| dc.description.abstract | E-leaming has been widely used by various institutions all over the world. This has been positively embraced by
many people who are eager to acquire knowledge for various reasons. This Las attracted a lot of interest by scholars
who are determined to improve this learning mode and enable easy access of learning information by various
categories of groups. There are a number of proposals brought forward by researchers for consideration by system
developers so that they can come up with robust and scalable e-learning systems. Among the suggestions which
have been put forward for consideration include but not limited to the following: System adaptability, learner profile
updates and ability to provide relevant learning information suited for various categories of learners. However, there
is need to incorporate into both, the existing and the proposed learning systems, the ability to classify learners as
they go on with the learning process. The other issue which needs to be considered is ability of the system to allow
learners to learn while they are either online or offline.
In manyparts of the world, especially in the developing world, most people do not have reliable continuous internet
connections. Furthermore, the cost of bandwidth is high making many people not able to afford it.
A research was carried out and a model was developed that was tested in a learning institution with learners. The
results of the test were analyzed which showed that 83.3% of the learners were correctly classified and 76% of them
were able to learn under intermittent internet connection conditions.
This study therefore found out that it was possible to have learner models that can adapt to learner characteristics
andprovide relevant learning information as per the learner level of knowledge and that learners were able to learn
underboth online and offline modes with correct classifications taking place. | en |
