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

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7. Perceived usefulness .46* .47* .50* .43* -.20* -.22* 1 8. Perceived ease of use .40* .43* .42* .40* -.<strong>15</strong>* -.20* .79* 1 9. Learning flow 1 .31* .32* .37* .28* -.16* -.18* .58* .48* 1 10. Learning flow 2 .30* .32* .31* .22* -.17* -.16* .47* .36* .73* 1 11. Achievement .21* .18* .28* .29* -.18* -.24* .28* .20* .28* .25* 1 M 4.02 3.75 4.10 4.10 2.56 2.64 3.87 3.81 3.88 3.80 33.75 SD .56 .54 .51 .50 .88 .88 .62 .65 .69 .71 10.<strong>15</strong> Skewness .03 .28 -.17 .08 .04 .03 -.13 .11 -.34 -.49 -.71 Kurtosis -.34 .30 .18 -.05 -.26 -.25 .01 -.51 .38 .25 3.34 n 248 248 248 248 248 248 248 248 248 248 248 *p
addition, the cross-loadings of the variables ranged from -.21 to .76, confirming that all constructs in the estimated model fulfilled the condition of convergent, as well as discriminant, validity. Therefore, the measurement model appeared to fit the data well and did not need to be changed. Structural model and hypothesis testing The proposed relationships were analyzed, as shown in Table 4, and the initial structural model provided a good fit to the data (e.g., TLI= 1.005; CFI= 1.000; RMSEA= .000(.000∼.038)). CMIN (χ 2 ) Table 4. Fit statistics for the structural model p df TLI CFI Structural model 26.51 .696 31 1.005 1.000 Note: n=248 RMSEA (90% confidence interval) .000 (.000~.038) In order to test the hypothesis, direct effects among self-efficacy, intrinsic value, test anxiety, perceived usefulness and ease of use, learning flow, and achievement were examined at the alpha level of .05, by reviewing the weights. First, the effects of self-efficacy, intrinsic value, and perceived usefulness and ease of use on learning flow were investigated. The effect of self-efficacy on learning flow was =.205 (t= 2.203, p
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January 2012 Volume 15 Number 1
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Supporting Organizations Centre for
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Analyzing the Learning Process of a
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Angeli, C., & Valanides, N. (2012).
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ased on an integration and evaluati
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ased on the assumption that no sing
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Diagram type D thinking (shown in F
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collaborative task in terms of inte
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Table 4. Descriptive statistics for
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Hong, N. S., Jonassen, D. H., & McG
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commercial off-the-shelf digital ga
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The post-questionnaire was used aft
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Phase Table 1. Phases and activitie
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Research results Describing student
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Assessment results for each one of
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References Annetta, L.A., Minogue,
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Huang, T.-W. (2012). Aberrance Dete
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Detection power Typically, the rela
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Results Detection rates As seen in
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2 .00 .05 3 .02 .10 1 .60 .40 ECI 4
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their easily understandable devices
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Ifenthaler, D. (2012). Determining
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activities is assumed to be reflect
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that the problem representations (i
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deductive reasoning inventory (33 m
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HIMATT structural measures The part
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outcomes, r = .297, p < .01. Accord
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Azevedo, R. (2009). Theoretical, co
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Seel, N. M. (1999b). Educational se
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Initially this paper explores defin
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gamers were boys, and 35% were girl
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Teachers underwent eight hours of p
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A correlation analysis was used to
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playing the game. This would mean P
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Yu, F. Y. (2012). Any Effects of Di
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Considering that identity concealme
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In the nickname group, the student
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Attitudes toward assessors Percepti
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Liu, Z. F., Chiu, C. H., Lin, S. S.
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Appendix A: Attitudes toward Peer-A
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Appendix C: Perception toward the I
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Han, H., & Johnson, S. D. (2012). R
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Research participants The target po
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that its value of cross-loading is
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The canonical variable for the emot
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Literature in the field of online l
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Cornelius, R. R. (1996). The scienc
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Shih, W.-C., Tseng, S.-S., Yang, C.
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To provide personalized (e-)learnin
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Figure 3. An illustrative example o
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elementary schools. Thus they are b
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Table 5. Descriptive statistics for
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References Abowd, G. D., & Atkeson,
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Tseng, K.-H., Chang, C.-C., Lou, S.
