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    Smart education: an event framework for cognitive blended learning

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    Full-text thesis (35.82Mb)
    Date
    2017
    Author
    Karumba, Samuel Maina
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    Abstract
    Digital learning has increasingly been adopted around the world, evidenced by large scale deployment of online learning platforms. More specifically, the use of hand held devices such as mobile phones and tablets has disrupted learning as we traditionally knew it. Blended learning,which extends classroom learning with computer mediated learning, is increasingly being adopted by education systems around the world. However, the two (blended learning and traditional classroom learning) have not been well integrated. For example, there is limited or no information sharing between digital learning mostly carried out by an automated tutor and the traditional classroom conducted by a human instructor. This leads to fragmentation in the overall teaching and learning experience.Existing blended learning platforms have tried to address this issue by focusing on performance management. This approach ignores the bigger challenge in public and private schools: the large number of students to teacher and the inability to offer personalised learning that is essential for students to excel academically. Understanding how personalized technical interventions can be designed requires understanding of where issues intersects. We present the overall architecture and design of event framework. The first version supporting a core set of capabilities for blended learning has been implemented as mobile applications for teachers and students. We conducted a limited pilot to test the technology in an actual classroom setting. We also report on a usability study of the event framework that demonstrates user awareness and support for data-driven cognitive decision-making in education.
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    http://hdl.handle.net/11071/5828
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    • MMTI Theses and Dissertations (2017) [27]

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