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

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Analysis of Response Statements An analysis was conducted to analyze participants’ response statements to the agent prompts both qualitatively and quantitatively. The qualitative content of the response statements was examined and quantified to find out at which levels of reflection have occurred in participants’ response statements. In the following subsections, we describe the coding scheme of measuring respoinse statements, the coding process and inter-rater-reliability. Coding Scheme of Measuring Response Statements A tripartite coding scheme, adapted by Ortiz (2006) from the categorization scheme proposed by Surbeck, Han, & Moyer (1991), was adopted to analyze the participant’ response statements to the agent prompts. This scheme, which includes categories of reaction, elaboration, and contemplation, adopts the perspective that the nature of the stimulus to reflect will impact the quality of reflection (Moore & Whitfield, 2008), which conforms to what this study seeks to investigate. In Table 2, the categories of response statements used in this study, tailored from the categorization scheme mentioned above, are provided for comparison and to illustrate and judge participants’ elicited levels of reflection revealed in the learning-by-teaching process. Categories Description Table 2. Categories of Response Statements Sample Response statements Reaction/ Reactive The entry reports facts, feelings, concern of [Respond to how to evaluate the performance Statements an opinion. Course issues or concepts may of the agent tutee] “Good that you got the be referred with no development or answer right, but your explanation isn’t very elaboration. good. ” – Reaction: Report feelings Elaboration/ The entry expands upon descriptive [Respond to the quest to make explanations to Elaborative information by explaining feelings, or the agent tutee] Statements giving illustrate example of course “Economics fundamentally reflects on supply concepts. The work uses interpretation of and demand. Supply is market can offer. It course concepts refers to producer supplying of goods.” – Elaboration: Interpret course concepts Contemplation/ The entry reference assumption about one’s [Respond to why to teach the agent tutee] Contemplative self or one’s behaviour, indicating a shift in “To emphasize the importance of prior Statements thought or attitude about one’s self. knowledge to succeed in future business” – Contemplation: Indicate a shift in attitude about oneself Other Statements which are irrelevant or off-topic [Respond to what is the most thing trying to teach the agent tutee] “Music Player. Old and new modern” Coding Process and Inter-Rater Reliability Two raters were involved in the coding process. To begin, the first rater analyzed a sample of ten response statements to become confident with the coding scheme. Then, the first rater explained the coding scheme, as shown in Table 2, to the second rater. The second rater then analyzed the first ten response statements as well. The consensus was achieved between the two raters to differentiate among the three categories: reaction, elaboration and contemplation. After that, the two raters analyzed the remaining response statements independently. Cohen’s kappa was used to estimate the level of agreement between the two raters, taking the agreement occurring by chance into account. Calculated with Kohen’s Kappa, agreement between the two raters appeared to be good, κ = 0.653 (A Cohen’s kappa value between 0-0.4 is considered poor, 0.4-0.6 fair, 0.6-0.75 good, and 0.75 outstanding.). 345
Results Learning Outcomes Pre- and Post- Test Scores Figure 4 shows the result of pre- and posttest scores. A one-way analysis of variance (ANOVA) result indicated that the three conditions had no significant difference as to students’ prior knowledge when almost all students are domain novices and achieve low scores in the pretest (F (2, 26) = .219, p = .805). However, when we look at posttest gains, all the three conditions showed statistical significant increase after the treatment (F (2, 26) = 3.50, p = .045). Figure 4. Pre- and Post- Test Scores Figure 5. Performance of Student Map in Main Study 346
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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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future. Therefore, they had an oppo
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surprising that most interaction wa
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Pawan, F., Paulus, T. M., Yalcin, S
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systems by using 18 personalization
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Short-Term Sensory Memory is a temp
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with respect to articles by using a
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system also computes a review value
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DFL. d ( yi ) is the degree of mem
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the experimental group can understa
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Finally, Figure 10(A) and Figure 10
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Appendix # Question Description Par
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mental models, are cognitive struct
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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: All the three groups completed the
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.
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