January 2012 Volume 15 Number 1 - Educational Technology ...

More documents

Recommendations

Info

interaction, and the number of management type of interaction were the indicator variables. The age variable was controlled in the associations of interaction with emotional intelligence. The gender variable was controlled in the associations of emotional intelligence with social bond and interaction. Results The participant ages ranged from 24 to 63 (M=40.5 SD=10). The majority of the participants were female (74%), native English speakers (92%), and Caucasian (87%). The participants represent the population in the program because the population was also primarily female (67.5%), Caucasian (74.8%), and their ages ranged from 22 to 63 (M=38.33 SD=9.12). Relationship between emotionalintelligence and interaction The results showed a negative relationship between emotional intelligence and the amount of interaction in synchronous interaction. Among the variables, students’ ability to perceive emotion by facial expression and the number of text and audio messages in synchronous interaction were found to be contributing variables in the negative association. No relationship was found in asynchronous interactions. The results showed no significant canonical correlation between students’ emotional intelligence and types of interactions both in synchronous and asynchronous online learning environment. After examining the Pearson partial correlation, canonical correlation analysis was conducted to further examine the relationship between the two sets of research variables. Two indicator variables in the managing emotion branch were excluded in the canonical correlation analysis because they do not have Pearson partial correlation with any interaction variables, which may weaken the canonical correlation between the latent variables. As shown in Table 1, the first canonical correlation between emotional intelligence and the amount of messages in synchronous interaction was found to be statistically significant (r=.506, p=.048, α=.05). The squared canonical correlation for the first dimension was .256, which represents the amount of shared variance between the amount of interaction canonical variable and the emotional intelligence canonical variable. # Canonical Correlation Table 1. Canonical Partial Correlations between EI and the Amount of Interaction Squared Canonical (R 2 ) Eigenvalues of Inv(E)*H = CanRsq/(1-CanRsq) Test of H0 Eigenvalue Cumulative F DF 1 DF 2 Sig. 1 .506 .256 .335 .602 1.54 24 238.43 .048* 2 .354 .126 .144 .853 1.04 15 190.88 .419 3 .251 .063 .067 .970 .73 8 140.00 .662 4 .129 .067 .017 1.000 .40 3 71.00 .753 Note. Significance level *p
that its value of cross-loading is .339. This result is consistent in the squaring of multiple correlations. The squared multiple correlations show that the first canonical variable of the amount of interaction has some predictive power for the number of messages in the synchronous text interaction (.101) and the number of messages in the synchronous audio interaction (.115). Table 2. Relative Importance of Variables for the First Canonical Correlation between EI and the Amount of Interaction Variate/ Canonical Canonical Cross- Squared Multiple Redundancy Variables Weights Loading Correlations Index Dependent .068 MT 1.333 .318 .101 WT -.957 .093 .009 MA .581 .339 .115 WA -.119 .215 .046 Independent .044 EI-A -.964 -.410 .168 EI-E .453 .004 .000 EI-B .164 -.080 .006 EI-F -.258 -.272 .074 EI-C -.212 -.092 .008 EI-G .401 .082 .007 Relationship between social bond and interaction The results showed a positive relationship between students’ social bond and the types of interaction in synchronous text interaction. This relationship was not found in asynchronous interactions and synchronous audio interaction. The results showed no significant canonical