Data Mining Techniques To Predict Student Academic Performance In Higher Education: Literature Review.

Educational system is significantly changing in today's world. Recently, the New Education Policy (NEP)-2020 isstarted implementing in India. Students can have various options for getting education according to their choices and requirements. NEP-2020 is more student-centric rather than making them compulsory to get the degree with prescribed syllabus. AI has a major role in NEP-2020. Data mining technology plays a vital role in this new higher education system. As the Higher Education Institutions are growing rapidly, it is necessary for them to impart quality education for enrollment of students. Institutions can maintain educational quality by improving their results. This can be achieved by predicting student academic performance with the help of data mining algorithms. Classification, clustering, regression and association rule mining are the data mining techniques which can be implemented on student dataset to predict the final grade. This study focuses on prediction of student performance using classification and regression data mining techniques. The aim of this literature review is to study various data mining tools, algorithms and the important attributes that affect the student academic performance. [ABSTRACT FROM AUTHOR]

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