Are MOOC Learning Analytics Results Trustworthy? With Fake Learners, They Might Not Be!
The rich data that Massive Open Online Courses (MOOCs) platforms collect on the behavior of millions of users provide a unique opportunity to study human learning and to develop data-driven methods that can address the needs of individual learners. This type of research falls into the emerging field...
Main Authors: | Alexandron, Giora, Yoo, Lisa Y., Ruiperez Valiente, Jose Antonio, Lee, Sunbok, Pritchard, David E. |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Physics |
Format: | Article |
Published: |
Springer Science and Business Media LLC
2020
|
Online Access: | https://hdl.handle.net/1721.1/124002 |
Similar Items
-
Evaluating the Robustness of Learning Analytics Results Against Fake Learners
by: Alexandron, Giora, et al.
Published: (2018) -
Using Multiple Accounts for Harvesting Solutions in MOOCs
by: Ruiperez-Valiente, Jose A., et al.
Published: (2016) -
Validating the pre/post-test in a MOOC environment
by: Chudzicki, Christopher, et al.
Published: (2021) -
Validating the pre/post-test in a MOOC environment
by: Chudzicki, Christopher, et al.
Published: (2021) -
Researching for better instructional methods using AB experiments in MOOCs: results and challenges
by: Chen, Zhongzhou, et al.
Published: (2016)