correlation between students’ social bond and the amount of interactions both in synchronous and asynchronous online learning environment. Table 3 displays the canonical partial correlations between the social bond variables and the types of interaction variables. The first canonical correlation between social bond and types of messages in synchronous text interaction was found to be statistically significant (r=.407, p=.037). The squared canonical correlation for the first dimension was .165. Table 3. Canonical Partial Correlations between Social Bond and the Types of Interaction # Canonical Squared Correlation Canonical (R 2 Eigenvalues of Inv(E)*H Test of H0 ) = CanRsq/(1-CanRsq) Eigenvalue Cumulative F DF 1 DF 2 Sig. 1 .407 .165 .198 .755 2.05 9 175.38 .037* 2 .241 .058 .061 .989 1.16 4 145.00 .331 3 .055 .003 .003 1.000 .22 1 70.00 .639 Note. Significance level *p
Page 1 and 2:
January 2012 Volume 15 Number 1
Page 3 and 4:
Supporting Organizations Centre for
Page 5 and 6:
Analyzing the Learning Process of a
Page 7 and 8:
Angeli, C., & Valanides, N. (2012).
Page 9 and 10:
ased on an integration and evaluati
Page 11 and 12:
ased on the assumption that no sing
Page 13 and 14:
Diagram type D thinking (shown in F
Page 15 and 16:
collaborative task in terms of inte
Page 17 and 18:
Table 4. Descriptive statistics for
Page 19 and 20:
Hong, N. S., Jonassen, D. H., & McG
Page 21 and 22:
commercial off-the-shelf digital ga
Page 23 and 24:
The post-questionnaire was used aft
Page 25 and 26:
Phase Table 1. Phases and activitie
Page 27 and 28:
Research results Describing student
Page 29 and 30:
Assessment results for each one of
Page 31 and 32:
References Annetta, L.A., Minogue,
Page 33 and 34:
Huang, T.-W. (2012). Aberrance Dete
Page 35 and 36: Detection power Typically, the rela
Page 37 and 38: Results Detection rates As seen in
Page 39 and 40: 2 .00 .05 3 .02 .10 1 .60 .40 ECI 4
Page 41 and 42: their easily understandable devices
Page 43 and 44: Ifenthaler, D. (2012). Determining
Page 45 and 46: activities is assumed to be reflect
Page 47 and 48: that the problem representations (i
Page 49 and 50: deductive reasoning inventory (33 m
Page 51 and 52: HIMATT structural measures The part
Page 53 and 54: outcomes, r = .297, p < .01. Accord
Page 55 and 56: Azevedo, R. (2009). Theoretical, co
Page 57 and 58: Seel, N. M. (1999b). Educational se
Page 59 and 60: Initially this paper explores defin
Page 61 and 62: gamers were boys, and 35% were girl
Page 63 and 64: Teachers underwent eight hours of p
Page 65 and 66: A correlation analysis was used to
Page 67 and 68: playing the game. This would mean P
Page 69 and 70: Yu, F. Y. (2012). Any Effects of Di
Page 71 and 72: Considering that identity concealme
Page 73 and 74: In the nickname group, the student
Page 75 and 76: Attitudes toward assessors Percepti
Page 77 and 78: Liu, Z. F., Chiu, C. H., Lin, S. S.
Page 79 and 80: Appendix A: Attitudes toward Peer-A
Page 81 and 82: Appendix C: Perception toward the I
Page 83 and 84: Han, H., & Johnson, S. D. (2012). R
Page 85: Research participants The target po
Page 89 and 90: The canonical variable for the emot
Page 91 and 92: Literature in the field of online l
Page 93 and 94: Cornelius, R. R. (1996). The scienc
Page 95 and 96: Shih, W.-C., Tseng, S.-S., Yang, C.
Page 97 and 98: To provide personalized (e-)learnin
Page 99 and 100: Figure 3. An illustrative example o
Page 101 and 102: elementary schools. Thus they are b
Page 103 and 104: Table 5. Descriptive statistics for
Page 105 and 106: References Abowd, G. D., & Atkeson,
Page 107 and 108: Tseng, K.-H., Chang, C.-C., Lou, S.
Page 109 and 110: Figure 1. The five stages of KT (Gi
Page 111 and 112: The use of learning strategies, mon
Page 113 and 114: Additionally, the above two scales
Page 115 and 116: Figure 3. Canonical structure betwe
Page 117 and 118: highly positive perception of CM an
