It has become a major
challenge to cover the actual needs of the learners through the e-learning
systems. Due to different learning patterns of students it has become vital to
understand the student performance in a much more detail manner. Getting a proper
understanding of the students overall performance which is based on the amount
of information that he or she has gathered through the online resources, will
help the teachers and tutors to identify the different learning capacities of
the students and they will be able to provide the necessary guidance to the
students to improve their capabilities since the main objective of e-learning
system is not to help the student to pass but to help students to learn.
Evaluating the performance
in an e-learning system becomes a massive challenge due to the factors in the
learning model. Many of the qualitative and quantitative factors, which are
available in an e-learning framework, highlight different aspects of the
students' learning which are not been considered yet for evaluation purposes of
the student performances. To improve the learning capabilities of the students,
teachers and the tutors should be capable in monitoring the overall performance
of each student separately and dynamically adjust their teaching methodologies
on the poor performance students and to assist the knowledge producers to
change the knowledge flow and to take immediate decisions to improve learning
capacities. In order to upgrade the learning capacities of the students in an
e-learning education a deeper analysis is much required to evaluate the overall
performance of students at this stage. Therefore by analysing these factors,
learning patterns and activities between the teachers and students in an
e-learning system a proper performance model can be implemented.
What can we do it address the issue ???...This is what I suggest for You..!!!
Educational data mining is a
rising research discipline which is concerned with developing various
methodologies to extract knowledge from educational data sources to better
understand students and the way they learn. Different methodologies are been
developed with relation to the data mining area which involves in predicting
student performances by studying learning to recommend improvements to
educational practices they use. The methodologies which are used in educational
data mining differ from traditional data mining which is mainly based on
exploiting the multiple levels of meaningful hierarchy in educational data.
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