1. Learning Analytics
foundation of mass personalized education
Sander Latour

2. Bedankt voor de uitnodiging
Thank you for inviting me

5. Roadmap to the beer
The educational model
The revolution
The technology
Learning Analytics
The future of learning

6. Roadmap to the beer
Point out the irony of this talk
Walk out and get a beer
Alternative

7. What characterizes our
model of education?
High school University

8. Traditional education
Teacher-centric
One-size fits all
Standardized
Passive
Individually
Assessment-centric
Certain ordering of topics

10. Does the system work?
Did it work for you? For your friends?
For everybody in society?

11. Revolution in education
"the world of education is stirring"

15. Concerns on the surface

16. http://www.wearethepeoplemovie.com

17. School
Society
19th
21st

18. Most watched?

19. Sir Ken Robinson

24. Big Breakthroughs Happen
When What Is Suddenly
Possible Meets What Is
Desperately Necessary
- Thomas L. Friedman

25. Or: Old Wine In New Bottles

26. technically
So what is suddenly possible?

27. There are many developments
that improve education
without (explicitly) using technology
Wait a minute

28. Online learning
Transformation or Digitalization?

29. Massive Open Online Course
Ever heard of MOOCs?

31. Not all Online Learning...
...is massive, open or even a course

32. Web-based ITS MOOC

33. Web-based ITS MOOC

34. Learning Analytics
foundation of mass personalized education

35. Many students
Increasing data
How can you personalize?

41. Learning Analytics is the measurement, collection,
analysis and reporting of data about learners and their
contexts, for purposes of understanding and optimizing
learning and the environment in which it occurs.

42. Learners
Data
Analysis
Intervention
The Learning Analytics cycle
Doug Clow. 2012. The learning analytics cycle: closing the loop effectively.
In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK '12)

43. Arnold, K. E. (2010). Signals: Applying Academic Analytics.
Educause Quarterly, 33(1), n1
Purdue Course Signals

44. Learning
Analytics
Educational
Datamining
Academic
Analytics

45. Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics
in learning and education. Educause Review, 46(5), 30-32.

46. Learners
Data
Analysis
Intervention
The Learning Analytics cycle

47. Learners
Data
The Learning Analytics cycle

48. Browsing behavior
Chat/forum/blog posts
Comments on chat/forum/blog posts
Likes/ratings
Answers/mistakes in quizzes
Time spent on task
Requesting hints
Sharing of resources
Social interactions
Drafts of end products
Location
Body sensors
Environment/context
Video recording of the learning
Possible data sources

49. Learners
Data
Analysis
The Learning Analytics cycle

50. Recommendations for material
Recommendations for pupils / mentors
Prediction of students at risk
Finding bottlenecks in content
Updating cognitive / user models
Analysing video control behavior
Social Network Analysis
Discourse Analytics
Head pose tracking
Tracking speech at a table
Typical analysis

51. Learners
Data
Analysis
Intervention
The Learning Analytics cycle

52. Reflection
Showing a prediction of success
Overview of what you did
Overview of what the group did
Insight in the group process
Suggestion
Learning material
Intelligent Curriculum
Potential partners
Potential mentors
Better learning approach
Intervention via student

53. Reflection
Showing a prediction of success
Overview of what a student did
Overview of what the group did
Insight in the group process
Suggestion
New learning material
Potential partners
Potential mentors
Better teaching approach
Intervention via teacher

54. Adaptive learning material
Adaptive navigation
Adaptive tests
Clean-up of bad material
Automatic intervention

55. Learners
Data
Analysis
Intervention
The Learning Analytics cycle

57. What are potential issues or downsides?
Critical thinking

58. Privacy
Lack of data
Pedagogical effect
Jumping to conclusions
Enforcing the factory model
Tool-centric vs. Learner-centric
Potential issues

59. What could possible scenarios be?
The future of learning

61. Are droids taking our jobs?

62. Official sources of information

63. People that inspired me
Sir Ken Robinson Noam Chomsky Eric Mazur
George Siemens Erik Duval Salman Khan

64. I'm not saying everything
should be changed
I'm saying everything
should be questioned

65. Thank you
http://www.slideshare.net/sanderlatour