MORF

The MOOC Replication Framework.

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Publications

Josh Gardner, Yuming Yang, Ryan S. Baker, and Christopher Brooks (2018). Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining. Workshop on Enabling Reproducibility in Machine Learning at the Thirty-fifth International Conference on Machine Learning. arXiv. Github.

Josh Gardner, Christopher Brooks, Juan Miguel Andres, and Ryan Baker (2018). Replicating MOOC Predictive Models at Scale. Proceedings of the Fifth Annual Meeting of the ACM Conference on Learning@Scale; London, UK.

Josh Gardner, Christopher Brooks, Juan Miguel L. Andres, and Ryan Baker (2018). MORF: A Framework for MOOC Predictive Modeling and Replication At Scale. arXiv.

Miguel Andres, Ryan S. Baker, Dragan Gašević, George Siemens, Scott A. Crossley, Srećko Joksimović (2018). Studying MOOC Completion at Scale Using the MOOC Replication Framework. Proceedings of the International Conference on Learning Analytics and Knowledge (LAK’18) (pp. 71-78).

Miguel Andres, Ryan S. Baker, George Siemens, Catherine A. Spann, Dragan Gašević, and Scott Crossley (2017). Studying MOOC Completion at Scale Using the MOOC Replication Framework. Proceedings of the 10th International Conference on Educational Data Mining (pp. 338-339).

Miguel Andres, Ryan S. Baker, George Siemens, Dragan Gasevic, and Catherine A. Spann (2016). Replicating 21 Findings on Student Success in Online Learning.