An Integrated Framework Based on Latent Variational Autoencoder for Providing Early Warning of At-Risk Students

An Integrated Framework Based on Latent Variational Autoencoder for Providing Early Warning of At-Risk Students

The rapid development of learning technologies has enabled online learning paradigm to gain great popularity in both high education and K-12, which makes the prediction of student performance become one of the most popular research topics in education. However, the traditional prediction algorithms...

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Bibliographic Details
Main Authors: Xu Du, Juan Yang, Jui-Long Hung
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Performance prediction
early warning prediction
latent variational autoencoder
resampling methods
deep neural network
t-SNE
Online Access:https://ieeexplore.ieee.org/document/8952699/

Internet

https://ieeexplore.ieee.org/document/8952699/

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