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    Model for transforming engineering education using technology-enhanced learning

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    Date
    2015
    Author
    Samaka, Mohammed
    Ally, Mohamed
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    Abstract
    Engineering education is important for all countries to progress and to be competitive in the twenty-first century. This is especially true for countries in the Middle East and North Africa (MENA), which are developing very fast. MENA must train a large number of high-quality engineers to meet the demand for engineers today and in the future. Engineering schools need to transform engineering education to be more flexible and more relevant, and deliver engineering programs in a blended format where students can complete part of the training anywhere and at any time and complete parts that require face-to-face instructions to complete on-campus or in an industry placement. Engineering programs should implement problem-based learning, games and simulation, and contextual learning to encourage outcome-based learning and higher level learning. To cater for different learning styles, proven learning theories should be followed to develop quality programs to improve the completion rate. Technology-enhanced learning consisting of e-learning, online learning, mobile learning, and blended learning should be implemented for the new generation of students, to improve access for students who live in remote locations and those who cannot physically attend a campus. A model for engineering programs to develop quality learning materials is proposed. The model proposed is learner-centered, will cater for different learning styles, and, if followed properly, will result in high-level or deep learning. The proposed model consists of four components. These include a variety of strategies to prepare and motivate the student to start the course, different learning activities for different learning styles and independent learning, interaction strategies to promote high-level learning, and transfer of training in the real environment.
    DOI/handle
    http://dx.doi.org/10.1007/978-3-319-15323-0_5
    http://hdl.handle.net/10576/53650
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    • Computer Science & Engineering [‎2428‎ items ]

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