october 2012 - TOJET the Turkish online journal of educational ...

More documents

Recommendations

Info

TOJEET: The Turkish Online Journal oof Educational TTechnology – Occtober 2012, volume 11 Issue 4 Table 10 Hof fstede’s culturaal dimensions scores of STEEM and non-STTEM professio onals STEM Non-STEM Welch-Lerrche two sampple t-test professionns professions (n = 702) ) (n = 1021) t df p Power distaance index (PDI) 6.08 12.001 2.55 1354.61 0.006 Collectivism vs. individualism (IDV) 77.0 76. .1 -0.44 1296.95 0.669 Masculinity y vs. femininity (MAS) -0.26 5.993 1.52 1320.63 0.064 Uncertaintyy avoidance (UAI) 41.23 45.444 1.43 1289.87 0.077 Long-time orientation (LTO) 42.91 42.117 -0.71 1287.87 0.762 Figure 3 The Extendedd UTAUT Moddel with Path Coefficients fo or Participantss with STEM vvs. non-STEM M Proofessions Summary of Results andd Discussion Generic reesults. This study validated UTAUT andd the correspon nding measureement instrumment for Turkiish language aand culture, pproving thus eevidence of thhe applicabilityy of educationnal technologyy acceptance as conceptualized by Venkaatesh and collea agues (2003, 22012). Thus, thhe applicabilityy of UTAUT wwas extended too a new culturaal context. Alsso, UTAUT waas extended froom the Inform mation Systems domain, wher re it was initiallly developed to Educational l Sciences. Applying this t to the Turkkish sample off educational teechnology user rs reveals a collective accepttance profile thhat differs fromm similar findi ings in other European E counntries (Nistor eet al., in press) ). Turkish userrs of educationnal technologyy displayed subbstantially highher scores in booth performanc ce and effort exxpectancy, and d lower scores in perceived ffacilitating con nditions. While e they evaluatted the own coomputer literaccy at similar leevels as German and Romannian users, thei ir computer liteeracy was the mmain determinnant of the use bbehavior. Thiss profile suggessts a very stroong correlationn between tecchnology use, computer literracy and expeectations, in thhe sense that an intensive uuse of educatiional technoloogies is associiated with hig gher computerr literacy (proobably based oon experientiaal and self-direected learning), , and with (proobably knowledge-based) higgher expectatioons of increasinng performanc ce and reducinng effort (Çağl lar & Demirokk, 2010). Furth her, this suggeests a clear sepparation between intensive aand occasionall technology users. u Another pervasive finding is the veery weak or hardly significaant effect of uuse intention oon use behavioor. At first sigght, this contraadicts the theoory of reasoned d action/planned behavior (AAjzen & Fishbbein, 2000). At A a closer loook, however, th his can be expplained by thee high degree of technologyy diffusion, which leaves littlee degrees of freeedom in participants’ choicee of educationa al technology vvs. previous le earning forms, and practicallyy leads in manyy cases to forceed use of technnology (Liu, 20012). From the cultural c point oof view (Hofsttede, 2001), thhe study at hannd reveals Turkkish culture ass associated wiith very low power p distancee, high individu ualism, very loow masculinityy, moderate unncertainty avoiidance and lonng term orienntation. These findings disp play large differences to HHofstede’s meeasurements aand estimationns, suggesting cultural chang ges occurred in n recent years. Also, unexpe ectedly low vaalues of culturaal masculinity in this study, , corroborated d with negatiive values repported by Niistor et al. (iin press) sugggest a possibble reconceptuualisation of cultural masculin nity. Copyright © Th he Turkish Onlinne Journal of Ed ducational Technnology
TOJET: The Turkish Online Journal of Educational Technology – October 2012, volume 11 Issue 4 Influence of regional culture. In this case, Hofstede’s (2001) model of cultural values in connection with the newly developed Welch-Lerche test revealed non-significant cultural differences between Istanbul area and other regions of Turkey. Comparing this result with significant cultural differences reported by Nistor et al. (in press) between Southern and Eastern Germany in the dimensions PDI, UAI and LTO support the interpretation of a culturally homogeneous sample, which contradicts the hypothesis of east-west differences within Turkey. However, there were significant differences in the regional acceptance profiles, i.e. higher scores of performance expectancy and educational technology usage, and lower scores of computer anxiety. The differences