Design quality in building behavioral intention through affective and cognitive involvement for e-learning on smartphones

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 1 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 Page 1 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 2 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 Page 2 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 3 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 Page 3 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 4 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 Page 4 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 5 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 Page 5 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 6 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. Page 6 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 7 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 Page 7 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 8 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 Page 8 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 15 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. Page 15 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 16 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 Page 16 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 17 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 Page 17 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 18 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 Page 18 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 19 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). Page 19 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 20 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 Page 20 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 21 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 Page 21 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 22 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 Page 22 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 23 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. Page 23 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 24 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 . Page 24 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 31 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 Page 31 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 32 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 . 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Page 38 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 In e ne Resea ch 39 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 Page 39 o 39 h p://mc.manusc ip cen al.com/in In e ne Resea ch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60