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Currently, online learning has gained a huge recognition within the higher education context and it has become a vital need in the current society to find such improvements, to increase the level of knowledge in people. In the modern society e-learning
is recognized highly where it connects the students with the learning resources limitlessly. People have introduced various Learning Management Systems (LMS) in order to overcome the problem of managing large information sources and they are currently playing
a remarkable role in e-learning environments. The lack of knowledge for employing learning methodologies in an accurate manner, has currently made these e-learning systems to face many problems. Even though LMSs enable the teachers to manage diverse educational materials in a much easier manner because of the differences in accessibility levels to the learning resources and study materials; it has become an unsolved problem to view the overall performance of each student in accordance with the behaviour of the
student which is indicates the actual image of student learning capacity, on the course module. So it has become a massive challenge
to cover the actual needs of the learners through the e-learning systems. Due to different learning patterns of students, it is becoming a
vital need to understand the student performance, in a much more detailed manner.
Getting a proper understanding on a student 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 the tutors to identify the different learning capacities of the students
and will be able to provide the necessary guidance to improve their capabilities. To improve the learning capabilities of the students,
the teachers and tutors should be capable of monitoring the overall performance of each student, separately and dynamically adjust
their teaching methodologies on students and to take immediate decisions to improve learning of students. In this context,
methodologies available in educational data mining can be used to extract knowledge from educational data sources to better
understand students and the way they learn. This paper mainly focuses on the use of different data mining techniques upon the educational data to identify or discover the important knowledge on student learning which can be used to evaluate the students
overall performances in the e-learning systems and identify and how these are been used to recognize different learning patterns of the students. Currently most of the techniques which are been used in each step in the data mining process contain its own advantages and
disadvantages depending on the usage with the educational data which indicate the patterns of learning of students in many different
forms and with various accuracy levels. However, based on these techniques, different models can be implemented to evaluate the
performance of each student and it will be used to predict the overall performance that each student will be taking at the end of the course modules. Based on these results the teachers can provide the necessary guidance to the students who need more attention and also as an assistance to improve their capabilities on teaching and this will enable the knowledge producers to dynamically change the knowledge flows within the e-learning environments in a more effective and efficient manner. |
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