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This paper presents several strategies that can improve neural network-basedpredictive methods for MOOC student course trajectory modeling, applyingmultiple ideas previously applied to tackle NLP (Natural Language Processing)tasks. In particular, this paper investigates LSTM networks enhanced with twoforms of regularization, along with the more recently introduced Transformerarchitecture.

Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling