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Analysis of Influencing Factors in Predicting Students Performance Using MLP - A Comparative Study

Jai Ruby, Dr. K. David

In recent years, Educational Data Mining has put on a massive appreciation within the research realm and it has become a vital need for the academic institutions to improve the quality of education. The quality of education is measured by the academic performance of students and the results produced. In higher education institutions a substantial amount of knowledge is hidden and need to be extracted using Knowledge Discovery process. Data mining helps to extract the knowledge from available dataset and should be created as knowledge intelligence for the benefit of the institution. Many factors influence the academic performance of the students. The study model is mainly focused on analyzing the prediction accuracy of the academic performance of the students using only influencing factors by Multi Layer Perceptron algorithm and to compare it with the prediction accuracy of the academic performance of the students using a dataset that comprises of all academic, personal and economic factors of the students using Multi Layer Perceptron algorithm.