Student Performance Prediction by Using Data Mining Classification Algorithms
In this paper, the authors present the results from data mining research, performed at one of the famous and prestigious Bulgarian universities, with the main goal to reveal the high potential of data mining applications for university management and to contribute to more efficient university enrolment campaigns and to attracting the most desirable students. The research is focused on the development of data mining models for predicting student performance, based on their personal, pre-university and university-performance characteristics. The dataset used for the research purposes includes data about students admitted to the university in three consecutive years. Several well known data mining classification algorithms, including a rule learner, a decision tree classifier, a neural network and a Nearest Neighbour classifier, are applied on the dataset.