April 2012 Volume 15 Number 2 - Educational Technology & Society

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content, (4) to observe peer’s comments and reflection contents, and (5) to revise original reflection contents. Here, a screen snapshot of the learning system is shown in Figure 4. Figure 4. A screen snapshot of the learning system Regarding how to effectively facilitate the learning activity with the proposed system, all participants were actively engaged in reflecting the local traffic problems. Besides, they could utilize MTVRS’ four main different functions: accessing, discovering, discussing, and sharing to assist individuals to promote, facilitate, and enhance collaboration and interaction in relevant traffic violations issues through mobile communication technologies for synchronization. On the other hand, the learners could also review comments and photographs posted on a PC through the web page to share peer’s reflection contents synchronously. In fact, these learning activities could be seen as social collaborative learning. Providing individual’s reflection contents and sharing their comments with peers could help learners improve their critical thinking abilities. Besides, the instructor also participated in these learning activities to enhance the learning process. According to the concept of cognitive conflict (Piaget, 1970), learners will try to revise their original reflection content to a higher level to avoid the unbalancing effect if they review others’ high-quality reflection content. Moreover, when a high-quality reflection content is posted by a learner, the instructor will also give positive reinforcement to the learner and guide other learners to look at this particular content. Instruments Usefulness of mobile learning systems The usefulness of mobile learning systems (UMLS), a questionnaire adapted by Motiwalla (2007) and then Uzunboylu et al. (2009) was added to for use in measuring learners’ satisfaction with ML systems. The questionnaire mainly addresses three dimensions: asynchronous communication, synchronous communication, and mobile communication. The present study thus adapted this 23-item questionnaire (see Table 2), focusing on the usefulness of mobile devices for examining the effect of mobile learning systems (MLS) on traffic violations in an ML environment to collect data. For this measure, each item was evaluated on a five-point Likert scale (one is strongly disagree and five is strongly agree). Reflection levels Bain et al. (1999) classified reflection into five different levels: reporting, responding, relating, reasoning, and reconstructing, according to learners’ reflection content. However, in fact, the reflection content from learners was 185
too simple, incomplete, or they even misunderstood the questions. Therefore, the questionnaire could not satisfy the lowest level of reporting. To avoid this situation, this study adopted the modified evaluation criteria by Chen et al. (2009) to score the group’s reflection content of traffic violations article from each learning group (see Appendix 1). Procedures The designed learning activity was deployed for about four weeks including pretest stage, reflective learning activity and evaluation stage. Figure 5 shows the procedure of the experiment. In the first stage, the teacher introduced the learning activity and instructed the use of the proposed system which includes the idea of how to achieve reflective learning in the mobile setting. In this stage, a pre-test was administered to evaluate the initial reflection level of each group. In the second stage, according to the design of the learning activity mentioned above, the learners collaborated to complete the learning activity and contributed the reflection content and comments for the learning topic. After conducting the learning activities, the learners were asked to take a questionnaire regarding the usefulness of the proposed system and a post-test in the third stage. Further, all the learners in each group were interviewed to obtain their opinions about the present study. Results First stage (Pre-test) Second stage (Reflective learning activities with the proposed system) Third stage (Questionnaire and Post-test) Introduce the learning activity Grouping Read a traffic violation article Post group co-reflection contents Learners use Smart Phone to transmit photos of local traffic problems Accessing Discussing Discovering Sharing Read a traffic violation article Post group co-reflection contents Questionnaire and Interview Figure 5. Experimental procedure 100 minutes 4 weeks <strong>15</strong>0 minutes This section discusses results concerning: the UMLS questionnaire survey of ML activities based on different gender and age level, and the traffic violation reflection levels of the ML activities based on different groups. Effects of mobile learning on traffic violations To examine the effects of ML on traffic violations after using the proposed ML environment, SPSS statistic software was used to analyze the results of the UMLS questionnaire. After the learners completed the survey, the reliabilities 186
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April 2012 Volume 15 Number 2
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Supporting Organizations Centre for
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Contextualizing a MALL: Practice De
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Kop, R. (2012). The Unexpected Conn
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Human mediation and information flo
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elevant information based on some k
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of learners. A search facilitated t
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information as human mediation mean
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Blau, I., & Barak, A. (2012). How D
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examined whether the readiness to p
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Table 5 presents the ANOVA for the
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However, in discussing a non-sensit
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deviations showed smaller variance,
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actual participation discussing sen
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Mesch, G., & Elgali, Z. (2009). Soc
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Although prior research on overall
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with a score of 39 and below as “
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Table 2 demonstrates mean scores an
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Discussion Although the recent Inte
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Furthermore, the most preferred pla
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MEB. (2009). Internete erisim proje
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Learning Management Systems (LMS) b
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practice and repetition with feedba
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Online peer assessment Peer assessm
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At an international conference on m
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� Ability to produce rich assessm
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Meishar-Tal, H., & Tal-Elhasid, E.
