A resource-aware content adaptation approach for E-Learning environment / Mohd Faisal Ibrahim

The rapid growth of web and mobile technologies has allowed people to access E-Learning content from heterogeneous client devices. In order to deliver the best presentation of content requested, the E-Learning system must possess a mechanism that not only capable of accurately discovering the charac...

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Bibliographic Details
Main Author: Ibrahim, Mohd Faisal
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2018
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/20489/1/ABS_MOHD%20FAISAL%20IBRAHIM%20TDRA%20VOL%2013%20IGS%2018.pdf
http://ir.uitm.edu.my/id/eprint/20489/
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Summary:The rapid growth of web and mobile technologies has allowed people to access E-Learning content from heterogeneous client devices. In order to deliver the best presentation of content requested, the E-Learning system must possess a mechanism that not only capable of accurately discovering the characteristics and capabilities of a client’s device but also capable of finding out about network and server resource availability. Three recurring issues need to be addressed when constructing such solutions: 1) How to identify the device characteristic and the capabilities of a device, 2) How to find out about network resource availability, and 3) How to adapt application behavior. Addressing these questions the dissertation makes three main contributions. First, a content negotiation and adaptation architecture was proposed to facilitate the process of identifying and detecting client device. It differs from other existing content negotiation approaches by introducing the idea of combining dynamic and static device capabilities detection methods. It consists of a device database and two processing components: (1) device identification module and (2) device capabilities detection module. The content negotiation and adaptation architecture was implemented and validated through various laboratory experiments and field studies which the results highlight the importance of using token attributes matcher by eliminating the need of using the entire user agent strings for device identification and capabilities detection. Besides reducing the processing overhead it also achieves better results in terms of accuracy compared to the user agent approach…