Early prediction of dropout in online courses using Artificial Neural Networks

Increasing technological advances have created the need to implement new teaching methods. Hence, online education was born, which is defined as education mediated by a virtual learning environment. This type of education, not being a traditional classroom education, difficult to monitor students getting high dropout rates. The use of artificial neural networks helps to predict the behavior of students using historical data and obtain results in the early stages of their student performance, allowing teachers to define strategies to address the high rate of student dropout and take early actions to avoid it.