A taxonomy of eLearning frameworks
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Authors
Zebiba Ali Abegaz
Issue Date
2021-10-08
Type
Thesis
Language
en
Keywords
Education systems , eLearning , eLearning frameworks , eLearning models , eLearning building blocks , eLearning components , eLearning classification , eLearning taxonomy , eLearning adoption , eLearning maturity
Alternative Title
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.