Student's Academic Performance Analysis using SOM

The ability to monitor the progress of students' academic performance is a critical issue and monitoring student academic performance is not an easy task. Many factors could act as barriers to students attaining and maintaining high scores throughout the academic career. Moreover such type of problems could be solved with the help of data mining techniques. The prediction of academic results shows the students overall academic performance during their tenure and enables them to cope with academics easily. The proposed study aims to develop an effective decision classifier for monitoring and predicting students' academic performance using clustering techniques. One such method investigated in this model is Self Organizing Map or SOM clustering technique. This method is applied to the student data set and the results are predicted.