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    Designing an M-learning system for Community Education and information on HIV and AIDS in Kenya

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    Date
    2012
    Author
    Oduor, Fredrick O
    Type
    Thesis
    Language
    en
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    Abstract
    The aim of the study is to determine how m-learning can be used to create an interactive learning environment that can help improve awareness on HIV in Kenya by improving the contextualisation of information and providing a seamless platform for discussions on issues relating to HIV AIDS. The specific objectives that are addressed include to identify the pedagogical and technical challenges that are likely to be faced in using the m-learning model and the e-platform for discussing HIV AIDS related issues; to determine if the m-learning model influences gain of knowledge on HIV AIDS; to personalise the information presented to individual model users in terms of their learning interests and to develop an m-learning model that allows for the aggregation and contextualisation of information on HIV AIDS to the specific needs of the information seeker. The study involved developing a prototype m-learning system, use of the system by selected 50 truck drivers and reporting on selected aspects of the system. The data collection involved administration of questionnaire and acquisition of system data on the use of the prototype. The findings reveal technical and pedagogical challenges such as internet access and use of technical words. Additionally, the findings show that m-learning model influences knowledge gain, allows for personalisation of information and integration of information from different sources. These findings have multiple implications on policy, practice and research. Importantly, the findings show the potential offered by m-learning in community education on HIV AIDS and highlight the need for improved dialogue and support for learner autonomy within m-learning.
    URI
    http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/56606
    Citation
    Masters of Science in Computer Science
    Publisher
    University of Nairobi
     
    School of Computing and Informatics
     
    Collections
    • Faculty of Science & Technology (FST) [4213]

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