MORF:Data Studies

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This page lists all known MORF based data studies since 2020.

Published Studies

Hutt et al. (2022)[1]

Title - Controlled outputs, full data: A privacy-protecting infrastructure for MOOC data.

Andres-Bray (2021)[2]

Title - Replication in Massive Open Online Course Research Using the MOOC Replication Framework (Doctoral dissertation, University of Pennsylvania).

Zhao, Wang, & Sahebi (2020)[3]

Title - Modeling knowledge acquisition from multiple learning resource types.

Wang et al. (2021)[4]

Title - Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor Factorization.

Ongoing Studies

  • Investigating algorithmic bias in predicting dropout from MOOCs for intersectional identities (led by researcher at CMU)
  • Detecting which MOOC forum posts should be responded to by course staff (led by former graduate student at Penn)
  • Other ongoing projects involving researchers at University of Florida, Northern Kentucky University, SUNY Albany, University of Pennsylvania

References

  1. Hutt, S., Baker, R. S., Ashenafi, M. M., Andres‐Bray, J. M., & Brooks, C. (2022). Controlled outputs, full data: A privacy‐protecting infrastructure for MOOC data. British Journal of Educational Technology.
  2. Andres-Bray, J. M. L. (2021). Replication in Massive Open Online Course Research Using the MOOC Replication Framework (Doctoral dissertation, University of Pennsylvania).
  3. Zhao, S., Wang, C., & Sahebi, S. (2020). Modeling knowledge acquisition from multiple learning resource types. arXiv preprint arXiv:2006.13390.
  4. Wang, C., Sahebi, S., Zhao, S., Brusilovsky, P., & Moraes, L. O. (2021, June). Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor Factorization. In Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (pp. 179-188).