Monday, 11 September 2017

Use of Education Data Mining in Predicting Educational Dropout 

Data mining helps to mine the unique and significant data from the data warehouse. It is used to express knowledge discovery and search for essential relationships among different variables/attribute in the data warehouse. It can be used in the different field of the real world like banking, education, medical, telecommunications and fraud detection etc. Educational Data Mining has emerged due to the increasing accessibility of educational data and hence the need to analyze this massive data. Educational Data Mining is a multidisciplinary field of research that is used to analyze educational data using data mining techniques. It is essential in education especially when want to check the performance of the student in the near future with their previous record in their education. It is extremely time-consuming and durable process if we want to analyze the student performance manually. The outcome of the manual process is also not up to the mark. There is a dilemma of school dropout in the education system in India and we just try to find out the reasons for their dropout. For that, work has been done to find out the diverse attribute of the student which helps them to dropout in education. So reducing the education dropout in India is one of the challenges that educational institution is dealing with. They aims to enroll more students by providing qualified faculty, best infrastructure, improving laboratories work, sports facilities, and best study program. After enrollment, the main aim of each faculty is to guide each student to effectively complete their studies with the proper knowledge and acquire good skills. Nowadays, however, the deployment of Student Information Systems at the institutional level provides an appropriate infrastructure for student's data organization and storage as well as data acquisition and deeper analyses. This data can help model the behavior of dropouts, and predict future dropouts, therefore giving a chance to counselors to advise and guide students into success. The demand for education in India has increased as more and more children are now attending their schools. But there is lots of problem with the education system causing many students to drop their study. We lack in good infrastructure, quality teachers and poor delivery of course content in India causing people to drop out. It is a common excuse for the students that they don't have easy access to educational institutions. This problem is very true for that student how migrants for different places due to their family problem. They just face the problem for the issue of transfer certificates, school leaving certificate and other such formalities. “It is our educational system that is not encouraging people, creating more and more formalities for the migrant’s students”. Due to all the formalities needed to fulfill, it looks easier to shift jobs than to shift a schools/colleges and once a child is out of school for too long, admissions become even more difficult. The use of Educational Data Mining are list below:
i) To analyze different Data Mining techniques used in the education.
ii) To analyze the work done by different researchers in the field of education with Data Mining till 2016.
iii) To analyze the work done by different researchers to predict the educational dropout with Data Mining.
iv) To spot different attributes and Data Mining techniques which are frequently used for dropout prediction?
v) To find any existing gaps in predicting dropout and find the missing attributes if any, which my further contribute in the better prediction.



Thanks
Mukesh Rajput

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Thanks
Mukesh Rajput