Clustering patterns of engagement in Massive Open Online Courses (MOOCs): the use of learning analytics to reveal student categories

Author:

Khalil Mohammad,Ebner Martin

Publisher

Springer Science and Business Media LLC

Subject

Education

Reference37 articles.

1. Alario-Hoyos, C., Muñoz-Merino, P. J., Pérez-Sanagustín, M., Delgado Kloos, C., & Parada, G. (2016). Who are the top contributors in a MOOC? Relating participants’ performance and contributions. Journal of Computer Assisted Learning. doi: 10.1111/jcal.12127 .

2. Anderson, A., Huttenlocher, D., Kleinberg, J., & Leskovec, J. (2014). Engaging with massive online courses. In Proceedings of the 23rd International Conference on World Wide Web (pp. 687–698). ACM.

3. Balakrishnan, G., & Coetzee, D. (2013). Predicting student retention in massive open online courses using hidden Markov models. Tech. Rep. UCB/EECS-2013-109, University of California.

4. Carson, S., & Schmidt, J. (2012). The massive open online professor academic matter. Journal of Higher Education. Retrieved May 02, 2016 from http://www.academicmatters.ca/2012/05/the-massive-open-online-professor/ .

5. Charrad, M., Ghazzali, N., Boiteau, V., & Niknafs, A. (2013). NbClust: An examination of indices for determining the number of clusters: NbClust package. Retrieved May 12, 2016 from https://cran.r-project.org/web/packages/NbClust/NbClust.pdf .

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