A Cloud-based Framework for Personalized Mobile Learning Provisioning using Learning Objects Metadata Adaptation

Elarbi Badidi

Abstract

With the proliferation of Internet-capable mobile handheld devices and the availability of wireless broadband networks, mobile learning is increasingly adopted to deliver learning content anywhere and anytime to mobile users. Offering compelling mobile learning solutions faces several challenges. These challenges are mainly the adaptation of the learning material to the profile and preferences of the mobile user and the support of multiple devices. Other concerns include the storage, retrieval, and processing of learning content outside of mobile devices. Furthermore, building rich learning management systems requires the integration of learning content from third party providers. This paper describes our proposed cloud-based framework for delivering adaptive mobile learning services. The paper explains the benefits and requirements of cloud-based solutions for educational organizations, and describes the components of the proposed framework together with the process of integrating learning objects imported from third-party providers with in-house learning objects of the educational organization.

References

  1. Brusilovsky, P. (2003). Adaptive navigation support in educational hypermedia: The role of learner knowledge level and the case for meta-adaptation, British Journal of Educational Technology, 34(4), pages 487-497.
  2. Cavus, N. and Ibrahim D. (2009). M-Learning: an experiment in using SMS to support learning new English language words, British Journal of Educational Technology, 40(1), pages 78-91.
  3. Chung, T. S., Rust, R. T., and Wedel, M. (2008). My Mobile Music: An Adaptive Personalization System for Digital Audio Players, Marketing science, 28(1), pages 52-68.
  4. Crompton, H. (2013). A historical overview of mobile learning: Toward learner-centered education, In Z.L. Berge & L. Y. Muilenburg (Eds.), Handbook of mobile learning, pages 3-14, Florence, KY: Routledge.
  5. Davies, B. S., Rafique, J., Vincent, T. R., Fairclough, J., Packer, M. H., Vincent, R., and Haq, I. (2012). Mobile Medical Education (MoMEd) - how mobile information resources contribute to learning for undergraduate clinical students - a mixed methods study, BMC Med Educ, 12(1), pages 1.
  6. De Bra, P. and Ruiter, J. P. (2001). AHA! Adaptive Hypermedia for All, In Proc. of WebNet-World Conference on the WWW and Internet, Association for the Advancement of Computing in Education, pages 262-268.
  7. Economides, A. (2006). Adaptive Mobile Learning, Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education, WMUTE 7806, pages 26-28.
  8. Fang, H., Liu, J., Huang, R., and Li, Y. (2009). Research on adaptive mobile learning resources platform based on learning object model, the Int. Conference on Application of Information and Communication Technologies, AICT 2009, pages 1-6.
  9. Gipple, J. and Lord, E. (2016). Understanding Mobile Learning and Best Practices, ICS Learning Group. http://www.icslearninggroup.com/whitepapers/underst anding-mobile-learning-and-best-practices/.
  10. Heinrich, P. (2012). THE IPAD AS A TOOL FOR EDUCATION, A study of the introduction of iPads at Longfield Academy, Kent. http://www.emergingedtec h.com/2012/07/study-finds-benefits-in-use-of-ipad-aseducational-tool/
  11. Huang, J.J.S., Yang, S.J.H., Chen, Z.S.C., Wu, F.C.C. (2012). Web content adaptation for mobile device: A fuzzy-based approach, Knowledge Management & ELearning: An International Journal, 4(1), pages 102- 122.
  12. IEEE. (2002). IEEE Standard for Learning Object Metadata, IEEE Std 1484.12.1-2002, pages i-32, doi: 10.1109/IEEESTD.2002.94128.
  13. Jung, H., Park, S., and Chung, K. S. (2006). An Architecture for Adaptive Mobile Learning, In Proc. of the 20th Int. Conf. on Advanced Information Networking and Applications, AINA 2006, 2, pages 219-223.
  14. Lehman, R. (2007). Learning object repositories, New directions for adult and continuing education, 2007(113), pages 57-66.
  15. Litchfield, B. C., Driscoll, M. P., and Dempsey. J. V. (1990). Presentation sequence and example difficulty: Their effect on concept and rule learning in computerbased instruction, Journal of computer-based instruction, 17, pages 35-40.
  16. Masud, M. A. H. and Huang, X. (2013). M-learning Architecture for Cloud-based Higher Education System of Bangladesh, Mobile Computing, 2(4), pages 84-94.
  17. MERLOT. (2016). Multimedia Educational Resource for Learning and Online Teaching. http://www.merlot.org.
  18. Oh, J., Herrera, J., Bryan, N. J., Dahl, L., and Wang, G. (2010). Evolving the mobile phone orchestra, In Proc. of the Int. Conf. on New Interfaces for Musical Expression, pages 82-87.
  19. Pimmer, C. and Gröhbiel, U. (2008). Mobile Learning in corporate settings. Results from an Expert Survey, mLearn2008, The Bridge from Text to Context.
  20. Tennyson, R. D. and Christenson, D. L. (1988). MAIS: an intelligent learning system, In D. H. Jonassen (Eds.), Instructional Designs for microcomputer courseware. Hillsdale: N. J.: Erlbaum.
  21. Traxler, J. (2005). Defining mobile learning, IADIS International Conference on Mobile Learning.
  22. Vassileva, J., and Deters, R., 1998. Dynamic Courseware Generation on the WWW, British Journal of Educational Technologies, 29(1), pages 5-14.
  23. Velev, D.M. (2014). Challenges and opportunities of Cloud-based Mobile Learning, Int. J. of Information and Education Technology, 4(1), pages 49-53.
  24. Weber, G. & Brusilovsky, P. (2001). ELM-ART: An adaptive versatile system for Web-based instruction, Int. J. of Artificial Intelligence in Education, Special Issue on Adaptive and Intelligent Web-based Educational Systems, 12 (4), pages 351-384.
  25. WISC-ONLINE. (2016). Wisc-Online By teachers, for students, get unstuck. https://www.wisc-online.com/
Download


Paper Citation


in Harvard Style

Badidi E. (2016). A Cloud-based Framework for Personalized Mobile Learning Provisioning using Learning Objects Metadata Adaptation . In Proceedings of the 8th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-179-3, pages 368-375. DOI: 10.5220/0005810603680375


in Bibtex Style

@conference{csedu16,
author={Elarbi Badidi},
title={A Cloud-based Framework for Personalized Mobile Learning Provisioning using Learning Objects Metadata Adaptation},
booktitle={Proceedings of the 8th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2016},
pages={368-375},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005810603680375},
isbn={978-989-758-179-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - A Cloud-based Framework for Personalized Mobile Learning Provisioning using Learning Objects Metadata Adaptation
SN - 978-989-758-179-3
AU - Badidi E.
PY - 2016
SP - 368
EP - 375
DO - 10.5220/0005810603680375