A Classification Framework for Context-aware Mobile Learning Systems
Автор: Richard A.W. Tortorella, Kinshuk, Nian-Shing Chen, Sabine Graf
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 7 vol.9, 2017 года.
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The field of context awareness is ever increasing due to the proliferation and omnipresent nature of mobile computing devices. Not only is learning becoming ubiquitous, but the sensors in mobile devices are permitting learning systems to adapt to the context of the learners. This paper provides a classification framework for the field of context-aware mobile learning, which is applied to papers published within selected journals from January 2009 to December 2015 inclusive. Obtained from the combined fields of context awareness and educational technology, a total of 2,968 papers are reviewed, resulting in 41 papers being selected for inclusion in this study. The classification framework consists of three layers: hardware architecture layer, context architecture layer and an evaluation layer. The framework will allow researchers and practitioners to quickly and accurately summarize the status of the current field of context-aware mobile learning. Furthermore, it has the potential to aid in future system development and decision making processes by showing the direction of the field as well as viable existing methods of system design and implementation.
Context-aware learning system, mobile learning, adaptive learning, classification framework, ubiquitous learning, context-awareness
Короткий адрес: https://sciup.org/15014981
IDR: 15014981
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