in regional acceptance profiles may be then interpreted as caused by differences in technological and educational infrastructure, in the sense that these are better available in the capital than in other regions. Influence of professional culture. The comparative examination of cultural and acceptance profiles of STEM vs. non-STEM professionals revealed clear differences that support the view of STEM and non-STEM as two different cultures. From cultural perspective, STEM participants appear as more democratic (lower PDI scores), more oriented to feminine cultural values (such as more caring and making less difference between gender roles, which is reflected in lower MAS scores), and tendentially less uncertainty avoidant (lower UAI scores, however the Welch-Lerche test with p < 0.077 was tightly above the statistical significance threshold). The differences in PDI and UAI are consistent with those reported by Nistor et al. (in press). However, lower MAS for STEM professionals differs from the same findings. From ETA perspective, STEM professionals score higher in performance expectancy and use behavior, somewhat higher, however not statistically significant, in effort expectancy, and lower in computer anxiety. These findings are consistent with the differences in requirements between professions, and with the findings of Venkatesh and colleagues (2003, 2012). However, according to Venkatesh and Zhang (2010), since STEM culture appears to be more feminine than the non-STEM culture, performance expectancy should be higher for non-STEM, and lower for STEM, which could not be reproduced in this study. As for the UTAUT path coefficients, effort expectancy has a somewhat stronger influence for non- STEM professions, which is similar to Nistor et al. (in press). As a further concordance, facilitating conditions have a stronger influence for non-STEM professions. Finally, the generally weak influence of use intention on behavior is somewhat stronger for non-STEM, which can be interpreted by educational technology diffusion being stronger in STEM than in non-STEM domains, which leves more degrees of freedom for non-STEM professionals in adopting or refusing technology according to their use intention. CONCLUSIONS Conclusions on ETA. This study confirms the wide applicability of the ETA concept, as conceptualized by Venkatesh and colleagues (2003, 2012) in UTAUT. The corresponding empirical findings appear robust and reproductible across cultures (Nistor et al., in press; Venkatesh & Zhang, 2010). Given the relative high complexity of UTAUT, a more in-depth discussion of the model would have to consider three different zones of the model: firstly the intention-behavior correlation; secondly the predictors of technology use intention, and thirdly the influence of facilitating conditions and anxiety on use behavior. With respect to the first zone, Bagozzi (2007, p. 245) describes the intention-behavior correlation as “probably the most uncritically accepted assumption in social science research in general and IS research in particular”. Nistor (under review) emphasizes that the majority of previous studies that include this correlation use the same data collection method for both variables, which is prone to statistical arterfacts likely to inflationate the strength of the correlation (Podsakoff, MacKenzie & Podsakoff, 2012). In this study, in spite of common methods, the correlation is extremely low, which calls for alternative explanations to Ajzen and Fishbein’s reasoned action and planned behavior, such as restrained degrees of freedom in media choice or participants’ insufficient information on performance and effort in technology use. Future research should clarify these open issues. The predictors of technology use intention are designated in previous research (e.g., Nistor et al., in press; Pynoo, Tondeur, Braak, Duyck, Sijnave & Duyck, 2012; Schaupp, Carter & McBride, 2010; Venkatesh et al., 2012) as the strongest predictors in the entire acceptance model. The study at hand shows a simple alternative in which computer literacy, previously considered to be merely a moderator variable of the UTAUT model, can gain weight, become the strongest predictor and throw the other predictors at the lower limit of significance. Finally, facilitating conditions embody a main acceptance predictor in this study as well as in previous studies. Venkatesh et al. (2003, 2012) understand this variable as including also computer anxiety. On the other hand, many authors (Beaudry & Pinsonneault, 2010; Conti-Ramsden et al., 2010; Nistor et al., in press) emphasize the meaning of computer anxiety for the adoption of educational technology. In order to enhance the explicative power of UTAUT, the authors of this study sustain the explicit representation of computer anxiety as a separate predictor. Its impact on educational technology usage is then expressed both in absolute values of the UTAUT variables and in the path coefficient leading from computer anxiety to use behavior. Copyright © The Turkish Online Journal of Educational Technology 404
