no code implementations • 5 Dec 2022 • Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura Cruz, Kerrie Douglas, Andrew Lan, Christopher Brinton
Traditional learning-based approaches to student modeling (e. g., predicting grades based on measured activities) generalize poorly to underrepresented/minority student groups due to biases in data availability.
no code implementations • 2 Aug 2022 • Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura Cruz, Kerrie Douglas, Andrew Lan, Christopher Brinton
To learn better representations of student activity, we augment our approach with a self-supervised behavioral pretraining methodology that leverages multiple modalities of student behavior (e. g., visits to lecture videos and participation on forums), and include a neural network attention mechanism in the model aggregation stage.
no code implementations • 28 Oct 2021 • Yun-Wei Chu, Elizabeth Tenorio, Laura Cruz, Kerrie Douglas, Andrew S. Lan, Christopher G. Brinton
Our methodology for predicting in-video quiz performance is based on three key ideas we develop.
no code implementations • WS 2019 • Laura Cruz
In recent years, studies of authorship recognition has aroused great interest in graph-based analysis.