Vortrag im Rahmen der OPCO 12 Veranstaltung zu Learning Analytics

1. Gedanken zu
Learning Analytics
Martin Ebner

2. Horizon Report (2007 - 2012)
http://wp.nmc.org/horizon2011/

3. Educational Data Mining
Educationa data mining (EDM) is a field
that exploits statistical, machine-learning,
and data-mining (DM) algorithms over
the different types of educational data. Its
main objective is to analyze these types
of data in order to resolve educational
research issues.
Romero, C. (2010) Educational Data Mining: A Review of the State of the Art - in:
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE
Transactions on, 40, p. 601 - 618

4. ... there are 11 fields
• Analysis and Visualization of Data,
• Providing Feedback for Supporting Instructors
• Recommendations for Students
• Predicting Student’s Performance
• Student Modeling
• Detecting Undesirable Student Behaviors
• Grouping Students
• Social Network Analysis
• Developing Concept Maps
• Constructing Courseware
• Planning and Scheduling
Romero, C. (2010) Educational Data Mining: A Review of the State of the Art - in:
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE
Transactions on, 40, p. 601 - 618

5. Learning Analytics
Learning Analytics is the use of intelligent
data, learner-produced data, and analysis
models to discover information and social
connections, and to predict and advise on
learning.
George Siemens (2010) http://www.elearnspace.org/blog/2010/08/25/what-are-
learning-analytics

6. Learning Analytics
Learning Analytics is about collecting
traces that learners leave behind and
using those traces to improve learning.
Erik Duval (2012) http://www.slideshare.net/erik.duval/learning-
analytics-13050389

7. It‘s all about
http://www.flickr.com/photos/neeravbhatt/6995946039

8. Interpretation
Information
http://www.flickr.com/photos/auuep/3357824170

9. Beispiel
... ein scheinbar simples Problem ...

10. Beispiel
... das kleine EinmalEins für
Volksschulkinder ...

11. http://youtu.be/P9qVWtVWYQI

12. http://mathe.tugraz.at

13. http://mathe.tugraz.at

14. Funktionsweise des Algorithmus
!
http://mathe.tugraz.at

15. Analyse
• Beobachtungs
zeitraum:
1,5 Monate
• n = 230
• > 750 Sessions
• > 28.000
generierte
Beispiele
• > 6 Minuten /
Session im
Schnitt
!
http://mathe.tugraz.at

16. Analyse
! !
http://mathe.tugraz.at

17. Analyse - Alle BenutzerInnen
!
http://mathe.tugraz.at

18. Analyse - Alle BenutzerInnen
!
http://mathe.tugraz.at

19. Detailanalyse
... Lernfortschritt
!
!
... Lernrate
http://mathe.tugraz.at

20. http://mathe.tugraz.at/~mickname/access/login

21. Learning Analytics ist die Interpretation
von lernerspezifischen Daten um den
individuellen Lernprozess gezielt zu
verbessern.
Martin Ebner & Martin Schön (2012)

22. Potenzial ist heute noch schwer
abschätzbar, da mit zunehmender
Datenmenge gänzlich neue Sichtweisen
gewonnen werden können.
ABER ...
Martin Ebner & Martin Schön (2012)

23. Peter Purgathofer (2010), Gesellschaftliche Aspekte der Informationstechnologie

24. Peter Purgathofer (2010), Gesellschaftliche Aspekte der Informationstechnologie

25. Slides available at: http://elearningblog.tugraz.at
SOCIAL LEARNING
Computer and Information Services
Graz University of Technology
Graz University of Technology
Martin Ebner
martin.ebner@tugraz.at
mebner http://elearning.tugraz.at