Page 2 and 3:
THE TURKISH ONLINE JOURNAL OF EDUCA
Page 4 and 5:
Dear Colleagues, TOJET: The Turkish
Page 6 and 7:
TOJET: The Turkish Online Journal o
Page 8 and 9:
Page 10 and 11:
Page 12 and 13:
Page 14 and 15:
Page 16 and 17:
Page 18 and 19:
Page 20 and 21:
Page 22 and 23:
Page 24 and 25:
Page 26 and 27:
Page 28 and 29:
Page 30 and 31:
Annotation retrieval TOJET: The Tur
Page 32 and 33:
Page 34 and 35:
Page 36 and 37:
Page 38 and 39:
Page 40 and 41:
Page 42 and 43:
Page 44 and 45:
Page 46 and 47:
Page 48 and 49:
Page 50 and 51:
Page 52 and 53:
Page 54 and 55:
Page 56 and 57:
Page 58 and 59:
Page 60 and 61:
Page 62 and 63:
Page 64 and 65:
Page 66 and 67:
Page 68 and 69:
Page 70 and 71:
Page 72 and 73:
Page 74 and 75:
Page 76 and 77:
Page 78 and 79:
Page 80 and 81:
Page 82 and 83:
Page 84 and 85:
Page 86 and 87:
Page 88 and 89:
Page 90 and 91:
Page 92 and 93:
Page 94 and 95:
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
Stage 2 Process Stage 3 Output Stag
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
Page 114 and 115:
Learning effectiveness TOJET: The T
Page 116 and 117:
Page 118 and 119:
Appendix A: Questionnaire TOJET: Th
Page 120 and 121:
Page 122 and 123:
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
Page 134 and 135:
Page 136 and 137:
3 2.5 2 1.5 1 0.5 0 TOJET: The Turk
Page 138 and 139:
Page 140 and 141:
Page 142 and 143:
Page 144 and 145:
Page 146 and 147:
Page 148 and 149:
Page 150 and 151:
Page 152 and 153:
Page 154 and 155:
Page 156 and 157:
Page 158 and 159:
Page 160 and 161:
Page 162 and 163:
Page 164 and 165:
Page 166 and 167:
Page 168 and 169:
Page 170 and 171:
Page 172 and 173:
Page 174 and 175:
Page 176 and 177:
Page 178 and 179:
Page 180 and 181:
Computer Use Transformational Leade
Page 182 and 183:
Page 184 and 185:
Page 186 and 187:
Page 188 and 189:
Page 190 and 191:
Page 192 and 193:
Page 194 and 195:
Page 196 and 197:
Page 198 and 199:
Page 200 and 201:
Page 202 and 203:
Page 204 and 205:
Page 206 and 207:
Page 208 and 209:
Page 210 and 211:
Page 212 and 213:
Page 214 and 215:
Page 216 and 217:
Page 218 and 219:
Page 220 and 221:
Page 222 and 223:
Page 224 and 225:
Page 226 and 227:
Diverger TOJET: The Turkish Online
Page 228 and 229:
Page 230 and 231:
Page 232 and 233:
Page 234 and 235:
Page 236 and 237:
Page 238 and 239:
Page 240 and 241:
Page 242 and 243:
Page 244 and 245:
Page 246 and 247:
Page 248 and 249:
clarify their misconceptions. TOJET
Page 250 and 251:
Page 252 and 253:
Page 254 and 255:
Page 256 and 257:
Page 258 and 259:
Page 260 and 261:
Page 262 and 263:
*p < .05 TOJET: The Turkish Online
Page 264 and 265:
Page 266 and 267:
Page 268 and 269:
Page 270 and 271:
Page 272 and 273:
Page 274 and 275:
Page 276 and 277:
Page 278 and 279:
Page 280 and 281:
Page 282 and 283:
Page 284 and 285:
Page 286 and 287:
Page 288 and 289:
Page 290 and 291:
Page 292 and 293:
Page 294 and 295:
Page 296 and 297:
Page 298 and 299:
Page 300 and 301:
section to the user. TOJET: The Tur
Page 302 and 303:
Page 304 and 305:
Page 306 and 307:
Page 308 and 309:
Page 310 and 311:
Page 312 and 313:
Page 314 and 315:
Page 316 and 317:
Page 318 and 319:
Page 320 and 321:
Page 322 and 323:
Page 324 and 325:
Page 326 and 327:
Page 328 and 329:
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
Page 336 and 337:
Page 338 and 339:
Page 340 and 341:
Page 342 and 343:
Page 344 and 345:
Page 346 and 347:
Page 348 and 349:
Page 350 and 351:
Page 352 and 353:
Page 354 and 355:
Page 356 and 357:
Page 358 and 359:
Page 360 and 361:
Page 362 and 363:
Page 364 and 365: TOJET: The Turkish Online Journal o
Page 370 and 371: Statement Analysis TOJET: The Turki
Page 388 and 389: Appendices TOJET: The Turkish Onlin
Page 412 and 413: TOJEET: The Turkish Online Journal
Page 426 and 427: eactions TOJET: The Turkish Online
Page 464 and 465:
Page 466 and 467:
Page 468 and 469:
Page 470:
show all

october 2012 - TOJET the Turkish online journal of educational ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?