loadings and c oss-loadings (ou e loadings)
CV “shows he deg ee o which he i ems o a ce ain ins umen a e ela ed (Ronnie and Doug,
2013).” The CV assessmen c i e ion is ela ed o he compu a ion o he a e age a iance
ex ac ed (AVE). The minimum sugges ed alue o AVEs should be highe han o equal o 0.5
(Richa d and Youjae, 1988). This means ha all he indica o s epo o mo e han 50 pe cen o
he a iance o hei cons uc . Table 3 shows ha all he indica o s ul ill he ecommended
equi emen .
DV “is he ex en o which he cons uc does no co ela e wi h o he measu es ha a e di e en
om i ” (Richa d and Youjae, 1988). In a model, i speci ies he di e ences be ween adop ed
cons uc s (Chin, 1998). I s assessmen depends on wo c i ical elemen s, as men ioned in p e ious
esea ch. The i s elemen is ha he loadings o he i ems should be poo ly associa ed wi h all
cons uc s excep he one o which hey a e hypo he ically connec ed (Chin, 1998). As he
“co ela ion o he la en a iable sco es on he measu emen i ems needs o show an app op ia e
Cons uc s
I ems
Loadings c oss-loadings
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(8)
(9)
1-Fon quali y
FQ1
0.857
-0.328
0.002
0.056
-0.093
-0.058
0.043
-0.111
0.028
0.051
FQ2
0.856
-0.191
0.196
-0.018
0.055
0.202
-0.091
-0.175
-0.189
-0.031
FQ3
0.774
0.575
-0.218
-0.042
0.042
-0.160
0.052
0.317
0.179
-0.022
2-Aes he ic quali y
AQ1
0.071
0.828
-0.053
-0.147
0.176
-0.254
-0.109
-0.087
0.510
-0.019
AQ2
-0.047
0.924
0.010
-0.019
0.008
0.081
0.068
-0.062
-0.225
0.061
AQ3
-0.017
0.894
0.039
0.155
-0.172
0.152
0.031
0.145
-0.241
-0.046
3-In o ma ion quali y
IQ1
0.328
-0.217
0.867
-0.014
0.168
-0.073
-0.068
-0.232
0.039
-0.020
IQ2
-0.192
-0.010
0.860
0.159
-0.118
0.124
0.077
-0.278
-0.130
0.085
IQ3
-0.149
0.246
0.799
-0.156
-0.056
-0.054
-0.009
0.551
0.098
-0.070
4-Na iga ion quali y
NQ1
0.288
-0.057
0.057
0.849
0.004
0.110
-0.089
-0.280
-0.125
0.016
NQ2
0.025
-0.218
0.280
0.824
0.132
-0.017
-0.321
-0.096
0.194
-0.002
NQ3
-0.347
0.298
-0.365
0.766
-0.147
-0.103
0.443
0.414
-0.070
-0.015
5-Responsi eness
RS1
-0.149
-0.012
0.090
0.069
0.852
0.158
0.047
-0.131
-0.371
-0.027
RS2
0.054
-0.090
-0.089
0.048
0.883
0.082
0.080
0.069
-0.273
0.043
RS3
0.100
0.113
0.003
-0.128
0.793
-0.261
-0.139
0.064
0.073
-0.019
6-Use con ol
UC1
0.129
-0.117
-0.069
0.018
0.256
0.876
-0.023
-0.240
-0.089
-0.013
UC2
0.027
-0.060
0.095
-0.068
0.135
0.855
-0.021
-0.350
0.136
0.018
UC3
-0.168
0.190
-0.025
0.052
-0.419
0.810
0.048
0.629
-0.048
-0.005
7-Communica ion
CC1
0.104
-0.149
0.211
-0.331
0.204
0.094
0.867
-0.229
-0.067
0.018
CC2
0.063
-0.077
0.117
-0.132
-0.023
0.022
0.896
-0.203
0.248
-0.006
CC3
-0.192
0.259
-0.377
0.531
-0.205
-0.132
0.763
0.498
-0.216
-0.013
8-Cogni i e in ol emen
CI1
0.021
-0.020
-0.075
0.033
0.068
-0.063
-0.036
0.883
0.038
-0.023
CI2
-0.104
0.126
0.158
-0.148
0.174
-0.050
-0.054
0.901
-0.083
0.023
CI3
0.086
-0.109
-0.087
0.12
-0.249
0.115
0.092
0.873
0.048
0.000
9-A ec i e in ol emen
AI1
-0.008
-0.136
0.251
-0.389
-0.022
0.123
0.442
0.012
0.832
0.024
AI2
-0.050
-0.281
0.049
0.209
-0.127
0.066
-0.066
-0.021
0.871
0.002
AI3
0.036
0.016
-0.142
0.134
0.000
-0.03
-0.061
-0.044
0.877
-0.015
AI4
0.022
0.407
-0.151
0.029
0.152
-0.158
-0.304
0.056
0.843
-0.011
10-Con inued in en ion o use
