Abstract:
In traditional learning, teachers provide individual feedback and recommend LM to improve the students’
knowledge and to motivate, based on the skills and personality of the student. But in e-learning, there is no
role of a teacher. The e-learning systems provide lot of learning materials for the students after an exam
regardless of matching reading materials with the students’ knowledge and their reading preferences. If the
e-learning system does not provide learning materials students tend to google. Following both these
approaches create the overloaded information problem since the students cannot identify the best article
suddenly through web. Due to this problem a solution is suggested with recommending learning materials to
students based on their knowledge, interaction data, learning style model with their reading preferences. A
novel way of mapping students’ knowledge, interaction data and reading preferences is introduced by the
solution and in order to develop the solution model was selected as the LMS and creating feedback with the
learning material recommendations is implemented as a REST service. The problem is addressed considering
the software engineering students who tries to do online assessments.
The proposed system was evaluated by evaluators of various domains. Eventually, the test results attested
that the analysis, design, implementation and documentation have been carried out in an effective and in an
efficient manner.
