MOOCs, Learning Analytics and OER - a perfect triangle for the future of education!
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The document discusses the potential of MOOCs, learning analytics, and open educational resources (OER) for the future of education. It presents 5 theses on lessons learned from analyzing MOOC participation data: 1) dropout rates are overstated, 2) MOOCs enable participatory education, 3) effort does not predict success, 4) analytics reveal classroom learning patterns, and 5) learning occurs continuously. OER-MOOCs could make education widely accessible through open sharing of knowledge and innovative teaching models like flipped classroom. The author argues learning analytics are important to improve OER-MOOC platforms and online education.
MOOCs, Learning Analytics and OER - a perfect triangle for the future of education!
- 1. MOOCs, Learning Analytics and OER - a perfect triangle for the future of education! 03.05.2020 | CSEDU Martin Ebner This work is licensed under a Creative Commons Attribution 4.0 International License.
- 3. is a xMOOC platform for courses with an explicit open license (Creative Commons).
- 6. Currently about 100 open licensed courses are offered in various disciplines.
- 7. How to Implement Learning Analytics?
- 8. Khalil, M. & Ebner, M. (2015). Learning Analytics: Principles and Constraints. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2015. pp. 1326-1336. Chesapeake, VA: AACE
- 9. Khalil, M., Ebner, M. (2016) What Massive Open Online Course (MOOC) Stakeholders Can Learn from Learning Analytics? In: Spector, M., Lockee, B., Childress, M. (Ed.), Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy, Springer International Publishing, pp. 1-30
- 10. Khalil, M., Ebner, M. (2016) What Massive Open Online Course (MOOC) Stakeholders Can Learn from Learning Analytics? In: Spector, M., Lockee, B., Childress, M. (Ed.), Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy, Springer International Publishing, pp. 1-30
- 11. Khalil, M. & Ebner, M. (2015). Learning Analytics: Principles and Constraints. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2015. pp. 1326-1336. Chesapeake, VA: AACE
- 12. LA constraints Khalil, M. & Ebner, M. (2015). Learning Analytics: Principles and Constraints. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2015. pp. 1326-1336. Chesapeake, VA: AACE
- 13. Revealing Personal Information Morality to view students’ data Collecting and Analyzing data Transparency Students’ data deletion policy Khalil, M. & Ebner, M. (2015). Learning Analytics: Principles and Constraints. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2015. pp. 1326-1336. Chesapeake, VA: AACE LA constraints
- 14. Who owns students data, Students or institutions? Data Protection and Copyright Laws limit the use of LA apps Inaccurate analysis results? Achieving Confidentiality, Integrity and Availability LA constraints Khalil, M. & Ebner, M. (2015). Learning Analytics: Principles and Constraints. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2015. pp. 1326-1336. Chesapeake, VA: AACE
- 15. 5 crucial statements What can we learn from Learning Analytics?
- 16. Thesis 1 High Dropout Rate on MOOCs is a legend
- 17. GOL • 1012 Registrants • 479 Active Students (47.3%) • 217 complete course (21,5%) • 177 got certification (17,5%) LIN • 618 Registrants • 461 Active Students (74.5%) • 131 compete course (21,2%) • 99 got certification (16%) Lackner, E., Ebner, M., Khalil, M. (2015) MOOCs as granular systems: design patterns to foster participant activity, eLearning Papers, 42 (2015), pp. 28-37
- 18. Khalil, M., Ebner, M. (2015) A STEM MOOC for School Children - What Does Learning Analytics Tell us? In: Proceedings of 2015 International Conference on Interactive Collaborative Learning (ICL), Florence, Italy, pp. 1-7
- 19. Thesis 2 MOOCs means participatory education (at least in the first four weeks)
- 20. ~ 23,000 reads in GOL Forums ~ The highest on 21-Oct ~ Average of 170 read per day ~ Median of 47 read per day ~ 1623 Max reads on 21-Oct Week 1 Starts Week 2 Starts Week 3 Starts Course ended
- 22. Khalil, M., Ebner, M. (2016) What Massive Open Online Course (MOOC) Stakeholders Can Learn from Learning Analytics? In: Spector, M., Lockee, B., Childress, M. (Ed.), Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy, Springer International Publishing, pp. 1-30
- 23. GOL 16 Khalil, M., Ebner, M., & Admiraal, W. (2017). How can Gamification Improve MOOC Students Engagement?. In proceedings of the European Conference on Game Based Learning, Graz, Austria, (pp. 819-828)
- 24. Thesis 3 Higher effort is good but not a good predictor for success
- 25. Khalil, M., Ebner, M. (2016) What Massive Open Online Course (MOOC) Stakeholders Can Learn from Learning Analytics? In: Spector, M., Lockee, B., Childress, M. (Ed.), Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy, Springer International Publishing, pp. 1-30
- 26. Khalil, M., Ebner, M. (2016) What Massive Open Online Course (MOOC) Stakeholders Can Learn from Learning Analytics? In: Spector, M., Lockee, B., Childress, M. (Ed.), Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy, Springer International Publishing, pp. 1-30
- 27. Thesis 4 Learning Analytics tells us how learning in classrooms happens
- 28. Students (n=459) Khalil, M., Kastl, C., Ebner, M. (2016) Portraying MOOCs Learners: a Clustering Experience Using Learning Analytics. In: Proceedings of the European Stakeholder Summit on experiences and best practices in and around MOOCs. Khalil, M., Ebner, M., Kopp, M., Lorenz, A., Kalz. M. (Eds.). BookOnDemand, Norderstedt. pp. 265 - 278 1 (n=95) 2 (n=154) 3 (n=206) 4 (n=4)
- 29. Students (n=459) Khalil, M., Kastl, C., Ebner, M. (2016) Portraying MOOCs Learners: a Clustering Experience Using Learning Analytics. In: Proceedings of the European Stakeholder Summit on experiences and best practices in and around MOOCs. Khalil, M., Ebner, M., Kopp, M., Lorenz, A., Kalz. M. (Eds.). BookOnDemand, Norderstedt. pp. 265 - 278
- 30. Learning happens all time Thesis 5
- 31. Lackner, E., Khalil, M., Ebner, M. (2016) How to foster forum discussions within MOOCs: A case study. International Journal of Academic Research in Education. 2(2), DOI: 10.17985/ijare.31432
- 32. Maier, K., Leitner, P., & Ebner, M. (2019). Learning Analytics Cockpit for MOOC Platforms. In Emerging Trends in Learning Analytics. Leiden, Niederlande: Brill | Sense. doi: https://doi.org/10.1163/9789004399273_014
- 33. Leitner, P. , Maier, K., Ebner, M. (2020) Learning AnalyticS Tools for Massive Open Online Courses. accepted: in print
- 34. Why OER-MOOCs?
- 35. Making education accessible to all
- 41. OER-MOOCs facilitate access to education in an innovative way and enable new forms of teaching and learning
- 42. If the content is available as Open Educational Resources, the exchange between different educational situations becomes easy and legal - OER acts as driver
- 43. OER-MOOCs based on Learning Analytics seems to be an important step for (online) education
- 44. Graz University of Technology EDUCATIONAL TECHNOLOGY Graz University of Technology Martin Ebner (Educational Technologist) http://elearning.tugraz.at martin.ebner@tugraz.at Slides available at: This work is licensed under a Creative Commons Attribution 4.0 International License. https://learninglab.tugraz.at/informatischegrundbildung/ @mebner http://elearningblog.tugraz.at Yes, we care :-)