CIU1
-0.011
0.195
0.000
-0.005
-0.102
0.054
-0.066
-0.051
-0.066
0.876
CIU2
0.098
-0.039
-0.005
-0.006
0.01
-0.045
-0.003
0.001
-0.002
0.885
CIU3
-0.014
-0.082
0.028
0.039
0.06
-0.058
0.001
0.092
-0.053
0.868
CIU4
-0.089
-0.089
-0.027
-0.034
0.039
0.059
0.082
-0.051
0.144
0.730
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pa e n o loadings, one on which he measu emen i ems load highly on hei specula i ely
assigned ac o and no high on o he ac o s” (Ge en and S aub, 2005). In simple wo ds, all i ems
a e loaded highly on hei co esponding ac o s while lowe on o he ac o s (see Table 4). The
second c i e ion is associa ed wi h AVE alues. AVE illus a es he p opo ion o a iance a ained
by a cons uc . Thus, o ensu e and o measu e his indica o , he o each cons uc should
AVE
be highe han he co ela ion alue be ween cons uc s (see Table 5) (Chin, 1998; Fo nell and
La cke 1981; Ge en and S aub, 2005). Table 5 also shows ha o each cons uc , he a e age
is mo e signi ican han i s co ela ion coe icien wi h o he cons uc s. In addi ion o
AVE
Fo nell and La cke (1981), He e o ai –Mono ai Ra io o Co ela ions c i e ion was also
employed o assess he disc iminan alidi y and i shows ha he compu ed alues a e ≤ 0.90, as
sugges ed in p e ious s udies (Mohseni e al., 2018). In conclusion, his su ey has s ong
eliabili y and exhibi s good con e gen alidi y and disc iminan alidi y; he e o e, he esul s
sa is y widely accep ed alidi y s anda ds.
Table 5: Disc iminan alidi y: Fo nell–La cke (In e -co ela ions and Sq o AVE o la en a iables)
No e: Bold diagonal numbe s a e he squa e oo s o AVE.
Las ly, he e i ica ion o he likely exis ence o mul icollinea i y be ween he a iables was
analyzed using he ull a iance in la ion ac o (VIF) s a is ic. This echnique is used o iden i y
he possibili y o simila i y. Thus, a highe VIF alue be ween he wo indica o s sugges s ha hey
measu e simila hings. In such a case, one o he in ol ed a iables should be emo ed om he
model. The e o e, a high VIF index can be a se e e issue i he compu ed alue is la ge han he
indica ed alue. Usually, i is ecommended ha he VIF alue o a iables should be less han 5,
e en he mo e elaxed c i e ion ecommended in he p io s udy se s he h eshold a 10 (Faisal e
al., 2017). In he cu en s udy, he compu ed esul s show ha VIFs a e a below he c i ical
alue. Hence, no a iable had o be emo ed. The VIF alues in his esea ch a e obse ed o be
Cons uc s
Fo nell-La cke C i e ion (FL)
1
2
3
4
5
6
7
8
9
10
1
Fon quali y
0.830
2
Aes he ic quali y
0.777
0.883
3
In o ma ion quali y
0.804
0.758
0.842
4
Na iga ion quali y
0.763
0.764
0.809
0.814
5
Responsi eness
0.743
0.755
0.763
0.783
0.844
6
Use con ol
0.776
0.733
0.752
0.799
0.802
0.850
7
Communica ion
0.737
0.747
0.764
0.765
0.741
0.793
0.844
8
Cogni i e in ol emen
0.742
0.798
0.751
0.739
0.717
0.749
0.777
0.886
9
A ec i e in ol emen
0.753
0.814
0.797
0.752
0.814
0.764
0.800
0.769
0.856
10
Con inued in en ion o use
0.543
0.458
0.500
0.506
0.540
0.506
0.475
0.464
0.473
0.842
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benea h he signi ican h eshold alue = 5, while he a e age VIF (AVIF) = 1.98 (see Table 6). In
p io s udies, he ideal ecommended alue o AVIF is ≤ 3.3 (Hai e al., 1987; Joseph, 2009).
