October 2007 Volume 10 Number 4 - Educational Technology ...

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Table 4. Summary of MANOVA Results Condition Beliefs Resources High practice Low practice Attitude F E.S. F E.S. F E.S. F E.S. F E.S. Main effect Stages 11.86 *** 0.29 1.76 0.11 4.29 ** 0.17 6.51 *** 0.21 6.00 *** 0.20 Post Hoc (1
Regression models indicating relationships The questions in the third section of the questionnaire were grouped by dependent variable (high- and lowinteraction practices) and independent variable (beliefs, attitudes, and resources). The means of the responses were then used to represent each variable, since this is one of the most-used parameters to represent a group of values (Moore & Benbasat, 1991; Holcombe, 2000). After calculating these means, an analysis of the correlation between variables was done. As we can see in Table 6, there were significant correlations among teachers’ beliefs, attitude toward computers, available resources, and teaching practices (including high- and low- interaction practices). Beliefs show the greatest correlation with the dependent variables (high- and low-interaction practices); therefore beliefs will have a greater impact in the regression models. Table 6. Correlation Matrix for the Five Teacher Factors (N = 613) Pearson Correlation Beliefs H-Practice L- Practice Attitude Resources Beliefs 1 H-Practice 0.31** 1 L- Practice 0.48** 0.44** 1 Attitude 0.33** 0.09* 0.32** 1 Resources 0.27** 0.21** 0.16** 0.05 1 **Correlation is significant at the 0.01 level (2-tailed). *Correlation is significant at the 0.05 level (2-tailed). As we can see in Table 7, these coefficients of the multiple linear regressions were grouped into two categories: (1) the dependent variable is high-interaction practices; (2) the dependent variable is low-interaction practices. In each category six regression models, including one group with all the subjects and five groups with the subjects distributed into five stages, were calculated in order to compare the different contributions of variables (beliefs, attitudes toward computers, and available resources). Teachers’ beliefs and available resources turned out to be the major predictors of their high-interaction practices. Besides, all of the t values reached a significant level (0.05), which means that independent variables (beliefs and available resources) contributed significantly to the prediction of the dependent variable (high-interaction practices). The same procedure was used to analyze the subjects in the five stages of computer-based instructional evolution. As we can see in Table 7, beliefs are the greatest predictor of high-interaction practices except at the “entry” stage; here teachers’ beliefs and available resources are the best predictors of this variable. By contrast, beliefs and attitudes contribute significantly to the prediction of low-interaction practices. As we can see, beliefs are the greatest predictor for these practices except at the “adaptation” stage. In this stage, teachers’ beliefs and attitudes best predict that teachers will engage in low-interaction activities when they integrate computerbased technology into their classrooms. In conclusion, teachers’ beliefs are the most reliable predictors of their computer-based instructional practices. Similar findings can be found in many studies (Czerniak & Lumpe, 1996; Niederhauser & Stoddart, 2001; Ruthven, et al., 2004; Sandholtz, Ringstaff & Dwyer, 1996 ). Total (N=613) Entry (N=89) Table 7. Summary of Regression Models High-Interaction Practice Variables Beta S.E. t (p) R Constant 0.63 0.26 2.41(.016) Beliefs 0.47 0.07 6.97(.000) .34 Resources 0.18 0.05 3.37(.001) Constant 0.29 0.56 0.51(.061) Resources 0.34 0.14 2.50(.015) .44 Beliefs 0.39 0.18 2.19(.031) Constant Beliefs 1.82 0.29 0.51 0.14 3.55(.001) 2.04(.043) .17 Constant Beliefs 1.41 0.39 0.42 0.11 3.33(.001) 3.49(.001) .23 Constant Beliefs 0.31 0.73 0.61 0.16 0.50(.615) 4.71(.000) .41 Adoption (N=141) Adaptation (N=229) Appropriation (N=111) Invention Constant 0.21 1.09 0.19(.850) .42 126
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October 2007 Volume 10 Number 4
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Abstracting and Indexing Educationa
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The Relationship of Kolb Learning S
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a question about learning together
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affordances of networked learning s
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included a unit on collaborative le
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on at different times and work indi
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• the numerous evaluation studies
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wanted to work. The same inquiry pr
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usability studies have a place in t
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Milrad, M., & Jackskon, M. (2007).
