Performance Analysis and Prediction of Students Results Using RBF Networks

The size of educational databases has been found to steadily increase over the years. Stored databases contain hidden information. In this document, predictive modelling approaches along with the concepts of grouping and association rules mining are used to extract this hidden information. This hidden information is used to provide valuable insight to both student and tutors to work on the improvement of progress. A predictive model is formulated using RBF which will be useful in understanding the progress of the students. The instructor will be able to understand from the predictive models, the category of students who are already performing well and those that will perform better if given the right attention and approach at the right time.