Table 6: Addi ional model i and quali y indica o s
No e: SPR = Sympson's pa adox a io; RSCR = R-squa ed con ibu ion a io; SSR = S a is ical supp ession a io, SRMR =
S anda dized oo mean squa e esidua.
PLS-SEM also epo ed o he quali y indica o s i.e. a e age R2 = 0.657, p ≤ 0.001, a e age
adjus ed R2 = 0.656, ≤ 0.001, and a e age pa h coe icien = 0.155, p ≤ 0.001, espec i ely. Model
Fi is compu ed using s anda dized oo mean squa e esidual (SRMR) and Tenenhaus GoF
(Mohseni e al., 2018; Tenenhaus e al., 2005) c i e ion GoF= o
(
AVE
)
X
(
ARS
)
= = 0.65. In ecen s udies (We zels e al., 2009; Kock,
(
Communali y
)
X
(
ARS
)
(
0.721
)
X
(
0.596
)
2014), he esea che s ecommended he GoF c i e ia as ollows: small ≥ 0.1, medium ≥ 0.25, and
la ge ≥ 0.36. The alue o SRMR is obse ed o be 0.08, below he ecommended h eshold o
0.10, which means a good model i ness (see able 6). In conclusion, all he compu ed alues
demons a ed a good quali y i . Thus, he cu en s udy implemen s all he condi ions men ioned
abo e o e i y he model and hypo heses. Fo addi ional quali y measu es, see Table 6.
Table 7: Coe icien o de e mina ion R-squa ed (R2) and Q-squa ed (Q2) coe icien s
A e ha ing con i ma ion o he ou e model indica o s such as unidimensionali y, eliabili y, and
alidi y, he nex s age is o examine he inne model. The inne model desc ibes he s eng h o
he ela ionship among he hypo hesized a iables de i ed om subs an i e heo y (B iz-Ponce e
al., 2017; Chin, 1998). We assess he explana o y powe o he inne model (β) and he amoun o
a iance (R2) (Chin, 1998; Fo nell and Cha, 1994), whe e independen ac o s explain dependen
ac o s. Ini ially, i is c ucial o compu e he (β) and i s signi icance. Figu e 3 and Table 8
Quali y indices
Obse ed alue
Accep able
Ideal alue
95%
99%
SPR.
1.000
≥ 0.7
1
RSCR.
1.000
≥ 0.9
1
SSR.
1.000
≥ 0.7
Nonlinea bi a ia e causali y di ec ion a io.
