Application of Data Mining Technique for Prediction of Academic Performance of Student A Literature survey

Abstract

Application of data mining in the educational Systems can be directed to support the specific need of each of the participants in the education system and the process. Students are required to add the recommendation for additional activities, teaching material and task that would favor and improve his/her learning and the learning process. Professors would have the feedback, possibilities to classify students into group’s base on their need for guidance and monitoring, to find the mistakes, and find the effective actions. There are so many prediction model are available with difference approach and techniques in student performance prediction was reported by researcher, but there is no possibility if there are any predictors that accurately determine whether a student will be an genius, a drop out, or an average performer. The target of this study was to apply the k-map method for mining data to analyze the relationships in between students success and their behavior and to develop model for Prediction of Academic Performance of Students. This would be done by using Support Vector Machine (SVM) classifications and kernel k-map clustering mechanism. Predicting student’s performance can help identify the students who are at risk of failure and thus management can provide timely help and take essential steps to coach the students to improve performance.