Dropout prediction in MOOCs using behavior features and multi-view semi-supervised learning

@article{Li2016DropoutPI,
  title={Dropout prediction in MOOCs using behavior features and multi-view semi-supervised learning},
  author={Wentao Li and Min Gao and Hua Li and Qingyu Xiong and Junhao Wen and Zhongfu Wu},
  journal={2016 International Joint Conference on Neural Networks (IJCNN)},
  year={2016},
  pages={3130-3137}
}
While massive open online courses (MOOCs) have gained increasing popularity in recent years, dropout prediction has been an important task to solve due to the high rates of dropout students found in MOOCs. Current methods normally apply supervised learning methods to dropout prediction, using general features extracted from behavior records without the concern of behavior types. However, student learning behavior is diverse and there are no sufficient labeled data to train a model because it is… CONTINUE READING

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