dc.contributor.author |
Karanja, Richard G |
|
dc.date.accessioned |
2018-03-12T11:48:59Z |
|
dc.date.available |
2018-03-12T11:48:59Z |
|
dc.date.issued |
2017-11 |
|
dc.identifier.uri |
http://41.89.49.13:8080/xmlui/handle/123456789/1271 |
|
dc.description.abstract |
Knowledge as a Service (KaaS) has been a promising computing paradigm in the circles of cloud computing environments. In recent times there has been a growing need for access to knowledge on demand that is fully aligned with the cloud computing paradigm which derives from the idea that users will be able to access on- demand to any application from any location in the world. In KaaS, knowledge is considered an understanding of information based on its relevance on a problem area and is perceived as a precious resource essential in decision making. This research paper has developed a framework hinged on this technology that can be used to utilize knowledge from ambient learning systems in regard to sustainable development goals with a specific approach to the fourth goal targeting inclusive and equitable quality education through open education resources for lifelong learning. The main aim was to provide a platform for dissemination and exploitation of available knowledge that will help improve the quality of education on the ambient learning system. The research also involved a look at different ambient learning projects that aim to meet this SDG goal and helped come up with a KaaS model that can be implemented alongside an ambient learning system. This has helped find out how a collaborative effort can be approached in order to form a knowledge network that can allow access to heterogeneous sources of knowledge which can in turn be of benefit to the knowledge consumers i.e. ambient learning system developers. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
KCA University |
en_US |
dc.subject |
Cloud computing, Actionable Knowledge, TEL, and Multi-modal devices. |
en_US |
dc.title |
A Framework For Knowledge As A Service In The Support Of Mobile Interface Ambient Learning. |
en_US |
dc.type |
Thesis |
en_US |