Abstract
In the past year, the majority of conventional learning schemes have been transformed offline, gradually adapting E-Learning and M-Learning through the evolution of IT technology. In order to achieve effective learning, existing static schemes of learning must be transformed in all domains, to deliver true personalized learning depending on various user characteristics. Offering a conceptual background that supports this environment is the foundation of ubiquitous learning. Ubiquitous learning exists in the physical space of everyday life. It is possible to compose learning components existing in the activity space of an intelligent network. Adaptive learning in such ubiquitous environments is a significant learning step. In a general sense, our aim regard Ubiquitous computing is pursuit in the same light with Human Computer Interaction is pursuit by related works. However, in order to achieve sufficient improvement, ubiquitous learning requires 1) learning system has to provide learner centered learning contents what learner wants, 2) and through consideration of learner’s learning device and learning environment, it has to offer learning contents. In this paper, a system supporting the dynamic configuration of user optimized learning objects, and the transmission of learning content irrespective of the learner device used, is designed and implemented. In addition, through the development of an effective learning model, the effect on learning is maximized.
This work was supported in parts by Ubiquitous Autonomic Computing and Network Project, 21th Century Frontier R&D Program, MIC, Korea, ITRC IITA- 2006-(C1090-0603-0046), Grant No. R01-2006-000-10954-0, and Basic Research Program of the Korea Science & Engineering Foundation. Corresponding author: Eunseok Lee.
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Jeong, C., Lee, E. (2007). Context Aware Human Computer Interaction for Ubiquitous Learning . In: Smith, M.J., Salvendy, G. (eds) Human Interface and the Management of Information. Interacting in Information Environments. Human Interface 2007. Lecture Notes in Computer Science, vol 4558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73354-6_40
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DOI: https://doi.org/10.1007/978-3-540-73354-6_40
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