1.000
≥ 0.7
SRMR
0.070
0.040
0.040
d_ULS
2.450
0.730
0.800
d_G
1.130
0.530
0.550
AVIF
1.98
≤ 10
≤ 3.3
Cons uc
The coe icien o
de e mina ion R-squa ed
Adjus ed R-squa ed
S one-Geisse Q-squa ed
Cogni i e in ol emen
0.74
0.74
0.737
A ec i e in ol emen
0.81
0.80
0.803
Con inued in en ion o use
0.25
0.25
0.252
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demons a e he β o each pa h along wi h i s signi ican p- alue. The R2 examines he a iance
o each cons uc . I is used o desc ibe he model's explana o y powe . Tables 7 and 8 depic s R2
and - alue o each cons uc , espec i ely. Acco dingly, he ou e model explained 74% he
a iance o cogni i e in ol emen , 81% he a iance o a ec i e in ol emen , and 25 % in
con inued in en ion o use, espec i ely (see Table 7). In o he wo ds, he cons uc a ec i e
in ol emen has he highes alue, 81%, ollowed by cogni i e in ol emen , 74%. Howe e , i is
di icul o es ablish he ule o humb o he minimum accep able a iance alue. P io li e a u e
desc ibed he R2 alue 0.75 as s ong, 0.45 as mode a e, and 0.25 as weak (Joseph e al., 2011).
All he cons uc s in his s udy ha e s ong and mode a e le els o a iance excep he con inued
in en ion o use, which demons a ed a weak le el. I is also essen ial o compu e he e ec size in
o de o “iden i y which one o he independen a iables accoun o mos o he a iance in a
dependen a iable” (Joseph e al., 2011). Table 8 shows he e ec size alues. The alues o 0.02,
0.15, and 0.35 sugges ed small, medium, and la ge e ec sizes, espec i ely, as desc ibed in he
classic li e a u e. Finally, all he S one-Geisse Q2 coe icien s ( esampling-analog o he R2
coe icien ) exceeded he minimum h eshold o 0.00 alue, p o iding a ma k o sa is ac o y
p edic i e alidi y (see Table 7) (Joseph e al., 2011). In summa y, all indica o s a e obse ed o
be signi ican o suppo he p oposed model (see Figu e 3, and Table 7 and 8).
4. Resul s
The esul s pa ially suppo he p oposed hypo heses (see Figu e 1) and indica e ha he employed
quali y design posi i ely a ec s he con inued in en ion o use ia cogni i e and a ec i e
in ol emen . The unde lying analysis sec ion illus a es he essen ial indings ela ed o design
aspec s (see Figu e 3 and Table 8). The esul s a e also in e es ing because he e is no e idence
a ailable in p io li e a u e ha explains and analyzes he ole o design a ibu es sepa a ely in
online se ings.
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No es: The s aigh lines ep esen signi ican ela ionships; he do ed lines non-signi ican ela ionships o
unsuppo ed hypo heses.
Figu e 3 Resul s om S uc u al Model Analysis [Sample n = 662]
Hypo heses 1a-d: The quali y o appea ance e e s o he use o app op ia e g aphics, colo , on ,
and mul imedia i ems o o ganize he isual design o a websi e (Al-Qeisi e al., 2014). The p ecise
o ganiza ion and layou a e also conside ed essen ial aspec s o appea ance, a ac i eness, and
appeal. Fon quali y e e s o he appea ance and he a angemen o ex in o de o imp o e
legibili y and in o ma ion p ocessing. The e ec o on quali y (β = 0.09, p ≤ 0.08, = 1.73) on
cogni i e in ol emen is obse ed o be posi i e (see Figu e 3 and Table 8). Howe e , no
ela ionship is obse ed be ween on quali y and a ec i e in ol emen (β = 0.02, p ≤ 0.74, =
0.33). In his s udy, on quali y (i.e., s yle, size, and layou ) is ela ed o cogni i e in ol emen .
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sma phones is also conside ed an essen ial educa ional app oach. In his con ex , he in e ace
plays a c ucial ole in adop ing hese echnologies. The cu en s udy p oposes a model o explo e
he impac o design quali y on he con inued in en ion o use. Some in e es ing indings ela ed o
he implica ions o design a i ac s we e ob ained. These implica ions b ing p ac ical guidelines
o designing mo e in e ac i e in e aces o mee indi iduals' posi i e a i udes o con inued
in en ion o use.
