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Development of an Extended Information Quality Framework for E-Learning System Content for Engineering Education Courses

Alsiddiqi, Mohamed, Mishra, Rakesh and Asim, Taimoor (2012) Development of an Extended Information Quality Framework for E-Learning System Content for Engineering Education Courses. In: Learning with Mobile Technologies, Handheld Devices, and Smart Phones: Innovative Methods. IGI Global, Hershey, PA, USA, pp. 162-170. ISBN 9781466609365

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    Abstract

    Poor integration of pedagogical and technological learning elements within teaching and learning methodologies may have substantial impacts on the effectiveness of learning. Although educational institutions are improving their courses, teaching and learning methodologies and assessment strategies with tailored approaches, their efforts at improvement tend to focus narrowly on academic results. The authors believe that educational courses should give priority to educational goals and labour market expectations (industrial companies' requirements) in devising the methodology of teaching and learning. The technology based learning system has a capability to comply with diverse requirements as mentioned above. The purpose of this paper is to develop an extended information quality framework to measure the effectiveness of e-learning content for technology based learning system for engineering education courses (EECs) in Technical and Vocational Education (TVE) in Bahrain. The model incorporates the requirements of educational goals (TVE goals) and modern industrial needs and integrates these with existing information quality frameworks. The extended model incorporates pedagogical and technological elements, is consistent with the educational objectives and industrial requirements, and can be used as guidelines for measuring the effectiveness of e-learning packages delivered in EECs.

    Item Type: Book Chapter
    Subjects: L Education > L Education (General)
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Automotive Engineering Research Group
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
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    References:

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    Depositing User: Sara Taylor
    Date Deposited: 08 May 2012 12:31
    Last Modified: 08 May 2012 12:31
    URI: http://eprints.hud.ac.uk/id/eprint/13532

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