Towards Advanced Approaches to Predict Students Dropout in MOOCS

As the years have progressed, Massive Open Online Courses (MOOCs) have proven to be one of the main online learning methods for students around the world. However, the popularity of MOOCs has led to a major issue of low course completion rates and high MOOC dropout rates. As a result, predicting dropout rates in MOOCs is a research topic that is of interest to any researcher. In this paper, we aim to develop a deep learning model that focuses on extracting common features with modern techniques and trains our model to obtain better predictive performance compared to traditional methods and machine learning.