Difference between revisions of "MORF:Data Studies"
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* Detecting which MOOC forum posts should be responded to by course staff (led by former graduate student at Penn) | * 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 | * Other ongoing projects involving researchers at University of Florida, Northern Kentucky University, SUNY Albany, University of Pennsylvania | ||
== References == | |||
Revision as of 13:05, 17 July 2022
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
- ↑ 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.
- ↑ Andres-Bray, J. M. L. (2021). Replication in Massive Open Online Course Research Using the MOOC Replication Framework (Doctoral dissertation, University of Pennsylvania).
- ↑ Zhao, S., Wang, C., & Sahebi, S. (2020). Modeling knowledge acquisition from multiple learning resource types. arXiv preprint arXiv:2006.13390.
- ↑ 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).