Corpus ID: 49210787

Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining

@article{Gardner2018EnablingEM,
  title={Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining},
  author={Josh Gardner and Yuming Yang and R. Baker and C. Brooks},
  journal={ArXiv},
  year={2018},
  volume={abs/1806.05208}
}
  • Josh Gardner, Yuming Yang, +1 author C. Brooks
  • Published 2018
  • Computer Science, Mathematics
  • ArXiv
  • The use of machine learning techniques has expanded in education research, driven by the rich data from digital learning environments and institutional data warehouses. However, replication of machine learned models in the domain of the learning sciences is particularly challenging due to a confluence of experimental, methodological, and data barriers. We discuss the challenges of end-to-end machine learning replication in this context, and present an open-source software toolkit, the MOOC… CONTINUE READING
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