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Now-a-days the amount of data stored in educational database is increasing rapidly. These databases contain hidden information for improvement of students’ performance. The performance in higher education in India is a turning point in the academics for all students. This academic performance is influenced by many factors, therefore it is essential to develop predictive data mining model for students’ performance so as to identify the difference between high learners and slow learners student. Predicting the performance of a student is a great concern to the higher education managements. The scope of this project is to identify the factors influencing the performance of students in final examinations and to predict the grade of students so as to a give timely and an appropriate warning to students those who are at risk. In the present investigation, a survey cum experimental methodology was adopted to generate a database and it was constructed from a primary and a secondary source. This work will help the educational institutions to identify the students who are at risk and to and provide better additional training for the weak students.

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Schools as well as colleges have necessity to judge the academic efficiency of students by grades or external and internal marks and percentage of attendance and behavior or outlook of a student. 


Educational predicting the student’s performance is recently developed trend and interesting method that provides diverse predictions in all educational levels. Numerous methods of data mining includes the following. 


A. Calculation of Students academic performance 


B. Calculating student’s percentage of attendance. 


C. Students behavioral prediction 

Course Currilcum

    • Student Prediction Synopsis 00:00:00
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