Advertisement

Adaptive Multimedia Delivery in M-Learning Systems Using Profiling

  • Aleksandar KaradimceEmail author
  • Danco Davcev
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 231)

Abstract

The importance of mobile services in our everyday life is growing and there is an increased necessity for adapting the multimedia content according to the user’s requirements. Therefore, first we need to determine user cognitive preference in order to be able to make adaptation of the multimedia content to mobile user desires. This process of estimation of user profile characteristics and determining which services can be offered for the end user is profiling. This research will inspect the influence of profiling regarding the visualizer-verbalizer dimension of cognitive style in m-learning systems. We have conducted research experiments for different scenarios by using discrete event simulation in OPNET simulator. This paper considers the significance of high QoS requirements that are essential to achieve higher continuity of real-time delivery of multimedia contents.

Keywords

M-learning adaptive multimedia profiling OPNET 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Joseph, S., Uther, M.: Mobile language learning with multimedia and multi-modal interfaces. In: Proceeding of IEEE International Workshop on Wireless and Mobile Technologies in Education (ICHIT 2006), pp. 124–128. IEEE (2006)Google Scholar
  2. 2.
    Gil, D., Andersson, J., Milrad, M., Sollervall, H.: Towards a Decentralized and Self-Adaptive System for M-Learning Applications. In: Proceeding of IEEE Seventh International Conference on Wireless, Mobile and Ubiquitous Technology in Education (WMUTE), pp. 162–166. IEEE (2012)Google Scholar
  3. 3.
    Yang, S.R., Lim, Y.P.: Towards Content Adaptation for Mobile Learning. In: Proceeding of 2nd International Conference on Education and Management Technology, pp. 77–81. IPEDR IACSIT Press, Singapore (2011)Google Scholar
  4. 4.
    La, H.J., Kim, S.D.: A Conceptual Framework for Provisioning Context-aware Mobile Cloud Services. In: Proceeding of IEEE 3rd International Conference on Cloud Computing, pp. 466–473. IEEE (2010)Google Scholar
  5. 5.
    Muntean, V.H., Muntean, G.M.: A novel adaptive multimedia delivery algorithm for increasing user quality of experience during wireless and mobile e-learning. In: Proceeding of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), pp. 1–6. IEEE (2009)Google Scholar
  6. 6.
    Pettersson, O., Gil, D.: On the Issue of Reusability and Adaptability in M-learning Systems. In: Proceeding of 6th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, pp. 161–165. IEEE (2010)Google Scholar
  7. 7.
    Wang, J., Kourik, J.L.: Delivering database knowledge with web-based labs. In: Proceeding of American Society of Business and Behavioral Sciences, ASBBS in Las Vegas, pp. 923–931 (2012)Google Scholar
  8. 8.
    Laghari, K.R., Pham, T.T., Nguyen, H., Crespi, N.: QoM: A new quality of experience framework for multimedia services. In: Proceeding of IEEE Symposium on Computers and Communications (ISCC), pp. 851–856. IEEE (2012)Google Scholar
  9. 9.
    Jung, I.: The Dimensions of E-Learning Quality: From the Learner’s Perspective. Educational Technology Research and Development 59, 445–464 (2011)CrossRefGoogle Scholar
  10. 10.
    Shariffudin, R.S., Julia-Guan, C.H., Dayang, T., Mislan, N., Lee, M.F.: Mobile Learning Environments for Diverse Learners in Higher Education. In: IJFCC 2012, pp. 32–35 (2012)Google Scholar
  11. 11.
    Saranya, M., Vijayalakshmi, M.: Interactive Mobile Live Video Learning System in Cloud Environment. In: Proceeding of IEEE-International Conference on Recent Trends in Information Technology, ICRTIT, pp. 673–677. IEEE (2011)Google Scholar
  12. 12.
    Kushalnagar, R.S., Cavender, A.C., Pâris, J.F.: Multiple view perspectives: improving inclusiveness and video compression in mainstream classroom recordings. In: Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility (ASSETS 2010), pp. 123–130. ACM, New York (2010)CrossRefGoogle Scholar
  13. 13.
    Mayer, R.E.: Multimedia learning. Cambridge University Press, New York (2001)CrossRefGoogle Scholar
  14. 14.
    Mayer, R.E., Massa, L.J.: Three facets of visual and verbal learners: Cognitive ability, cognitive style and learning preference. Journal of Educational Psychology 95, 833–846 (2003)CrossRefGoogle Scholar
  15. 15.
    Zhang, J.: Discrete Event Simulation Enabled High Level Emulation of a Distribution Centre. In: Proceeding of 14th International Conference on Computer Modelling and Simulation (UKSim), pp. 470–475 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty of Computer Science and EngineeringSs. Cyril and Methodius UniversitySkopjeR. Macedonia

Personalised recommendations