.png){kind=icon}
返回
Multimedia augmented m-learning: Issues, trends and open challenges
.png){kind=icon}
OA
AI
DOI：10.1016/j.ijinfomgt.2016.05.010.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Mobile learning
Cloud learning
Multimedia-enabled learning
Personalized learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
27
论文数:
2.9K
被引数:
2.4W
机构
引用论文
Long-term behaviour of a gravity-driven dead end membrane filtration unit for potable water supply in cases of disasters.png)
Water Supply
Water SupplyIF0
PREAI
分享收藏
查看更多内容