Education 4.0 — Fostering student's performance with machine learning methods

Abstract

Educational activity is increasingly moving online and course contents are becoming available in digital format. This enables data collection and the use of data for analyzing learning process. For the 4th Revolution in Education, an active and interactive presence of students contributes to a higher learning quality. Machine Learning techniques recently have shown impressive development steps of the use of data analysis and predictions. However, it has been far less used for assessing the learning quality. For this paper we conducted analysis based on neural networks, support vector machine, decision trees and cluster analysis to estimate student's performance at examination and shape the next generation's talent for Industry 4.0 skills.