Mobile-based system for cost-effective e-learning contents delivery in resource and bandwidth constrained learning environments

Michael P. J. Mahenge, Joseph W. Mwangoka

Abstract


The advancement in Information and Communication Technologies (ICTs) has brought opportunities for the development of Smart Cities. The Smart City uses ICT to enhance performance and wellbeing, to reduce costs and resource consumption, and to engage more effectively and actively with its citizens. In particular, the education sector is adopting new ways of learning in Higher Education Institutions (HEIs) through e-learning systems. While these opportunities exist, e-learning content delivery and accessibility in third world countries like Tanzania is still a challenge due to resource and network constrained environments. The challenges include: high cost of bandwidth connection and usage; high dependency on the Internet; limited mobility and portability features; inaccessibility during the offline period and shortage of ICT facilities. In this paper, we investigate the use of mobile technology to sustainably support education and skills development particularly in developing countries. Specifically, we propose a Cost-effective Mobile Based Learning Content Delivery system for resource and network constrained environments. This system can be applied to cost-effectively broaden and support education in many cities around the world, which are approaching the 'Smart City' concept in their own way, even with less available technology infrastructure. Therefore, the proposed solution has the potential to reduce the cost of the bandwidth usage, and cut down the server workload and the Internet usage overhead by synchronizing learning contents from some remote server to a local database in the user’s device for offline use. It will also improve the quality of experience and participation of learners as well as facilitate mobility and portability in learning activities, which also supports the all-compassing learning experience in a Smart City.

https://doi.org/10.34105/j.kmel.2014.06.030

 


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Laboratory for Knowledge Management & E-Learning, The University of Hong Kong