dc.contributor.author | MARUBE, ABEDNEGO MOGIRE | |
dc.date.accessioned | 2013-02-19T06:10:59Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | MASTERS OF SCIENCE IN COMPUTER SCIENCE | en |
dc.identifier.uri | http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10155 | |
dc.description.abstract | The number of people depending on the web as a source of information has risen over the past
years. This has not left the education sector behind. The main challenge learner’s face while
using the web is getting the right content, reducing the time spent in searching, collaboration and
accessing content anywhere anytime hence the need for a context aware ubiquitous learning
framework. The framework consists of components that query websites based on user profiles,
aggregate content from various sources, encourage collaboration and transforms content to best
fit a user’s device irrespective of the location. Content aggregation is achieved through the use of
Mashups. These are interactive web 2.0 applications that combine content/information from
multiple sources. Everyday mashups are developed, however few support formal learning with
ability to handle dynamic data. A prototype of this framework was implemented with the
guidance of Dr. Robert Oboko using the feature driven development agile methodology. Students
taking Msc in computer science at the University of Nairobi tested the usability of the framework
through a usability survey based on a 5 likert scale. They further tested the prototype and rated
the content, collaborated amongst themselves and finally took a usability test to determine how
well the framework met the set objectives. The results of the survey indicated that the framework
was well received and appropriate in the formal learning setup. The study still leaves room for
improvement, such as introduction of location based context awareness into the framework to
support informal learning. These will be explored in future research. | en |
dc.language.iso | en | en |
dc.publisher | University of Nairobi | en |
dc.subject | context aware ubiquitous learning framework | en |
dc.title | Context aware framework to support formal ubiquitous learning | en |
dc.type | Thesis | en |
local.publisher | School of Computing and Informatics | en |