Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling [article]

Clarence Chen, Zachary Pardos
2020 arXiv   pre-print
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.
arXiv:2001.08333v2 fatcat:bm4rxrd7j5bn5hhv5ykhcrmkia