A Bayesian Approach to Predict Performance of a Student (BAPPS): A Case with Ethiopian Students

R. Bekele and W. Menzel (Germany)


Bayesian approach, Modelling, machine learning, Student Performance, Stochastic Modelling.


The importance of accurate estimation of student's future performance is essential in order to provide the student with adequate assistance in the learning process. To this end, this research aimed at investigating the use of Bayesian networks for predicting performance of a student, based on values of some identified attributes. We presented empirical experiments on the prediction of performance with a data set of high school students containing 8 attributes. The paper demonstrates a new application of the Bayesian approach in the field of education and shows that the Bayesian network classifier has a potential to be used as a tool for prediction of student performance.

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