An expe imen al p o o ype was de eloped o es he p oposed hypo heses. The s udy was
conduc ed in di e en educa ional ins i u ions, and he da a we e collec ed om bo h
unde g adua e and pos g adua e s uden s (n = 662). The la ge s uden sample was a conclusi e
and eliable ea u e o his esea ch. The esul s pa ially suppo he p oposed model. The indings
indica e ha design quali y heigh ens he indi idual's in ol emen , which ul ima ely leads o
con inued in en ion o use. The cu en s udy will d aw he a en ion o p ac i ione s owa ds he
pe cep ion o use s o p o iding hem wi h con enien and app op ia e lea ning esou ces. This is
because con enience and p ecise p ocedu es, along wi h unde s andable e minologies, heigh en
he in ol emen , mo i a ion, and exci emen , which ul ima ely leads o con inued in en ion o use.
Mo eo e , he u iliza ion o sui able isual in o ma ion and in e ac i i y aspec s enhance he le el
o engagemen and p omo e use in ol emen , i.e., pleasu e and in o ma ion p ocessing, while
in e ac ing wi h lea ning applica ions on sma phones. Academic ins i u ions should conside
design quali y as an essen ial aspec while de eloping lea ning esou ces. De elope s should
include isual elemen s, such as on , g aphics, colo , and mul imedia, in a way o inc ease
indi iduals’ in ol emen . Mo eo e , na iga ion and in o ma ion ea u es, i.e., in o ma ion
p esen a ion and menus appea ance, should be clea and easy o use o p o ide be e expe iences.
This is because a posi i e expe ience o deep in ol emen inc eases he o e all sa is ac ion
(Madi inos and Theodo idis, 2010). In e ac i i y, i.e., esponsi eness, use con ol, and
communica ion a e also essen ial o es ablish e ec i e communica ion. O he s udies (Kang e al.,
2015; Ta u e e al., 2017; Nikou and Economides, 2018) also discuss he impo ance o in e ace
design o ela ed echnologies. Likewise, Reycha and Wu (2015) a gue ha a ich design
e ec i ely engages indi iduals o explo e in o ma ional con en con enien ly.
Besides, his s udy also en ails se e al limi a ions by de aul . Fi s , he sample used was composed
o s uden s om highe educa ion ins i u ions, which may no ep esen he o e all popula ion.
Thus, he use o highe educa ion ins i u ion s uden s may a ec he gene alizabili y o his
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esea ch and dec ease he applicabili y o indings in o o he se ings. Second, he age, expe ience,
and educa ional backg ound o he s uden s we e likely o be homogenous. Too many dispe sions
wi h ega ds o his issue a e no expec able. Thi d, only a single p o o ype wi h limi ed ac i i ies
was used in his wo k, al hough his way is consis en wi h pas s udies (Saade and Bahli, 2005).
This may also educe he gene alizabili y and ans e abili y o he esul s. In e ms o u u e scope,
p e ious s udies ha show he ela ionship be ween design a ibu es and cogni i e and a ec i e
in ol emen a e limi ed. Thus, u he s udies a e necessa y o de e mine he ela ionship be ween
hese a iables. The en i onmen al and indi iduals ac o s, such as gende , expe ience, ai s,
cul u e, mo i a ion, no ma i e belie s, and moods may impac cogni i e and a ec i e in ol emen
may also be good poin s o u u e esea ch. We also wan o in es iga e u he he ole o de ice
ype and o he isual aspec s (i.e., classical s. exp essi e, symme y s. asymme y, complexi y
s. simplici y, and di e si y) in de e mining he indi idual’s in ol emen .
Acknowledgemen
This wo k has been pa ially unded by he Spanish Depa men o Science, Inno a ion, and
Uni e si ies (P ojec RTI2018-099235-B-I00) and he Uni e si y o O iedo (GR-2011-0040).
Re e ences
Abachi, H. R. and Muhammad, G. (2013) ‘The impac o m-lea ning echnology on s uden s and educa o s’,
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Appendix A
Cons uc s
I ems
Mean
SD
Fon quali y
(Shu-Hao e al., 2014; Ali, 2016; Faisal e al., 2017)
FQ1
I is easy o ead he ex on his websi e wi h he used on ype and size.
