A Review on Student Performance Analysis Based on Result Outcome

In our daily academic life we see a lot of data gets accumulated as a result of processes like examinations,registration,event organisation etc in schools and colleges. This data can be used effectively for the beneficiary of the institution itself. As this data is only operational ,we can develop a system for a graduation or higher level institution which will help the administration gain information turned knowledge from accumulated data. The system can be developed to perform three main functions :student performance analysis, prediction of rank of a student & evaluating the teaching quality. The system will take input from the faculty in the form of marks into it's database, analyse the students marks using neural networks, training & optimize data. The knowledge is hidden among the educational data set and it is extractable through data mining techniques. Present paper is designed to justify the capabilities of data mining techniques in context of higher education by offering a data mining model for higher education system in the university. In this research, the classification task is used to evaluate student’s performance and as there are many approaches that are used for data classification, the decision tree method is used here. By this task we extract knowledge that describes students’ performance in end semester examination. It helps earlier in identifying the dropouts and students who need special attention and allow the teacher to provide appropriate advising/counselling.