  This paper presents several strategies that can improve neural network-based
predictive methods for MOOC student course trajectory modeling, applying
multiple ideas previously applied to tackle NLP (Natural Language Processing)
tasks. In particular, this paper investigates LSTM networks enhanced with two
forms of regularization, along with the more recently introduced Transformer
architecture.