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Tsai, S. C. (2012). Integration of
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order to decrease text complexity a
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matter how the learners’ aptitude
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If compared by programs, WP student
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mean F2F 4.64 4.52 4.35 4.44 *: p
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een analyzed and were compared with
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Chen, G.-D., Lee, J.-H., Wang, C.-Y
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and diverse cognitional and emotion
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Encourage and persuade students wit
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Materials and procedure Each studen
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The lower part of Figure 4 shows st
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Mayer, R. E., Sobko, K., & Mautone,
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that an item is answered correctly
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Table 1. Relative concepts frequenc
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The Account Management Module provi
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Experiment 1 and results Figure 7.
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Utilization of Test Item 36 33 30 2
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Utilization of Test Item 36 33 30 2
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0.065 0.877 (17.56) 0.938 (22.55) 0
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Hwang, G.J., Hsiao, C.L., & Tseng,
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the diverse needs of modern industr
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Figure 1. The framework of interdis
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Research Design Figure 3. Recommend
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friendly. 8. I feel the layout and
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satisfaction, and system acceptance
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Ozok, A. A., Fan, Q., & Norcio, A.
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than students in a conventional cla
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shown in Figure 2 to include the st
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(1996) Pleasure-Arousal-Dominance (
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Based on this connection, we consid
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Final dominance measurements were p
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student mood and thereby allow comp
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Sessink, O., Beeftink, H., Tramper,
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The rationale behind the video form
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usefulness of the movies and their
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case of the first two questions and
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this paper in order to evaluate the
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The survey questions Appendix A In
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E-training in organizations E-train
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efficacy regarding online training,
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Method Sample and procedure Figure
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0.874 which exceeded the recommende
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Page 141 and 142: Brown, M., & Cudeck, R. (1993). Alt
Page 143 and 144: Wen, Y., Looi, C.-K., & Chen, W. (2
Page 145 and 146: when they are designing and impleme
Page 147 and 148: paper focuses on the first three st
Page 149 and 150: their self-esteem to be partners in
Page 151 and 152: Democratizing knowledge and symmetr
Page 153 and 154: 1) Reading the article: At the star
Page 155 and 156: Effects of RCKI principle-based ped
Page 157 and 158: References Alexander, C. (1979). Th
Page 159 and 160: Valsamidis, S., Kontogiannis, S., K
Page 161 and 162: The Analog system (Yan et al., 1996
Page 163 and 164: First, the number of the sessions a
Page 165 and 166: BioLayout uses a modified version o
Page 167 and 168: As shown in figure 3, all metrics c
Page 169 and 170: Figure 7. The detailed results for
Page 171 and 172: Enright, A. J., van Dongen, S., Ouz
Page 173 and 174: Chu, S. K. W., Kwan, A. C. M., & Wa
Page 175 and 176: teachers, as well as collaboration
Page 177 and 178: from the students’ ratings appear
Page 179 and 180: Table 5 summarizes the students’
Page 181 and 182: eading blogs (i.e., reminders, easy
Page 183 and 184: Luehmann, A. L. (2008). Using blogg
Page 185 and 186: Uzunboylu et al. (2009) examined th
Page 187 and 188: System implementation Overview of M
Page 189: Methods Before the experiment, a mo
Page 193 and 194: Comparisons of UMLS Questionnaire i
Page 195 and 196: already described may play an impor
Page 197 and 198: Parker, D., Manstead, A. S. R., Str
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Page 201 and 202: Literature review The related varia
Page 203 and 204: collected through Personal Informat
Page 205 and 206: Self-efficacy 92 5 21 13.37 3.726 W
Page 207 and 208: In this problem, intention was take
Page 209 and 210: References Ajjan, H., & Hartshorne,
Page 211 and 212: Tan, T.-H., Lin, M.-S., Chu, Y.-L.,
Page 213 and 214: Students perused the course materia
Page 215 and 216: problem. All articles were then sen
Page 217 and 218: tests, electronic tests are more li
Page 219 and 220: Students 10 and 11: My classmate Ed
Page 221 and 222: collection was also approved by all
Page 223 and 224: Ubiquitous Revision Seamless Collab
Page 225 and 226: Tai, Y. (2012). Contextualizing a M
Page 227 and 228: tasks were developed from task type
Page 229 and 230: experiences in this phase. Moreover
Page 231 and 232: test is administered again right af
Page 233 and 234: The collected data were analyzed wi
Page 235 and 236: Gorp, K. V., & Bogaert, N. (2006).
