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Doctoral Degrees (Information Systems and Technology)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6926

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Browsing Doctoral Degrees (Information Systems and Technology) by Subject "Artificial Neural Networks (ANN)"

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    Bridging the training needs of cybersecurity professionals in Mauritius through the use of smart learning environments.
    (2020) Sungkur, Roopesh Kevin.; Maharaj, Manoj Sewak.
    Teaching and Learning confined to within the four walls of a classroom or even online Learning through Massive Online Courses (MOOCs) and other Learning Content Management Systems (LCMS) are no longer seen as the optimal approach for competency and skills development, especially for working professionals. Each of these busy learners have their own training needs and prior knowledge. Adopting the one-size-fits-all teaching approach is definitely not effective, motivating and encouraging. This is why this research presents the use of SMART Learning Environment that makes use of Intelligent Techniques to personalise the learning materials for each learner. It has been observed that on one hand the country is not able to provide the required number of IT professionals with the desired skills and on the other hand, the number of unemployed graduates in areas other than IT is increasing. This mismatch in skills is becoming a pressing issue and is having a direct impact on the ICT Sector, which is one of the pillars of the Mauritian Economy. An in-depth Literature Review was carried out to understand the training needs of these Cybersecurity professionals and also to understand the different Intelligent Techniques that can be used to provide personalisation of learning materials. Data was collected during three phases, namely an Expert Reference Group Discussion, a pre-test questionnaire and a survey questionnaire. The Expert Reference Group Discussion was carried out to further shed light on the research question set and to further understand the training needs and expectations of Cybersecurity professionals in Mauritius. A SMART Learning Environment making use of Artificial Neural Networks and Backpropagation Algorithm to personalise learning materials was eventually designed and implemented. Design Science Research Methodology (DSRM), Activity Theory, Bloom’s Taxonomy and the Technology Acceptance Model were used in this study. Due to the inherent limitations of the models mentioned, the researcher also proposed and evaluated an emergent conceptual model, called the SMART Learning model. The major findings of this research show that personalisation of learning materials through the use of a SMART Learning Environment can be used to effectively address the training needs of Cybersecurity professionals in Mauritius.