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TOJEET: The Turkish Online Journal oof Educational TTechnology – Occtober 2012, volume 11 Issue 4 Fit index χ 2 Table 5 FFit Indices of tthe Extended UTAUT U Modell Level of accepptable fit Fit of tthe p < .055 eextended UTAAUT model 541.846; p < .000 CFI > .9000 .984 RMSEA < .0600 .039 SRMR < .0500 .028 CFI = com mparative fit inndex; RMSEA = root mean ssquare error off approximatioon; SRMR = sstandardized rooot mean residdual Figure 1 Verification of the Extendded UTAUT MModel with Pathh Coefficients for the EEntire Sample Table e 6 Hofstede’s s Cultural Dimmensions Scorees in Turkey, CCompared withh Germany and d Romania Turkeyy Coomparative valu ues (N = 17223) Germany Romania Power distaance index (PD DI) 9.6 36.1 20.1 Collectivism vs. individu ualism (IDV) 76.5 92.5 67.4 Masculinity y vs. femininit ty (MAS) 3.4 -29.9 38.5 Uncertaintyy avoidance (U UAI) 43.7 76.9 65.2 Long-term orientation (LTO) 42.5 45.6 53.7 The Influeence of Region nal Culture Regarding attitudes towaards education nal technologyy, participants from Istanbul area had signnificantly highher performanc ce expectationss, lower compu uter anxiety, thhey used educaational technoloogy more intennsively, and they evaluated the t own comp puter literacy hhigher than paarticipants from m other regionns (Table 7). With respect to Hofstede’s cultural dimen nsion scores, nno significant ddifferences wer re found (Tablee 8). Further de etails concerninng participants s’ acceptance were extracted by repeatingg the structura al equations prrocedure descrribed above annd testing the extended UTA AUT model sepparately for parrticipants from Istanbul area aand from otherr regions. Tabble 7 Values off the UTAUT Variables withh Regional Diff fferences Istannbul area Other regions r Diffferences (n = 962) (n = 761) (Onewaay ANOVA) M (SD) M ( SD) F df p Performancce expectancy 4.49 (0.69) 4.38 (0.69) ( 10.27 1722 0.0001 Effort expe ectancy 4.13 (0.75) 4.12 (0.72) ( 0.05 1722 0.8220 Social influuence 3.44 (1.07) 3.43 (1.03) ( 0.04 1722 0.8444 Facilitatingg conditions 3.20 (0.88) 3.13 (0.89) ( 2.71 1722 0.1000 Computer aanxiety 2.01 (0.96) 2.15 (0.99) ( 9.75 1722 0.0002 Use intention 3.57 (1.24) 3.56 (1.20) ( 0.00 1722 0.9775 Use behaviior 4.45 (0.67) 4.29 (0.68) ( 26.45 1722 0.0000 Computer lliteracy 4.59 (0.66) 4.44 (0.66) ( 20.35 1722 0.0000 Copyright © Th he Turkish Onlinne Journal of Ed ducational Technnology
TOJEET: The Turkish Online Journal oof Educational TTechnology – Occtober 2012, volume 11 Issue 4 Table 8 Hofstede’s Cultural C Dimennsions Scores with Regionall Differences Istanbul areea Other reegions Welch-Lerrche two sampple t-test (n = 962) ) (n = 7761) t df p Power distaance index (PDI) 11.8 6.99 -2.08 1466.13 0.981 Collectivism vs. individualism (IDV) 79.0 73. .3 -2.87 1492.18 0.998 Masculinity y vs. femininity (MAS) 3.92 2.776 -0.29 1488.80 0.613 Uncertaintyy avoidance (UAI) 46.0 40. .9 -1.75 1487.76 0.960 Long-time orientation (LTO) 42.1 42. .9 0.84 1529.47 0.202 As shown in i Figure 2, the e use behavior r of participantts from Istanbuul area was stroonger influenceed by facilitatinng conditions, , and their use e intention was stronger inflluenced by efffort expectancyy, wheres the use behavior of participants s from other areas was strronger influennced by compuuter anxiety, and their use intention moore subjected too social influennce. Figgure 2 The Exte tended UTAUTT Model with RRegional Diffeerences (Istanbbul area/other Regions) The Influeence of Professsional Culturee Observing participants’ attitudes towwards educatioonal technologgy, those withh STEM prof fessions showwed significantlly higher perfo formance and eeffort expectanncy, at the sam me time lowerr computer annxiety, they used educational technology more m intensiveely, and evaluaated the own ccomputer literaacy as higher tthan participannts with non-SSTEM professions (Table 9). As for the diffferences betweeen professionaal groups relat ted to Hofstedee’s cultural dimmensions, the pparticipants wiith STEM proffessions were less l power disttant, exhibited lower values oon masculinity y, and were le ess uncertaintyy avoidant thann the participa ants with non-STEM professsions. Howeveer, according tto the Welch-L Lerche test onlly the differencce in PDI provved to be signifficant (Table 10). 1 With respeect to the pathh coefficients of o the extende ed UTAUT moodel (Figure 3), 3 the use behhavior of the pparticipants wiith STEM proofessions was less l influencedd by facilitatinng conditions and computer r anxiety as coompared to noon STEM proffessions. Their r use intention was also someewhat weaker in nfluenced by eeffort expectancy. Table 9 VValues of the UUTAUT Variabbles for the Entire Sample an nd for the Partticipants with SSTEM vs. nonn STEMM Professions STEM professions Non-STEM M professions Diffferences (n = 702) (n = 1021) 1 (Onewaay ANOVA) M (SD) M ( SD) F df p Performancce expectancy 4.48 (0.64) 4.41 (0.72) ( 5.018 1722 0.0225 Effort expe ectancy 4.18 (0.70) 4.09 (0.76) ( 6.621 1722 0.010 Social influuence 3.49 (1.01) 3.40 (1.07) ( 3.650 1722 0.0556 Facilitatingg conditions 3.19 (0.91) 3.15 (0.87) ( 0.715 1722 0.3998 Computer aanxiety 2.00 (0.97) 2.12 (0.98) ( 5.536 1722 0.019 Use intention 3.53 (1.24) 3.59 (1.22) ( 1.067 1722 0.3002 Use behaviior 4.44 (0.66) 4.34 (0.68) ( 8.208 1722 0.0004 Computer lliteracy 4.59 (0.66) 4.48 (0.66) ( 12.09 1722 0.0001 Copyright © Th he Turkish Onlinne Journal of Ed ducational Technnology
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