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Predicting students' performance using artificial neural networks PDF Print E-mail
I.E. Livieris, K. Drakopoulou and P. Pintelas, Predicting students' performance using artificial neural networks, In the Proceddings of Information and Communication Technologies in Education, 2012.

Abstract - Artificial intelligence has enabled the development of more sophisticated and more efficient student models which represent and detect a broader range of student behavior than was previously possible. In this work, we describe the implementation of a user-friendly software tool for predicting the students' performance in the course of “Mathematics” which is based on a neural network classifier. This tool has a simple interface and can be used by an educator for classifying students and distinguishing students with low achievements or weak students who are likely to have low achievements.

 

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