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Figure 1. The five stages of KT (Gi
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The use of learning strategies, mon
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Additionally, the above two scales
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Figure 3. Canonical structure betwe
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highly positive perception of CM an
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Langan-Fox, J., Platania-Phung, C.,
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Gömleksiz, M. N. (2012). Elementar
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any statistically significant diffe
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consideration in an educational set
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conditions of a learning environmen
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Kahle, J. B. (1983). The disadvanta
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Appendix A Science and Technology S
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(Guuawardena, Nola, Wilson, Lopez-I
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Questionnaire on student satisfacti
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G4 53 (12.5) 48.9 (13.4) 0.39 G5 51
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across the five levels of knowledge
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Santhanam, R., Sasidharan, S., Webs
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This paper reports only the early e
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Figure 1 illustrates how the abovem
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teacher/instructor continues to dom
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The instructor plays a significant
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Data collection and data sources Fi
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y turning over the responsibility t
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Brophy, J. (1999). Toward a model o
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Lawanto, O., Santoso, H. B., & Liu,
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such as grades and evaluation by ot
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students’ interest, expectancy fo
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constructs that measure students’
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Bandura, A. (1978). Reflections on
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Lin, J. M.-C., & Liu, S.-F. (2012).
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Table 1. The MSWLogo commands learn
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other words, we had prepared a set
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lab. When she returned and found th
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Attitudes toward Programming and Co
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Table 5 successfully, it took four
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Kuter, S., Altinay Gazi, Z., & Alti
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not only the means for trainees’
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Data Collection Techniques and Anal
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organizations was highlighted by on
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provides the means for professional
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Kohonen, V. (2001). Towards experie
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As Rogers (1995) postulates in his
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Instrument and data collection Afte
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“Raising our computer skills in C
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teachers deploy ICT tools in langua
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Ma, W., Anderson, R., & Streith, K.
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APPENDIX A. Questionnaire for Dista
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consistency with other ideas, and a
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conceptions, justifying their belie
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each group. The experimental group
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specifically, instructional approac
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Table 3 shows that the mean frequen
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previous Web-based instructional le
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Millar, R., & Osborne, J.F. (1998).
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Several studies explore the roles t
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understand the content structures o
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teacher was not allowed to provide
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two coding schemes, as illustrated
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also very limited. Teachers and sof
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learning activities. British Journa
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2009; Bernard & Cathryn, 2006) or p
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In this study, the focus of the ins
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The student’s degree of mastery i
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The questionnaire for the acceptanc
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the t-test result, it is found that
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Scale Questionnaire item Mean S.D.
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Hwang, G. J. (2003). A conceptual m
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sharing, problem solving, and achie
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Virtual learning environment In the
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Class Table 1. The survey questions
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“…the distance and the lack of
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collaboration within EVS, thus prev
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Huang, T.-H., Liu, Y.-C., & Chang,
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y personalised context examples in
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Students’ Problem-Solving Guidanc
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Research Method Figure 8. The scree
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Table 4. Abstract of Pairwise Compa
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questions designed for the system h
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Lee, J. (2012). Patterns of Interac
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This study focused on online fora i
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Results and Discussion Due date-cen
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In addition, all groups developed 8
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Page 279 and 280: systems by using 18 personalization
Page 281 and 282: Short-Term Sensory Memory is a temp
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Page 285 and 286: system also computes a review value
Page 287 and 288: DFL. d ( yi ) is the degree of mem
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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
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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
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Page 307 and 308: RLO denotes a remote learning objec
Page 309 and 310: Figure 2. The flow-oriented LOFinde
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Page 313 and 314: Similarly, the relation metadata of
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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: The instrument used to measure lear
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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
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Page 345 and 346: prompts as scaffolding strategy to
Page 347 and 348: Reflection Types This study attempt
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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,
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Individual learning Figure 2. Scree
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Experimental Tools This study emplo
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Table 3 shows that almost all items
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I usually engaged myself in listeni
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References Bloom, B. S. (Ed.). (195
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APPENDIX 2. Taxonomy for Informatio
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understand how we can effectively u
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5. Is there a relationship between
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correlation between teachers’ IWB
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Q7. IWB provides advantages to me t
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training regarding this topic. This
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Conclusion This study provides a so
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Smith, H. J., Higgins, S., Wall, K.
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January 2012 Volume 15 Number 1 - Educational Technology ...

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