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A taxonomy of eLearning frameworks

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dc.contributor.advisor Ngassam, Ernest Ketcha Zebiba Ali Abegaz 2022-05-05T11:02:43Z 2022-05-05T11:02:43Z 2021-10-08
dc.description.abstract Research in the age of the knowledge economy has revealed that there is a growing demand for human skills to fit changes necessitated by breakthrough technology (Information and Communication Technology) innovation in higher education. Subsequently, the application of eLearning has become an inevitable reality and an opportunity for software vendors to make appropriate eLearning solutions available to the learning community. However, this has resulted in a plethora of eLearning frameworks which makes it challenging for learning institutions to select and adopt an appropriate eLearning framework to support their innovation goal. The purpose of this study is, therefore, to develop a consolidated view of existing eLearning frameworks using a taxonomy tree to guide institutions in their selection of an appropriate eLearning framework. This prime objective is achieved through the realisation of specific objectives; namely, the development of a generic eLearning framework and a methodology for eLearning adoption. The design science research methodology is applied to address the research questions identified in this study. Preliminary research investigations lead to the identification of distinguishing characteristics of existing eLearning frameworks from which relevant building blocks are deduced. These building blocks are constructs of the generic eLearning framework proposed in this research. The components and elements of the building block are then further identified as well as the metrics for their measurement. Another research investigation leads to the proposal of a methodology for eLearning adoption that shows a step-by-step guideline. This guideline is developed based on the generic eLearning framework and other findings from the literature. The taxonomy for eLearning frameworks is hereby constructed as a taxonomy tree with the building blocks of the generic eLearning framework as branches of the tree, as well as the classification and relationships of existing and new eLearning frameworks. The taxonomy tree provides an integrated view of eLearning frameworks (existing and derived) for ease of identification and reference by interested users. It also facilitates the selection of an appropriate eLearning framework for learning institutions. The validation and improvement exercise on the generic eLearning framework and a methodology for eLearning adoption are derived from surveys and interviews with selected participants. This research demonstrates that the overabundance of eLearning frameworks makes their selection and adoption extremely challenging to learning institutions because of the lack of a rigorous adoption and selection approach. This is thus overcome using the developed taxonomy tree that further serves as a guide to determine the maturity level of a learning institution followed by appropriate recommendations for improvements based on its positioning in the tree. en
dc.format.extent 1 online resource (xx, 312 leaves) : illustrations, color graphs
dc.language.iso en en
dc.subject Education systems en
dc.subject eLearning en
dc.subject eLearning frameworks en
dc.subject eLearning models en
dc.subject eLearning building blocks en
dc.subject eLearning components en
dc.subject eLearning classification en
dc.subject eLearning taxonomy en
dc.subject eLearning adoption en
dc.subject eLearning maturity en
dc.subject.ddc 378.173446780963
dc.subject.lcsh Internet in higher education -- Ethiopia -- Case studies
dc.subject.lcsh Education, Higher -- Ethiopia -- Computer-assisted instruction -- Case studies
dc.subject.lcsh Education, Higher -- Effect of technological innovations on -- Ethiopia -- Case studies
dc.subject.lcsh Universities and colleges -- Ethiopia -- Case studies
dc.subject.lcsh Distance education -- Ethiopia -- Computer-assisted instruction -- Case studies
dc.subject.lcsh Educational technology -- Ethiopia -- Case studies
dc.title A taxonomy of eLearning frameworks en
dc.type Thesis en
dc.description.department School of Computing en Ph. D. (Information Systems)

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