April 2012 Volume 15 Number 2 - Educational Technology & Society

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flower patterns, the bricks on the walls, locations of the map, or rate of exercise. Overall, the experimental group students perform better than the control group in all dimensions of mathematical connection ability. Conclusion In this study, we propose an adaptive U-learning system for math path activities and compare its performance to traditional paper-and-pencil based math path activities. The conclusions are as follows: (1) The adaptive U-learning system developed in this study can extend the application of U-learning to mathematics learning in elementary schools, and provide adaptive testing functions as well as adaptive remedial instructions to improve the shortcomings in previous studies. (2) After the experimental teaching sessions, the results indicate that the adaptive U-learning math path is conducive to the improvement of students’ mathematic achievements. (3) The results of the remedial lessons indicate that the adaptive U-learning math path remedial lessons are more effective than traditional paper-and-pencil based math path remedial lessons. (4) Regarding the performance of mathematical connection ability questionnaire, the experimental group performs better than the control group in dimensions of “consciousness”, “transformation” and “problem-solving”. The above conclusions show that the proposed instructional model and learning system are better than the traditional instructional model in learning “looking for patterns” unit. However, some people may doubt of the feasibility of the proposed instructional model because the prices of Tablet PCs are high. In Taiwan, Tablet PCs are also expensive. Only a few urban elementary schools, learning centers and cram schools can afford such devices to teaching. But, we think U-learning or pervasive learning is still a promising learning model and will become popular in the future because the mobile devices with big screen such as iPAD are getting cheaper with the rapid development of technologies. Furthermore, the study still leaves room for improvement, such as applying to other units, increasing the assessment module of students’ problem-solving process. These will be explored in future research. Acknowledgments This study is supported in part by the National Science Council of the Republic of China under contract numbers NSC 93-2521-S-142-004- and NSC 98-2511-S-142-003-M. References Airasian, P. W., & Bart, W. M. (1973). Ordering theory: A new and useful measurement model. Educational Technology, 13(5), 56-60. Appleby, J., Samuels, P., & Treasure-Jones, T. (1997). Diagnosys—A knowledge-based diagnostic test of basic mathematical skills. Computers & Education, 28(2), 113-131. Chen, G. D., Chang, C. K., & Wang, C. Y. (2008). Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques. Computers & Education, 50(1), 77-90. Chen, G. D., & Chao, P. Y. (2008). Augmenting traditional books with context-aware learning supports from online learning communities. Educational Technology & Society, 11(2), 27-40. Chen, N. S., Kinshuk, Wei, C. W., & Yang, J. H. (2008). Designing a self-contained group area network for ubiquitous learning. Educational Technology & Society, 11(2), 16-26. Chiou, C. K., Tseng, C. R., Hwang, G. J., & Heller, S. (2010). An adaptive navigation support system for conducting contextaware ubiquitous learning in museums. Computers & Education, 55(2), 834-845. Chu, H. C., Hwang, G. J., Huang, S. X., & Wu, T. T. (2008). A knowledge engineering approach to developing E-libraries for mobile learning. The Electronic Library, 26(3), 303-317. Chu, H. C., Hwang, G. J., & Tsai, C. C. (2010). A knowledge engineering approach to developing mindtools for context-aware ubiquitous learning. Computers & Education, 54(1), 289-297. El-Bishouty, M. M., Ogata, H., & Yano, Y. (2007). PERKAM: Personalized knowledge awareness map for computer supported ubiquitous learning. Educational Technology & Society, 10(3), 122-134. 307
Hall, T., & Bannon, L. (2006). Designing ubiquitous computing to enhance children’s learning in museums. Journal of Computer Assisted Learning, 22, 231-243. Huang, Y. M., Huang, T. C., & Hsieh, M. Y. (2008). Using annotation services in a ubiquitous Jigsaw cooperative learning environment. Educational Technology & Society, 11(2), 3-15. Hwang, G. J., Chu, H. C., Shih, J. L., Huang, S. H. , & Tsai, C. C. (2010). A decision-tree-oriented guidance mechanism for conducting nature science observation activities in a context-aware ubiquitous learning environment. Educational Technology & Society, 13(2), 53-64. Hwang, G. J., Kuo, F. R., Yin, P. Y., & Chuang, K. H. (2010). A heuristic algorithm for planning personalized learning paths for context-aware ubiquitous learning. Computers & Education, 54(2), 404-415. Hwang, G. J., Tsai, C. C., & Yang, J. H. (2008). Criteria, strategies and research issues of context-aware ubiquitous learning. Educational Technology & Society, 11(2), 81-91. Hwang, G. J., Yang, T. C., Tsai, C. C., & Yang, J. H. (2009). A context-aware ubiquitous learning environment for conducting complex science experiments. Computers & Education. 