Multimedia augmented m-learning: Issues, Trends and Open Challenges

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 may impede the life cycle of multimedia-enabled m-learning applications. The taxonomy characterizes the constraint regarding mobile device heterogeneity issues, network performance issues, content heterogeneity issues, content delivery issues, and user expectation. These issues are described, along with their causes and measures, to achieve solutions. Furthermore, we have identified five trending areas through which the adaptability and acceptability of multimedia-enabled m-learning platforms can be increased. Finally, we conclude the article by briefly discussing five open challenges, namely, low complexity encoding, data dependency, measurement and modeling, interoperability, and security.