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Context-Aware Mobile Learning on the Semantic Web

Context-Aware Mobile Learning on the Semantic Web
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Author(s): Rachid Benlamri (Lakehead University, Canada), Jawad Berri (Etisalat University College, United Arab Emirates) and Yacine Atif (Massey University, New Zealand)
Copyright: 2008
Pages: 22
Source title: Advances in Ubiquitous Computing: Future Paradigms and Directions
Source Author(s)/Editor(s): Soraya Kouadri Mostefaoui (Oxford Brookes University, UK), Zakaria Maamar (Zayed University, UAE) and George M. Giaglis (Athens University of Economics and Business, Greece)
DOI: 10.4018/978-1-59904-840-6.ch002

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Abstract

This chapter focuses on the theoretical and technological aspects of designing mobile learning (m-learning) services that deliver context-aware learning resources from various locations and devices. Context-aware learning is an important requirement for next generation intelligent m-learning systems. The use of context in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. In this research work, context reflects timeliness and mobility to nurture pervasive instruction throughout the learning ecosystem. In this context of ubiquity that is supported by a new generation of mobile wireless networks and smart mobile devices, it is clear that the notion of context plays a fundamental role since it influences the computational capabilities of the used technology. In particular, three types of context awareness are being considered in this work —platform-awareness, learner-awareness, and task-awareness. In this research work, these contextual elements are defined at the semantic level in order to facilitate discoverability of context-compliant learning resources, adaptability of content and services to devices of various capabilities, and adaptability of services to task at hand and interaction history. The work presented in this chapter contributes towards this direction, making use of the progress in Semantic Web theory and mobile computing to enable context-aware learning that satisfies learning timeliness and mobility requirements.

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