replicate.education

Josh Gardner, Yuming Yang, Ryan S. Baker, and Christopher Brooks (2019). Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective. Proceedings of the 13th International Conference on Educational Data Mining.

Andres-Bray, J.M., Ocumpaugh, J., Baker, R. (2019) Hello? Who is posting, who is answering, and who is succeeding in Massive Open Online Courses. Poster paper. To appear in Proceedings of the 13th International Conference on Educational Data Mining.

Josh Gardner, Christopher Brooks, and Ryan S. Baker (2019). Evaluating the Fairness of Predictive Student Models Through Slicing Analysis. Proceedings of the 9th International Conference on Learning Analytics & Knowledge. Best Paper Award.

Josh Gardner, Yuming Yang, Ryan Baker, Christopher Brooks. Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining. http://arxiv.org/abs/1806.05208

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

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, Goerge Siemens, Catherine A. Spann, Dragan Sasevic, 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.