Multimedia augmented m-learning: issues, trends and open challenges
Multimedia augmented m-learning: issues, trends and open challenges
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.
mobile learning, cloud learning, multimedia-enabled learning, personalized learning
784-792
Yousafzai, Abdullah
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Chang, Victor
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Gani, Abdullah
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Noor, Rafidah Md
74d5e504-a1f9-48c6-867e-73df86a2fc2c
October 2016
Yousafzai, Abdullah
c53db578-18cf-4dd2-9e43-b9291a7282f3
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Gani, Abdullah
fb6c3735-3015-40df-b9e3-e2cdfae39da3
Noor, Rafidah Md
74d5e504-a1f9-48c6-867e-73df86a2fc2c
Yousafzai, Abdullah, Chang, Victor, Gani, Abdullah and Noor, Rafidah Md
(2016)
Multimedia augmented m-learning: issues, trends and open challenges.
International Journal of Information Management, 36 (5), .
(doi:10.1016/j.ijinfomgt.2016.05.010).
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.
Text
IJIM_multimedia_and_m_learning_issues.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 9 May 2016
e-pub ahead of print date: 26 May 2016
Published date: October 2016
Keywords:
mobile learning, cloud learning, multimedia-enabled learning, personalized learning
Organisations:
Electronic & Software Systems
Identifiers
Local EPrints ID: 395107
URI: http://eprints.soton.ac.uk/id/eprint/395107
ISSN: 0268-4012
PURE UUID: c5744374-ea62-4ff4-9819-8adea9f98bd6
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Date deposited: 22 May 2016 14:51
Last modified: 15 Mar 2024 05:36
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Contributors
Author:
Abdullah Yousafzai
Author:
Victor Chang
Author:
Abdullah Gani
Author:
Rafidah Md Noor
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