Data Mining in Education Sector: A Review
-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.
... e 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. The development of any country depends upon the educational background of its citizens. Most of the developed countries have a high literacy rate. Developing countries are also witnessing a growing demand of higher education. Since this growing demand could not be met only by government Universities and colleges hence large numbers of private universities and institutions have been established in the last decade and the trend will continue in the future also. Despite significant progress over the last ten years, Indian higher education is faced with following broad challenges: A Gap between Supply and Demand: India has a low rate of enrolment in higher education, at only 12% (post graduation level), compared with 26% in China. There is enormous unmet demand for higher education. By 2020, the Indian government aims to achieve 30% gross enrolment, which will mean providing 40 million university places, an increase of 14 million in six years. Poor Quality of teaching and learning: The system is beset by issues of quality in many of its institutions: a chronic shortage of faculty, poor quality teaching, outdated and rigid curricula and pedagogy, lack of accountability and quality assurance and separation of research and teaching. Limited research Capacity: With a very low level of PhD enrolment (only 1% in year 2012-13), India does not have enough high quality researchers; there are few opportunities for interdisciplinary and multidisciplinary working, lack of early stage research experience; a weak ecosystem for innovation, and low levels of industry engagement. Reasons behind lower rate of enrolments in higher education, poor quality of teaching, learning and research needs to be discovered in order to achieve desired growth of any nation. Nowadays many tools and techniques are available to us that can change or improve the education system. Growing digitization of educational data has helped researcher to easily capture these available data and extract meaningful information to take corrective decisions. There are great openings in the educational data through which our knowledge towards education is tremendously increased as compared in the past decade. Educational data is increasing rapidly as more and more education system is going online. It has opened new areas like new computer supported interactive learning methods and tools-intelligent tutoring system, simulation games which has opened up opportunities to collect and analyze student data , to discover patterns and trends in those data and to make new discoveries and test hypothesis about how students learn through on line classes. The data collected from online learning systems can be aggregated over large numbers of students and can contain many variables that data mining algorithms can explore for model building. In today's era educational systems try to offer a customized learning method, by building a model of the individual's goals, attitude and knowledge. Educational Data Mining can be seen as an iterative cycle of hypothesis formation, testing and refinement.