mlsanityData to 14 Oct 2026

Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling

arXiv 2001.08333 ↗First posted 23 Jan 2020cs.LG cs.CY stat.MLcited by 1

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 23 Jan 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024Deep Learning for Educational Data Sciencecited by 1