| Summary: | 碩士 === 國立臺南大學 === 數位學習科技學系碩士班 === 96 === In recent years, there has been a rapid development in wireless communication with embedded and invisible devices that making a breakthrough to the modern learning pedagogies. Technologies made the transition from e-learning to m-learning age, and further, learning is turning a new page due to the evolution of Ubiquitous Learning which was integrated with the ubiquitous computing technologies and situated learning theories. U-learning makes students to interact with physical learning environments and objects, and consequently, improves the acquisitions of knowledge, skills, and experiences. However, most of the u-learning systems nowadays lack a suitable navigation scheme to assist students in learning, and subsequently may cause learners the problems of cognitive overload and disorientation. Therefore, an appropriate learning strategy designed according to the characteristics and differences of the learning objects and environments is required for u-learning. Accordingly, this thesis proposed a navigation strategy and individualized context-aware ubiquitous learning system with the utilization of RFID and Pocket PC devices. We used Repertory Grid and FOCUS algorithm for the similarity analysis and clustering of learning objects, and these results are further utilized for the proposed learning path navigation algorithm. This algorithm can provide dynamic and optimal paths to individual learners in the u-learning environment, and achieve the purpose of improving the learning efficiency and performance for u-learners.
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