Page 237 and 238: 4PL IRT model According to the numb
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would be more accurate if items j+1
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C�I or Change I�I) would be 0.2
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improved by rearrangement procedure
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Table 6. Repeated Measures ANOVA of
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Leppisaari, I., & Lee, O. (2012). M
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Selection of the virtual tool The t
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Environmental themes emerged strong
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Visualization of text (visual langu
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environments where visual technolog
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- Logging in to learning environmen
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McNaught, C., Lam, P. & Lam, S.L. (
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on-site to finally achieve a meanin
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Table 1. Digital game designers and
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worldviews are socio-cultural-histo
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Phase Methods Visitor data collecti
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operate the game without the help o
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Visitors (end users) must be heard.
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Islas Sedano, C., Pawlowski, J., Su
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part of something larger than the s
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Previous studies have developed rel
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Technology Acceptance. The 10 items
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Table 4. Model Fit Indices Model χ
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In the final path model of set 1, t
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Discussion Differing from prior stu
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Haythornthwaite, C., Kazmer, M. M.,
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Ge, Z.-G. (2012). Cyber Asynchronou
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college of a university situated in
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Table 3 shows us the following info
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Appendix B shows Class 1’s respon
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increase one’s ability to process
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Appendix A Responses concerning syn
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Shih, S.-C., Kuo, B.-C., & Liu, Y.-
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Adaptive U-learning Math Path Syste
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Figure 4. Online tutorial courses o
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Participants and Experimental Proce
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the influence of Test1 scores, an e
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Hall, T., & Bannon, L. (2006). Desi
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(Hofer & Pintrich, 1997; Liu, Lin &
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� Through online peer assessment,
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elativism.” High Internet self-ef
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Peng, H., Tsai, C.-C., & Wu, Y.-T.
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Since game-based learning has been
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The second reason is about the sust
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Methods Figure 5. Quest NPCs provid
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These differences indicated that pa
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quests further involves students’
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Chang, I.-H. (2012). The Effect of
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(1) Vision, planning and management
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Based on an examination of the lite
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Table 2. Analysis of reliability an
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λ10 - 0.69 0.83 ε5 14.50 * - 0.32
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Bailey, G. D. (1997). What technolo
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Stegall, P. (1998). The principal:
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instruction has studied the student
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espond and the estimation of possib
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Research question For the purpose o
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READI reliability To verify the con
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Physical -1.43333(*) .44699 .029 -2
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The results of this study suggest t
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Hsu, Y.-C., Ho, H. N. J., Tsai, C.-
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domains. Five research questions we
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Research sample groups (4) Faculty
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13. Policies, Social Culture Impact
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Non-Specified Others Engineering &
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(AR = -2.1) (n = 7) 2. Non-specifie
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(n): Total number of articles Resea
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Compared to the publications in 200
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Pedagogical Content Knowledge (TPAC
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April 2012 Volume 15 Number 2 - Educational Technology & Society

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