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

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Figure 5. The screenshot of understanding the question by animation guidance Figure 6. The screenshot of listing the equation Figure 7. The screenshot of listing the equation by animation guidance 253
Research Method Figure 8. The screenshot of double checking The participants in this study were selected from six classes of second and third grades in two elementary schools in Yilan County, Taiwan. The selection criteria were listed as follows: (1) Children with low mathematics achievement were identified by the class advisor that they had basic learning ability, need remedial instruction and had the average scores in mathematics posterior 25% of their class in the first monthly exam. (2) The class advisor consulted to the parents to find out the children who were willing to take the project as the experimental group. For the students in experimental group trained by the computer-assisted mathematic-problem-solving system after school, there were seventeen second graders and third graders with low-achieving selected by above two criteria. Eleven students with low-achieving in mathematics that parents couldn’t send and pick up were the control group. To test the discrimination and difficulty of the test questions, a pilot study was held between first monthly exam and second monthly exam of the first semester in academic year for the students from nine classes of second and third grades in two elementary schools in Yilan County, Taiwan. The test problems were divided into two examination papers, A and B. Both papers were designed for the students of second and third grades respectively. The difference between these two papers was the number magnitude. Most of the number used in the paper for the third grade was three figures; however, the number used in the paper for the second grade was double figures. After finishing the test, we combined the papers of the second and third grades to analyze of split-half reliability, discrimination and difficulty. Since the aim of this study was the remedial instruction of children with low mathematics achievement, the test questions were made based on the examination paper for the second grade (i.e., the number was double figures). This study employed independent-sample dual-factor covariance analysis. The dependent variable was the posttest score, the independent variables included the group and grade, and the control variable (covariance) was the pretest score. Exploration was first conducted to see if interaction was present between the group and the grade, and then to see if significant discrepancy was present between different factors in terms of mathematicalproblem-solving ability enhancement after conclusion of the experiment. Through independent-sample dualfactor covariance analysis, this study then looked into the presence of interaction between the group and the grade. It explored the impact of different factors on learning achievement of the computer-assisted mathematicproblem-solving system and determines whether significant discrepancy in learning achievement was present before and after the experiment in order to clarify whether the computer-assisted mathematic-problem-solving system could serve as an effective tool for remedial education. Answers given by students to the “Computer- Assisted Mathematic-Problem-Solving System Questionnaire” were analysed in terms of percentage for understanding of students’ opinion of the computer-assisted mathematics-problem-solving system. 254
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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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Page 217 and 218: Several studies explore the roles t
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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
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Page 239 and 240: Scale Questionnaire item Mean S.D.
Page 241 and 242: Hwang, G. J. (2003). A conceptual m
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Page 245 and 246: Virtual learning environment In the
Page 247 and 248: Class Table 1. The survey questions
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Page 253 and 254: Huang, T.-H., Liu, Y.-C., & Chang,
Page 255 and 256: y personalised context examples in
Page 257: Students’ Problem-Solving Guidanc
Page 261 and 262: Table 4. Abstract of Pairwise Compa
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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
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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
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Page 285 and 286: system also computes a review value
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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
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Page 303 and 304: Hsu, I.-C. (2012). Intelligent Disc
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Page 307 and 308: RLO denotes a remote learning objec
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Figure 2. The flow-oriented LOFinde
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if x include with y, and y include
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Similarly, the relation metadata of
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(defrule student-advisor (triple (p
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References ADL. (2006). Sharable Co
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determinants of how people think, b
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Mediating effect of learning flow A
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The instrument used to measure lear
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addition, the cross-loadings of the
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and ease of use had significant eff
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Connell, J. P., Spencer, M. B., & A
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Despotović-Zrakić, M., Marković,
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Learning is a cognitive activity th
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The survey consisted of 30 question
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Created data mining model needs to
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dealt with the matter taught at the
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Conclusion Conducted research showe
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Romero, C., Ventura S., García E.,
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prompts as scaffolding strategy to
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Reflection Types This study attempt
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All the three groups completed the
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Results Learning Outcomes Pre- and
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Map Analysis in Transfer Test Figur
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Generic Prompts and Specific Prompt
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Biswas, G., Schwartz, D., Bransford
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Chen, Y.-H., Looi, C.-K., Lin, C.-P
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of correct response, answer until c
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Figure 7 shows a screenshot of one
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Collaboration Questionnaire results
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following diagrams. The double-arro
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“Most students were encouraged to
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Bangert-Drowns, R.L., Kulick, C. C.
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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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