Navigation Mechanism in Blended Context-Aware Ubiquitous Learning Environment
In recent years, navigation support problems have been discussed and investigated in ubiquitous learning environment. Several researches have proven that students can perform better when navigation supports are provided by learning systems. However, tradi
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Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, 300, Taiwan, ROC {d09524003,judycrt}@chu.edu.tw 2 Department of Operation, Visitor Service, Collection and Information Associate Curator, National Museum of Natural Science, Taichung, Taiwan, ROC [email protected]
Abstract. In recent years, navigation support problems have been discussed and investigated in ubiquitous learning environment. Several researches have proven that students can perform better when navigation supports are provided by learning systems. However, traditional ubiquitous learning environments suffer from some physical limitations. For example, the capacities of learning targets are limited and/or moving times for reaching learning targets are required. To address these limitations and create a more efficient ubiquitous learning environment, a novel learning framework, namely the blended ubiquitous learning environment, is proposed. A blended navigation algorithm, B-MONS, is also proposed for developing a navigation support mechanism which suits the new learning framework. Experimental results show that students learn in the blended navigation environment with the help of B-MONs get higher learning performance. Keywords: ubiquitous learning, e-learning, blended learning, navigation support.
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Introduction
Several researchers have demonstrated the benefits of context-aware ubiquitous learning in helping students to improve their problem-solving ability in the real world [1-5]. However, they suffer a common problem which does not occur in the traditional learning environment, that is, how to provide an appropriate learning path for students. In practical applications, usually a fixed learning path is provided for all of the students without considering personal or environmental situations. When the diagram shifts to a u-learning environment, the pre-set learning path does not work anymore due to the fact that the constraints in such an environment are quite different from those in e-learning or m-learning.
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Corresponding author.
James J. (Jong Hyuk) Park et al. (eds.), Multimedia and Ubiquitous Engineering, Lecture Notes in Electrical Engineering 308, DOI: 10.1007/978-3-642-54900-7_29, © Springer-Verlag Berlin Heidelberg 2014
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C.-K. Chiou, J.C.R. Tseng, and T.-Y. Hsu
Researchers have paid considerable attention to solving the navigation problems in authentic learning environments [6, 7]. Because there are more real-time criteria to be considered in the authentic world, the navigation problem of context-aware u-learning becomes even more difficult than that of a web-based learning environment. In our previous work[6], a greedy method based navigation algorithm was proposed and verified by a serial of experiments that it would improve students’ learning performance in ubiquitous learning environment. Although the navigation support problem has been discussed and investigated, there are some problems that have not yet been addressed. For example, when a ulearning environment is overcrowde
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