53(2), 402-413. Joiner, R., Nethercott, J., Hull, R., & Reid, J. (2006). Designing educational experiences using ubiquitous technology. Computers in Human Behavior, 22(1), 67-76. Kuo, F. R., Hwang, G. J., Chen, Y. J., & Wang, S. L. (2007, July). Standards and tools for context-aware ubiquitous learning. Paper presented at the 7th IEEE International Conference on Advanced Learning Technologies, Niigata, Japan. Laine, T. H., Islas Sedano, C., Vinni, M., & Joy, M. S. (2009, October). Characteristics of pervasive learning environments in museum contexts. Paper presented at the 8th World Conference on Mobile and Contextual Learning (mlearn 2009), Orlando, FL. Liu, T. Y., & Chu, Y. L. (2010). Using ubiquitous games in an English listening and speaking course: Impact on learning outcomes and motivation. Computers & Education, 55(2), 630-643. Liu, T. Y., Tan, T. H., & Chu Y. L. (2009). Outdoor natural science learning with an RFID-supported immersive ubiquitous learning environment. Educational Technology & Society, 12(4), 161-175. Liyytinen, K., & Yoo, Y. (2002). Issues and challenges in ubiquitous computing. Communications of the ACM, 45(12), 62-65. Milrad, M., & Spikol, D. (2007). Anytime, anywhere learning supported by smart phones: Experiences and results from the MUSIS project. Educational Technology & Society, 10(4), 62-70. Ministry of Education of the R.O.C. (2009). Grade 1-9 curriculum guidelines. Retrieved May 20, 2009, from Taiwan Elementary and Secondary Educator Community website: http://teach.eje.edu.tw/9CC2/9cc_97.php Ogata, H., Saito, N. A., Paredes J. R. G., San Martin, G. A., & Yano, Y. (2008). Supporting classroom activities with the BSUL system. Educational Technology & Society, 11(1), 1-16. Ogata, H., & Yano, Y. (2003, September). How ubiquitous computing can support language learning. Paper presented at the 1st. International Conference on Knowledge Economy and Development of Science and Technology, Honjo, Japan. Ogata, H., & Yano, Y. (2004, March). Context-aware support for computer-supported ubiquitous learning. Paper presented at the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education, JhongLi, Taiwan. Peng, H., Chuang, P. Y., Hwang, G. J., Chu, H. C., Wu, T. T., & Huang, S. X. (2009). Ubiquitous performance-support system as mindtool: A case study of instructional decision making and learning assistant. Educational Technology & Society, 12(1), 107- 120. Rogers, Y., Price, S., Randell, C., Fraser, D. S., Weal, M., & Fitzpatrick, G. (2005). Ubi-learning integrating indoor and outdoor learning experiences. Communications of the ACM, 48(1), 55-59. Si, N. K., Weng, J. F., & Tseng, S. S. (2006). Building a frame-based interaction and learning model for U-learning. Lecture Notes in Computer Science, 4159, 796-805. Syvänen, A., Beale, R., Sharples, M., Ahonen, M., & Lonsdale, P. (2005) Supporting pervasive learning environments: Adaptability and context awareness in mobile learning. Proceedings of the Third IEEE International Workshop on Wireless and Mobile Technologies in Education 2005 (pp. 251-253). Los Alamitos, CA: IEEE Computer Society. Yang, J. H. (2006). Context aware ubiquitous learning environments for peer-to-peer collaborative learning. Educational Technology & Society, 9(1), 188-201. Zurita, G., & Nussbaum, M. (2004). Computer supported collaborative learning using wirelessly interconnected handheld computers. Computers & Education, 42(3), 289-314. 308
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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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Even though the result does not con
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Brown, M., & Cudeck, R. (1993). Alt
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Wen, Y., Looi, C.-K., & Chen, W. (2
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when they are designing and impleme
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paper focuses on the first three st
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their self-esteem to be partners in
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Democratizing knowledge and symmetr
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1) Reading the article: At the star
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Effects of RCKI principle-based ped
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References Alexander, C. (1979). Th
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Valsamidis, S., Kontogiannis, S., K
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The Analog system (Yan et al., 1996
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First, the number of the sessions a
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BioLayout uses a modified version o
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As shown in figure 3, all metrics c
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Figure 7. The detailed results for
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Enright, A. J., van Dongen, S., Ouz
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Chu, S. K. W., Kwan, A. C. M., & Wa
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teachers, as well as collaboration
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from the students’ ratings appear
