PREDICTING STUDENT PERFORMANCE OF DIFFERENT REGIONS OF PUNJAB USING CLASSIFICATION TECHNIQUES

Abstract

Abstract—Education is a key factor for achieving a long-term economic progress. Although the educational level of Punjab has been improved in the last decades. But results can be more improved if little attention is paid .As competitive environment is prevailing among the academic institutions, challenge is to increase the quality of education through data mining. Student's performance is a great concern for academic institutions. Classification methods like decision trees, Bayesian network etc can be applied on the educational data for predicting the student’s performance in examination. These classification methods will be useful to identify the weak students and help them to score better marks. Various decision tree algorithms like C4.5, ID3 and CART can be applied to the research. In this study, C4.5 algorithm is applied on Student of different colleges of Punjab to predict their performance in the final examination. The outcome of the decision tree predicts the number of students who are likely to pass, fail or promoted to next year. The results provide steps to improve the performance of the students who were predicted to fail or promoted. After declaration of the results in the final examination the marks obtained by the students are fed into the system and the results are analyzed for the next session. The comparative analysis of the results states that the prediction has helped the weaker students to improve and brought out betterment in the result.