Artificial Intelligence in Education: application in student performance evaluation.

Abstract

Education has gained importance to accelerate the development of countries by means of personalized education and students' characteristics, family properties, etc., and boost their knowledge acquisition. While it is challenging task for humans to analyze each student independently, Artificial Intelligence and machine learning approaches provide rapid solutions with high accuracy to assist humans. This paper presents several experiments with different educational datasets to predict and classify student performances. Several machine learning models are considered for each problem and obtained results show that Artificial Intelligence can assist instructors to improve personalized education before or during the active semester. It is also analyzed that Radial Basis Function Neural Network outperforms other models considered in this research.