Identifying personalized context-aware knowledge structure for individual user in ubiquitous learning environment

Stis Wu, Alex Chang, Maiga Chang, Tzu Chien Liu, Jia Sheng Heh

    Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

    23 Citations (Scopus)

    Abstract

    Ubiquitous learning extends e-learning from indoor to outdoor but also overcomes the weakness of mobile learning which only provides the specific domain knowledge to learners in particular learning environment. A ubiquitous learning environment covers the knowledge of different domains, hence, how to offer individual learner the learning sequence according to the learner's preference is an important issue. In order to solve the research issue, this paper first builds a context-awareness knowledge structure to store the different domain knowledge in a ubiquitous learning environment. After that, with pre-built stories and learning objects' characteristics, the system can aware of what domain knowledge learners are interesting with. Several exhibition rooms and artifacts in museum are used to demonstrate the idea of this research.

    Original languageEnglish
    Title of host publicationProceedings - 5th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, WMUTE 2008
    Pages95-99
    Number of pages5
    DOIs
    Publication statusPublished - 2008
    Event5th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, WMUTE 2008 - Beijing, China
    Duration: 23 Mar. 200826 Mar. 2008

    Publication series

    NameProceedings - 5th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, WMUTE 2008

    Conference

    Conference5th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, WMUTE 2008
    Country/TerritoryChina
    CityBeijing
    Period23/03/0826/03/08

    Keywords

    • Context-awareness knowledge structure
    • Museum learning
    • Pervasive learning
    • Ubiquitous learning environment

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