4.79
1.668
FQ2
The on colo is appealing on his websi e
4.81
1.690
FQ3
The ex alignmen and spacing on his websi e make he ex easy o ead.
5.13
1.663
Aes he ic quali y
(Mummalaneni, 2005; Koo and Ju, 2010; Cy and Head, 2013; Ali, 2016; Hoehle e al.,
2016)
AQ1
The mobile applica ion g oups elemen s oge he ha a e simila and belong
oge he .
5.33
1.609
AQ2
The mobile applica ion uses anima ions app op ia ely.
5.40
1.602
AQ3
The sc een design o his mobile applica ion (i.e. colo s, images, layou e c.) is
a ac i e.
5.28
1.588
In o ma ion quali y
(E oglu e al., 2001; Hausman and Siekpe, 2009; Hsu e al., 2012; Al-Qeisi e al., 2014;
Ali, 2016; Ta u e e al., 2017)
IQ1
The in o ma ion p o ided a his mobile applica ion is use ul.
5.13
1.663
IQ2
The in o ma ion p o ided a he mobile applica ion is accu a e and comple e.
5.41
1.647
IQ3
The in o ma ion p o ided a his mobile applica ion is ele an .
5.28
1.559
Na iga ion quali y
(Koo and Ju, 2010; Hsu e al., 2012; Cy and Head, 2013; Ali, 2016; Hoehle e al., 2016;
Ta u e e al., 2017)
NQ1
I can easily na iga e his mobile applica ion.
5.03
1.643
NQ2
The mobile applica ion uses a na iga ional hie a chy.
5.17
1.536
NQ3
This mobile applica ion p o ides good na iga ion acili ies o in o ma ion
con en .
5.32
1.794
Responsi eness
(Hsu e al., 2012; Fan e al., 2017; Rod íguez-To ico e al., 2019)
RS1
I am able o ob ain he in o ma ion I wan wi hou any delay.
4.86
1.658
RS2
The mobile applica ion is e y as in esponding o my eques .
4.98
1.598
RS3
When I use he mobile applica ion, I el I was ge ing ins an aneous
in o ma ion.
5.25
1.693
Use Con ol
(Jiang e al., 2010; Fan e al., 2017; Ta u e e al., 2017; Rod íguez-To ico e al., 2019; Wu,
2019)
UC1
I eel ha I ha e a g ea deal o con ol o e my using expe ience.
4.93
1.606
UC2
The mobile applica ion is manageable.
5.19
1.636
UC3
While I was using he mobile applica ion, I could choose eely wha I wan ed
o do.
5.21
1.620
Communica ion
(Jiang e al., 2010; Fan e al., 2017)
CC1
The mobile applica ion acili a es wo-way communica ion.
5.14
1.573
CC2
The mobile applica ion acili a es concu en communica ion.
5.23
1.562
CC3
The mobile applica ion gi es me he oppo uni y o alk back.
5.24
1.786
Cogni i e in ol emen
(Celuch and Slama, 1998; Reycha and Wu, 2015)
CI1
This mobile applica ion is needed.
5.32
1.630
CI2
This mobile applica ion is aluable.
5.30
1.593
CI3
This mobile applica ion is ele an .
5.30
1.595
A ec i e in ol emen
(Celuch and Slama, 1998; Reycha and Wu, 2015)
AI1
This mobile applica ion is ascina ing.
5.26
1.573
AI2
This mobile applica ion is in e es ing.
5.50
1.603
AI3
This mobile applica ion is appealing.
5.45
1.618
AI4
This mobile applica ion is in ol ing.
5.31
1.612
Con inued in en ion o use
(Ahn e al., 2007; Hoehle e al., 2016; Ta u e e al., 2017)
CIU1
I in end o con inue using he mobile applica ion.
4.82
1.894
CIU2
I will use his mobile applica ion on a egula basis in he u u e.
4.94
1.724
CIU3
I p edic I will con inue using he mobile applica ion.
4.93
1.791
CIU4
I encou age iends and ela i es o be he cus ome s o he mobile applica ion.
4.94
1.815
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