Page 119 and 120: Langan-Fox, J., Platania-Phung, C.,
Page 121 and 122: Gömleksiz, M. N. (2012). Elementar
Page 123 and 124: any statistically significant diffe
Page 125 and 126: consideration in an educational set
Page 127 and 128: conditions of a learning environmen
Page 129 and 130: Kahle, J. B. (1983). The disadvanta
Page 131 and 132: Appendix A Science and Technology S
Page 133 and 134: (Guuawardena, Nola, Wilson, Lopez-I
Page 135 and 136: Questionnaire on student satisfacti
Page 137 and 138:
G4 53 (12.5) 48.9 (13.4) 0.39 G5 51
Page 139 and 140:
across the five levels of knowledge
Page 141 and 142:
Santhanam, R., Sasidharan, S., Webs
Page 143 and 144:
This paper reports only the early e
Page 145 and 146:
Figure 1 illustrates how the abovem
Page 147 and 148:
teacher/instructor continues to dom
Page 149 and 150:
The instructor plays a significant
Page 151 and 152:
Data collection and data sources Fi
Page 153 and 154:
y turning over the responsibility t
Page 155 and 156:
Brophy, J. (1999). Toward a model o
Page 157 and 158:
Lawanto, O., Santoso, H. B., & Liu,
Page 159 and 160:
such as grades and evaluation by ot
Page 161 and 162:
students’ interest, expectancy fo
Page 163 and 164:
constructs that measure students’
Page 165 and 166:
Bandura, A. (1978). Reflections on
Page 167 and 168:
Lin, J. M.-C., & Liu, S.-F. (2012).
Page 169 and 170:
Table 1. The MSWLogo commands learn
Page 171 and 172:
other words, we had prepared a set
Page 173 and 174:
lab. When she returned and found th
Page 175 and 176:
Attitudes toward Programming and Co
Page 177 and 178:
Table 5 successfully, it took four
Page 179 and 180:
Kuter, S., Altinay Gazi, Z., & Alti
Page 181 and 182:
not only the means for trainees’
Page 183 and 184:
Data Collection Techniques and Anal
Page 185 and 186:
organizations was highlighted by on
Page 187 and 188:
provides the means for professional
Page 189 and 190:
Kohonen, V. (2001). Towards experie
Page 191 and 192:
As Rogers (1995) postulates in his
Page 193 and 194:
Instrument and data collection Afte
Page 195 and 196:
“Raising our computer skills in C
Page 197 and 198:
teachers deploy ICT tools in langua
Page 199 and 200:
Ma, W., Anderson, R., & Streith, K.
Page 201 and 202:
APPENDIX A. Questionnaire for Dista
Page 203 and 204:
consistency with other ideas, and a
Page 205 and 206:
conceptions, justifying their belie
Page 207 and 208:
each group. The experimental group
Page 209 and 210:
specifically, instructional approac
Page 211 and 212:
Table 3 shows that the mean frequen
Page 213 and 214:
previous Web-based instructional le
Page 215 and 216:
Millar, R., & Osborne, J.F. (1998).
Page 217 and 218:
Several studies explore the roles t
Page 219 and 220:
understand the content structures o
Page 221 and 222:
teacher was not allowed to provide
Page 223 and 224:
two coding schemes, as illustrated
Page 225 and 226:
also very limited. Teachers and sof
Page 227 and 228:
learning activities. British Journa
Page 229 and 230:
2009; Bernard & Cathryn, 2006) or p
Page 231 and 232:
In this study, the focus of the ins
Page 233 and 234:
The student’s degree of mastery i
Page 235 and 236:
The questionnaire for the acceptanc
Page 237 and 238:
the t-test result, it is found that
Page 239 and 240:
Scale Questionnaire item Mean S.D.
Page 241 and 242:
Hwang, G. J. (2003). A conceptual m
Page 243 and 244:
sharing, problem solving, and achie
Page 245 and 246:
Virtual learning environment In the
Page 247 and 248:
Class Table 1. The survey questions
Page 249 and 250:
“…the distance and the lack of
Page 251 and 252:
collaboration within EVS, thus prev
Page 253 and 254:
Huang, T.-H., Liu, Y.-C., & Chang,
Page 255 and 256:
y personalised context examples in
Page 257 and 258:
Students’ Problem-Solving Guidanc
Page 259 and 260:
Research Method Figure 8. The scree
Page 261 and 262:
