Prediction of Work Integrated Learning Placement Using Data Mining Algorithms

Data mining in education is used to study data and discover new patterns that can be used for decision making. The classification algorithms are applied on educational data set for predicting work integrated learning placement based on student performance. J48, Bayes Net, Naive Bayes, Simple Cart, and REPTREE algorithms are applied to student data set to predict their performance for placement in the work place. The decision tree from the prediction shows likely students ready for placement in the work environment. The research compares different data mining techniques for classifying student's based on data set for the semester before final examinations.