Multimedia augmented m-learning: Issues, trends and open challenges
Document Type
Article
Publication Date
1-1-2016
Abstract
The advancement in mobile technology and the introduction of cloud computing systems enable the use of educational materials on mobile devices for a location- and time-agnostic learning process. These educational materials are delivered in the form of data and compute-intensive multimedia-enabled learning objects. Given these constraints, the desired objective of mobile learning (m-learning) may not be achieved. Accordingly, a number of m-learning systems are being developed by the industry and academia to transform society into a pervasive educational institute. However, no guideline on the technical issues concerning the m-learning environment is available. In this study, we present a taxonomy of such technical issues that can impede the life cycle of multimedia-enabled m-learning applications. The taxonomy is devised based on the issues related to mobile device heterogeneity, network performance, content heterogeneity, content delivery, and user expectation. These issues are discussed, along with their causes and measures, to achieve solutions. Furthermore, we identify several trending areas through which the adaptability and acceptability of multimedia-enabled m-learning platforms can be increased. Finally, we discuss open challenges, such as low complexity encoding, data dependency, measurement and modeling, interoperability, and security as future research directions.
Keywords
Mobile learning, Cloud learning, Multimedia-enabled learning, Personalized learning
Divisions
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Funders
Bright Spark Program and High Impact Research Grant, University of Malaya: BSP/APP/1635/2013 and UM.C/625/1/HIR/MOE/FCSIT/03
Publication Title
International Journal of Information Management
Volume
36
Issue
5
Publisher
Elsevier