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Table 5 summarizes the students’
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eading blogs (i.e., reminders, easy
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Luehmann, A. L. (2008). Using blogg
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Uzunboylu et al. (2009) examined th
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System implementation Overview of M
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Methods Before the experiment, a mo
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too simple, incomplete, or they eve
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Comparisons of UMLS Questionnaire i
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already described may play an impor
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Parker, D., Manstead, A. S. R., Str
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Avci, U., & Askar, P. (2012). The C
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Literature review The related varia
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collected through Personal Informat
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Self-efficacy 92 5 21 13.37 3.726 W
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In this problem, intention was take
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References Ajjan, H., & Hartshorne,
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Tan, T.-H., Lin, M.-S., Chu, Y.-L.,
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Students perused the course materia
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problem. All articles were then sen
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tests, electronic tests are more li
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Students 10 and 11: My classmate Ed
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collection was also approved by all
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Ubiquitous Revision Seamless Collab
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Tai, Y. (2012). Contextualizing a M
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tasks were developed from task type
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experiences in this phase. Moreover
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test is administered again right af
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The collected data were analyzed wi
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Gorp, K. V., & Bogaert, N. (2006).
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4PL IRT model According to the numb
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examinee’s ability more accuratel
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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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Page 265 and 266: Table 1. Digital game designers and
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Page 277 and 278: part of something larger than the s
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Page 281 and 282: Technology Acceptance. The 10 items
Page 283 and 284: Table 4. Model Fit Indices Model χ
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Page 287 and 288: Discussion Differing from prior stu
Page 289 and 290: Haythornthwaite, C., Kazmer, M. M.,
Page 291 and 292: Ge, Z.-G. (2012). Cyber Asynchronou
Page 293 and 294: college of a university situated in
Page 295 and 296: Table 3 shows us the following info
Page 297 and 298: Appendix B shows Class 1’s respon
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Page 301 and 302: Appendix A Responses concerning syn
Page 303 and 304: Shih, S.-C., Kuo, B.-C., & Liu, Y.-
Page 305 and 306: Adaptive U-learning Math Path Syste
Page 307 and 308: Figure 4. Online tutorial courses o
Page 309 and 310: Participants and Experimental Proce
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Page 315 and 316: (Hofer & Pintrich, 1997; Liu, Lin &
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Page 321 and 322: Peng, H., Tsai, C.-C., & Wu, Y.-T.
Page 323 and 324: Since game-based learning has been
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Page 327 and 328: Methods Figure 5. Quest NPCs provid
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Page 333 and 334: Chang, I.-H. (2012). The Effect of
Page 335 and 336: (1) Vision, planning and management
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Page 339 and 340: Table 2. Analysis of reliability an
Page 341 and 342: λ10 - 0.69 0.83 ε5 14.50 * - 0.32
Page 343 and 344: Bailey, G. D. (1997). What technolo
Page 345 and 346: Stegall, P. (1998). The principal:
Page 347 and 348: instruction has studied the student
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Page 351 and 352: Research question For the purpose o
Page 353 and 354: READI reliability To verify the con
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Page 357 and 358: The results of this study suggest t
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Page 361 and 362: 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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