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information- and communication tech
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Interactive Examination, the studen
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Table 1. Criteria for grading OD st
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content. Differences in the attitud
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Even though further research on the
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Olofsson, A. D. (2007). Participati
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Etzioni (1993) points out that an i
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programme. They are rather construc
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to be that each individual trainee
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Bernmark-Ottosson, A. (2005). Demok
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The Knowledge Foundation (2005). IT
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Figure 1. Design Theories in contex
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attention as we frequently discuss
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Blog Reflection This design concept
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Narrative Structure (Form) Content
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Löwgren, J., & Stolterman, E. (200
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critique, neither do the single ind
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suggested by Ljungberg (1999b) we c
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the del.icio.us site (see figure 3)
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Device cultures It is not only the
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uilt using a camera-equipped PDA ru
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Jones, C., Dirckinck-Holmfeld, L.,
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Milrad, M., & Spikol, D. (2007). An
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components to be able to deal with
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compulsory throughout the project.
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only with their existing day-today
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As our work continues, we will try
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cognition as well as self-regulated
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Page 85 and 86: Al-A'ali, M. (2007). Implementation
Page 87 and 88: complex cognitive skills involve em
Page 89 and 90: Table 1. CAT and a linear mathemati
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Page 93 and 94: Figure 7. Our newly added factors i
Page 95 and 96: question factors according to IRT;
Page 97 and 98: Instructure 1 Login User-ID Passwor
Page 99 and 100: Shute, V., & Towle, B. (2003). Adap
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Page 109 and 110: in the course. A randomized block d
Page 111 and 112: To test whether ET can effectively
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Page 115 and 116: Fleischmann, K. R. (2007). Standard
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Page 139 and 140: Procedure Content analysis procedur
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Page 149 and 150: Investigating the problem An extens
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The Text Editor allows the editing
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Mathematical content and structure
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Consolidation exercises Solution co
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As to course components, the activi
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handle more formal representations
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Lagrange, J. B., Artigue, M., Labor
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processed information was classifie
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Method Participants The participant
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Table 5. Learning outcomes of diffe
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peers and benefited most from discu
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Kayes, D.C. (2005). Internal validi
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This paper considers the potential
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The first assumption ensures that c
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allowed to rise when external fundi
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The second option, lowering the cos
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Downes, S. (2003). Design and Reusa
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Appendix A. Good-enough approaches
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Rapid Prototyping and Design Based
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Initial Design Because the field-ba
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• reducing the number of required
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that they felt this hindrance; I fe
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goals” (Edelson, 2002, p. 114) wa
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more and more from the periphery of
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Edelson, M. (1988). The hermeneutic
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Wang, H.-Y., & Chen, S. M. (2007).
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If the universe of discourse U is a
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we can see that S( X ) − S( Y ) S
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Example 1: Let Ã and B ~ be two va
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columns shown in Table 2, where 1
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(3) Find the maximum value among th
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By applying Eq. (7), we can get the
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Q.2 carries 25 marks, Q.3 carries 2
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the proposed methods can evaluate s
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Gogoulou, A., Gouli, E., Grigoriado
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enabling learner (subject) to work
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• Self-, Peer- and Collaborative-
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(iii) Regulates the communication:
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Figure 3. A screen shot of the SCAL
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2 nd study: Thirty-five students pa
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them characterized it as time and e
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Soller, A. (2001). Supporting Socia
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making reference to the others wher
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Solution 2.2: Deliberately select h
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just near a deadline, when it may b
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assessed on an individual basis. Wi
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- and even appreciated - by student
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Panitz, T., & Panitz, P. (1998). En
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Concept Mapping Concept mapping by
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Research Questions In order to dete
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with their teacher but rather than
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Tukey’s HSD post hoc test reveale
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collaboratively during study time?
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Jegede, O.J., Alaiyemola, F.F., & O
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esources. The use of synchronous te
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The use of digital communication mo
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contributed more information and en
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3. Use the second screen for the le
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• Use drawing to develop writing
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student and teacher on the synchron
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Vogel, J. J., Vogel, D. S., Cannon-
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Cases The first set of ten case stu
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Kılıçkaya, F. (2007). Website re
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