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The Scientific World Journal
Volume 2014 (2014), Article ID 109435, 9 pages
http://dx.doi.org/10.1155/2014/109435
Research Article

A Service Based Adaptive U-Learning System Using UX

1Humanitas College, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul 130-701, Republic of Korea
2Department of Computer Science & Engineering, Gangneung-Wonju National University, Gangwon-do 220-711, Republic of Korea

Received 2 May 2014; Accepted 15 June 2014; Published 23 July 2014

Academic Editor: Jong-Hyuk Park

Copyright © 2014 Hwa-Young Jeong and Gangman Yi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. M. Martin, T. K. Shih, and J. C. Hung, “A personal tutoring mechanism based on the cloud environment,” Journal of Convergence, vol. 4, no. 3, pp. 37–44, 2013. View at Google Scholar
  2. M. Ćukušić, N. Alfirević, A. Granić, and Z. Garača, “e-Learning process management and the e-learning performance: results of a European empirical study,” Computers & Education, vol. 55, no. 2, pp. 554–565, 2010. View at Google Scholar
  3. H. Jia, M. Wang, W. Ran, S. J. H. Yang, J. Liao, and D. K. W. Chiu, “Design of a performance-oriented workplace e-learning system using ontology,” Expert Systems with Applications, vol. 38, no. 4, pp. 3372–3382, 2011. View at Publisher · View at Google Scholar
  4. K. M. Lin, “E-learning continuance intention: moderating effects of user e-learning experience,” Computers and Education, vol. 56, no. 2, pp. 515–526, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. T. Saba, “Implications of E-learning systems and self-efficiency on students outcomes: a model approach,” Human-Centric Computing and Information Sciences, vol. 2, article 6, 2012. View at Google Scholar
  6. P. Brusilovsky and E. Millán, The Adaptive Web—Methods and Strategies of Web Personalization, vol. 4321 of Lecture Notes in Computer Science, Springer, Berlin, Germany, 2007. View at Publisher · View at Google Scholar
  7. R. Joiner, J. Nethercott, R. Hull, and J. Reid, “Designing educational experiences using ubiquitous technology,” Computers in Human Behavior, vol. 22, no. 1, pp. 67–76, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. M. S. Kerr, K. Rynearson, and M. C. Kerr, “Student characteristics for online learning success,” Internet and Higher Education, vol. 9, no. 2, pp. 91–105, 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. P.-S. Tsai, C.-C. Tsai, and G.-H. Hwang, “College students' conceptions of context-aware ubiquitous learning: a phenomenographic analysis,” The Internet and Higher Education, vol. 14, no. 3, pp. 137–141, 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. A. Ortigosa, P. Paredes, and P. Rodriguez, “AH-questionnaire: an adaptive hierarchical questionnaire for learning styles,” Computers & Education, vol. 54, no. 4, pp. 999–1005, 2010. View at Publisher · View at Google Scholar
  11. N. C. Mendonça, J. A. F. Silva, and R. O. Anido, “Client-side selection of replicated web services: an empirical assessment,” Journal of Systems and Software, vol. 81, no. 8, pp. 1346–1363, 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. G. D. Chen, C. K. Chang, and C. Y. Wang, “Ubiquitous learning website: scaffold learners by mobile devices with information-aware techniques,” Computers and Education, vol. 50, no. 1, pp. 77–90, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. B. Guo, D. Zhang, and M. Imai, “Enabling user-oriented management for ubiquitous computing: the meta-design approach,” Computer Networks, vol. 54, no. 16, pp. 2840–2855, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. H. Wang, Y. Zhang, and J. Cao, “Access control management for ubiquitous computing,” Future Generation Computer Systems, vol. 24, no. 8, pp. 870–878, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. A. Schmidt, L. Terrenghi, and P. Holleis, “Methods and guidelines for the design and development of domestic ubiquitous computing applications,” Pervasive and Mobile Computing, vol. 3, no. 6, pp. 721–738, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. Y. Hao, Y. Zhang, and J. Cao, “Web services discovery and rank: an information retrieval approach,” Future Generation Computer Systems, vol. 26, no. 8, pp. 1053–1062, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. B. Benatallah, F. Casati, and F. Toumani, “Representing, analyzing and managing Web service protocols,” Data & Knowledge Engineering, vol. 58, pp. 327–357, 2006. View at Google Scholar
  18. S. Paurobally and N. R. Jennings, “Protocol engineering for web services conversations,” Engineering Applications of Artificial Intelligence, vol. 18, no. 2, pp. 237–254, 2005. View at Publisher · View at Google Scholar · View at Scopus
  19. M. Weiss, B. Esfandiari, and Y. Luo, “Towards a classification of web service feature interactions,” Computer Networks, vol. 51, no. 2, pp. 359–381, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  20. H. Cho and M. Choi, “Personal mobile album/diary application development,” Journal of Convergence, vol. 5, no. 1, pp. 32–37, 2014. View at Google Scholar
  21. M. B. Juric, A. Sasa, B. Brumen, and I. Rozman, “WSDL and UDDI extensions for version support in web services,” The Journal of Systems and Software, vol. 82, no. 8, pp. 1326–1343, 2009. View at Publisher · View at Google Scholar · View at Scopus
  22. M. J. Kim, M. W. Oh, and J. T. Kim, “A method for evaluating the performance of green buildings with a focus on user experience,” Energy and Buildings, vol. 66, pp. 203–210, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. F. Pucillo and G. Cascini, “A framework for user experience, needs and affordances,” Design Studies, vol. 35, no. 2, pp. 160–179, 2014. View at Google Scholar
  24. F. Zhou and R. J. Jiao, “An improved user experience model with cumulative prospect theory,” Procedia Computer Science, vol. 16, pp. 870–877, 2013. View at Google Scholar
  25. E. L.-C. Law, P. van Schaik, and V. Roto, “Attitudes towards user experience (UX) measurement,” International Journal of Human-Computer Studies, vol. 72, no. 6, pp. 526–541, 2014. View at Publisher · View at Google Scholar
  26. C.-M. Chen, “Intelligent web-based learning system with personalized learning path guidance,” Computers & Education, vol. 51, no. 2, pp. 787–814, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. P.-C. Sun, R. J. Tsai, G. Finger, Y. Chen, and D. Yeh, “What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction,” Computers & Education, vol. 50, no. 4, pp. 1183–1202, 2008. View at Publisher · View at Google Scholar · View at Scopus
  28. C. Chen, “Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance,” Expert Systems with Applications, vol. 36, no. 5, pp. 8816–8829, 2009. View at Publisher · View at Google Scholar · View at Scopus
  29. P. Brusilovsky, “Adaptive and intelligent technologies for web-based education,” in Special Issue on Intelligent Systems and Teleteaching, C. Rollinger and C. Peylo, Eds., vol. 4, pp. 19–25, Künstliche Intelligenz, 1999. View at Google Scholar
  30. B. Beldagli and T. Adiguzel, “Illustrating an ideal adaptive e-learning: a conceptual framework,” in Proceedings of the 2nd World Conference on Educational Sciences (WCES '10), pp. 5755–5761, February 2010. View at Publisher · View at Google Scholar · View at Scopus