Table 4. Abstract of Pairwise Compa
Page 263 and 264:
questions designed for the system h
Page 265 and 266:
Lee, J. (2012). Patterns of Interac
Page 267 and 268:
This study focused on online fora i
Page 269 and 270:
Results and Discussion Due date-cen
Page 271 and 272:
In addition, all groups developed 8
Page 273 and 274:
future. Therefore, they had an oppo
Page 275 and 276:
surprising that most interaction wa
Page 277 and 278:
Pawan, F., Paulus, T. M., Yalcin, S
Page 279 and 280:
systems by using 18 personalization
Page 281 and 282:
Short-Term Sensory Memory is a temp
Page 283 and 284:
with respect to articles by using a
Page 285 and 286:
system also computes a review value
Page 287 and 288:
DFL. d ( yi ) is the degree of mem
Page 289 and 290:
the experimental group can understa
Page 291 and 292:
Finally, Figure 10(A) and Figure 10
Page 293 and 294:
Appendix # Question Description Par
Page 295 and 296:
mental models, are cognitive struct
Page 297 and 298:
Based on the theoretical implicatio
Page 299 and 300:
Data analysis To test the model fit
Page 301 and 302:
may be considered an effective inte
Page 303 and 304:
Hsu, I.-C. (2012). Intelligent Disc
Page 305 and 306:
(Gradinarova, Zhelezov et al. 2006)
Page 307 and 308:
RLO denotes a remote learning objec
Page 309 and 310:
Figure 2. The flow-oriented LOFinde
Page 311 and 312:
if x include with y, and y include
Page 313 and 314:
Similarly, the relation metadata of
Page 315 and 316:
(defrule student-advisor (triple (p
Page 317 and 318:
References ADL. (2006). Sharable Co
Page 319 and 320:
determinants of how people think, b
Page 321 and 322:
Mediating effect of learning flow A
Page 323 and 324:
The instrument used to measure lear
Page 325 and 326:
addition, the cross-loadings of the
Page 327 and 328:
and ease of use had significant eff
Page 329 and 330:
Connell, J. P., Spencer, M. B., & A
Page 331 and 332:
Despotović-Zrakić, M., Marković,
Page 333 and 334:
Learning is a cognitive activity th
Page 335 and 336:
The survey consisted of 30 question
Page 337 and 338:
Created data mining model needs to
Page 339 and 340:
dealt with the matter taught at the
Page 341 and 342:
Conclusion Conducted research showe
Page 343 and 344:
Romero, C., Ventura S., García E.,
Page 345 and 346:
prompts as scaffolding strategy to
Page 347 and 348:
Reflection Types This study attempt
Page 349 and 350:
All the three groups completed the
Page 351 and 352:
Results Learning Outcomes Pre- and
Page 353 and 354:
Map Analysis in Transfer Test Figur
Page 355 and 356:
Generic Prompts and Specific Prompt
Page 357 and 358:
Biswas, G., Schwartz, D., Bransford
Page 359 and 360:
Chen, Y.-H., Looi, C.-K., Lin, C.-P
Page 361 and 362:
of correct response, answer until c
Page 363 and 364:
Figure 7 shows a screenshot of one
Page 365 and 366:
Collaboration Questionnaire results
Page 367 and 368:
following diagrams. The double-arro
Page 369 and 370:
“Most students were encouraged to
Page 371 and 372:
Bangert-Drowns, R.L., Kulick, C. C.
Page 373 and 374:
primary research questions. First,
Page 375 and 376:
Individual learning Figure 2. Scree
Page 377 and 378:
Experimental Tools This study emplo
Page 379 and 380:
Table 3 shows that almost all items
Page 381 and 382:
I usually engaged myself in listeni
Page 383 and 384:
References Bloom, B. S. (Ed.). (195
Page 385 and 386:
APPENDIX 2. Taxonomy for Informatio
Page 387 and 388:
understand how we can effectively u
Page 389 and 390:
5. Is there a relationship between
Page 391 and 392:
correlation between teachers’ IWB
Page 393 and 394:
Q7. IWB provides advantages to me t
Page 395 and 396:
training regarding this topic. This
Page 397 and 398:
Conclusion This study provides a so
Page 399:
Smith, H. J., Higgins, S., Wall, K.
show all

January 2012 Volume 15 Number 1 - Educational Technology ...

Create successful ePaper yourself

Delete template?

Save as template?