«Learning Analitycs in MOOCs». eMadrid seminar on «MOOCs as part of the future of digital learning» at UNED, as part of LWMOOCS Conference Author: Pedro J. Muñoz Merino, associate professor at UC3M and coordinator of the LALA project

1. Learning Analytics in MOOCs
Learning With MOOCs 2018
Pedro J. Muñoz-Merino
Universidad Carlos III de Madrid
pedmume@it.uc3m.es
Twitter: @pedmume

2. Data in MOOCs
Image taken from http://www.datadial.net/blog/index.php/2011/08/24/why-your-
website-isnt-as-fast-as-it-should-be/

3. Need of learning
analytics in MOOCs
• Many students -> automatic decisions are
necessary
• New available data that is registered (e.g.
new functionality)

4. SPOC environments
• MOOC technology with new functionality
can be used for small scale courses -> SPOCs

5. Learning analytics cycle
Steiner, C., Kickmeier-Rust, M., Türker, M. A. (2014). Review Article about LA and
EDM Approaches, Deliverable D3.1 – LEA’s Box Project, http://css-
kmi.tugraz.at/mkrwww/leas-box/downloads/D3.1.pdf

6. Detector example 1:
Assessment of skills and
adaptive learning
PJ Muñoz-Merino, R. Gonzalez Novillo, C Delgado Kloos: "Assessment of
skills and adaptive learning for parametric exercises combining knowledge
spaces and item response theory. Appl. Soft Comput. 68: 110-124 (2018)
• Parametric exercises. If
one is done correctly,
another instance of the
same exercise can be
done correctly
• Prerrequisites among
exercises

7. Detector example 1:
Assessment of skills and
adaptive learning
PJ Muñoz-Merino, R. Gonzalez Novillo, C Delgado Kloos: "Assessment of
skills and adaptive learning for parametric exercises combining knowledge
spaces and item response theory. Appl. Soft Comput. 68: 110-124 (2018)
• Combination of IRT
and KS

8. Detector example 2:
Gamification behavior
J.A. Ruipérez-Valiente, P.J. Muñoz-Merino, C. Delgado Kloos, C. (2017).
Detecting and Clustering Students by their Gamification Behavior with
Badges: A Case Study in Engineering Education. International Journal of
Engineering Education, 33(2-B), 816-830.

9. Challenges with the
detectors
• No possible in all the environments
• Some functionality needed
• Some requirements needed
• Know the exact meaning
• Accuracy
• Number of cases
• Probability
• Interpretation by teachers

10. Visual analytics: ANALYSE

11. Challenges with visual
analytics
• Understanding by stakeholders -> training needed
• How to act based on the visualizations
• Add pedagogical knowledge, e.g. flipped classroom
• Add course structure
• Add other semantic information
P.J. Muñoz‐Merino et al. (2017). Flipping the classroom to improve
learning with MOOCs technology. Computer Applications in
Engineering Education, 25(1), 15-25.

12. Learning analytics and
the flipped classroom
Rubio Fernández, A., Muñoz-Merino, P. J., & Delgado Kloos, C.
(2018, April). Scenarios for the application of learning analytics
and the flipped classroom. In Global Engineering Education
Conference (EDUCON), 2018 IEEE (pp. 1619-1628). IEEE

13. Prediction: grades
P.M. Moreno-Marcos, P. J. Muñoz-Merino, C. Alario-Hoyos, I. Estévez-
Ayres, & C. Delgado Kloos (2018). Analysing the predictive power for
anticipating assignment grades in a massive open online course.
Behaviour & Information Technology, 1-16.

14. Prediction: dropout

15. Challenges with
prediction
• What can be predicted
• What variables to use for the prediction
• How can be predicted
• Accuracy of the prediction
• Extensibility to other environments. Semantics
affects the prediction, e.g. to other courses

16. Conclusions
• Learning analytics in MOOCs can be very helpful.
Indicators, visualizations, predictions
• Limitations
• Depend on the environment
• Which information should be presented
• Accuracy
• Understandable by stakeholders of the exact meaning
• Adding and combining pedagogy and other semantic
information
• How to act based on it

17. LALA project
• Build capacity in Latin American higher education
institutions to create, adapt, implement learning
analytics tools to improve the academic decision
processes
• https://www.lalaproject.org/

18. Learning Analytics in MOOCs
Learning With MOOCs 2018
Pedro J. Muñoz-Merino
Universidad Carlos III de Madrid
pedmume@it.uc3m.es
Twitter: @pedmume