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Predicting students' performance in online courses using multiple data sources

Computers and Society 2021-09-17 v1 Machine Learning
Authors: Mélina Verger , Hugo Jair Escalante
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Abstract

Data-driven decision making is serving and transforming education. We approached the problem of predicting students' performance by using multiple data sources which came from online courses, including one we created. Experimental results show preliminary conclusions towards which data are to be considered for the task.

Keywords

education technology machine learning theory educational data mining

Cite

@article{arxiv.2109.07903,
  title  = {Predicting students' performance in online courses using multiple data sources},
  author = {Mélina Verger and Hugo Jair Escalante},
  journal= {arXiv preprint arXiv:2109.07903},
  year   = {2021}
}

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