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A Survey on Analysis the Students Mind in Different Area

Journal: International Journal of Science and Research (IJSR) (Vol.7, No. 12)

Publication Date:

Authors : ; ;

Page : 633-639

Keywords : Data Mining; Educational Data Mining; Prediction; Profiling Data Mining; Clustering; Relationship Mining; Education; Students; Performance; Patterns; Classification;

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Over the past decade there has been a rapid growth in higher education system. A lot of new institutions have come up both from public and private sector offering variety of courses for under graduating and post graduating students. The rates of enrolments for higher education has also increased but not as much as the number of higher institutions are increasing. It is a concern for today's education system and this gap has to be identified and properly addressed to the learning community. Hence it has become important to understand the requirement of students and their academic progression. Educational Data Mining helps in a big way to answer the issues of predictions and profiling of not only students but other stake holders of education sectors. This paper discusses the application of various Data Mining tools and techniques that can be effectively used in answering the issues of predictions of student's performance and their profiling. This study explores multiple factors theoretically assumed to affect students? performance in higher education, and finds a qualitative model which best classifies and predicts the students? performance based on related personal and social factors. Educational Data Mining refers to techniques, tools, and research designed for automatically extracting meaning from large repositories of data generated by or related to people' learning activities in educational settings.

Last modified: 2021-06-28 20:23:20