This presentation was given by Peter Karlberg of the National Agency for Education (Skolverket) of Sweden at the GCES Conference on Education Governance: The Role of Data in Tallinn on 13 February during the afternoon session workshop on Learning Analytics.

1. Education governance; The role of data
Workshop C: Learning Analytics
Peter Karlberg | Skolverket
peter.karlberg@skolverket.se
twitter: peterkarlberg
linkedin: https://www.linkedin.com/in/peterkarlberg
#laceproject

2. What is learning analytics?
• the measurement, collection, analysis and reporting of data
about learners and their contexts, for purposes of understanding
and optimising learning and the environments in which it occurs
– First International Conference on Learning Analytics And Knowledge (LAK11), Banff, Alberta, Feb 27-Mar 1, 2011
– other terms; Educational data mining (EDM), Big data in education, learner analytics
…..

3. Photo public domain: http://commons.wikimedia.org/wiki/File:DESYNebelkammer.jpg
- Erik Duval
http://erikduval.wordpress.com/2012/01/30/learning-
analytics-and-educational-data-mining/
“collecting traces
that learners leave
behind and using
those traces to
improve learning”

4. Clow, LAK12, 2012

5. School dashboards (Google Images)
• Maybe chop the first slide about this.
5

6. ELLI
Teacher view
6
Buckingham Shum and Deakin Crick, 2012 (LAK12)

7. What data do we have about learners?
• Demographics
• Previous educational experience
• Grades, scores, achievements, struggles
• Attendance, location, gaze
• Software logs
• Online tracking
• Other online activity (tracking)
• … more every week.
7
Photo (CC)-BY-SA AJ Cann https://www.flickr.com/photos/ajc1/15574010080/

8. What can we do with that data?
• Identify learners who need help
– Simple or predictive
• Trigger interventions
– Via teacher, or direct
• Learn which interventions work
• Build a complete cognitive learning system
• Suggest resources or source of help
– Learners like you found this helpful
– This person might be able to help you
8
Photo (CC)-BY-NC Pulpolux https://www.flickr.com/photos/pulpolux/8735428280

9. what should we do?

10. 10
control
Photo (CC)-BY Andy Roberts https://www.flickr.com/photos/aroberts/3035796
surveillance

11. 11
support
Photo (CC)-BY-NC-SA Drew Bennett https://www.flickr.com/photos/abennett96/2710211041
guidance

12. Glasswinged butterfly, ? Greta oro
Photo (CC)-BY-NC-ND by Greg Foster on Flickr http://www.flickr.com/photos/gregfoster/3365801458/
Principles
• Privacy
• Data protection
• Ethics
• Transparency

13. Dutch
perspective
13

14. Example 1: Math Garden (NL)
14

15. A garden that needs maintainens
• From primary school –
• Encourages weekly practice – otherwise the
garden withers
• Rewards: blooming plants and virtual coins
(which can be exchanged)
• Automatically adjusts the difficulty of math
exercises to the ability level of the user
15

16. Studi.se (SWE)
• Videos (also with sub-titles in many languages), texts and
quizzes
• Feedback to both the student and the teacher
16

17. Interactive Flipped Classroom (SWE)
• Based on the flipped classroom method
• Makes the students more active in the
classroom
• But they are still quite passive when looking at
videos
• Technical platform which helps the teacher to
cut the videos in smaller chunks and add
quizzes
• Also possible for students to stop the video
and write questions to the teacher 17

18. Feedback to the teacher
• How many have looked at the video (and
when)?
• How did the group score on the quizzez?
• Which parts did they found (particularly)
difficult?
• Where they confused by the examples?
• Specific questions feeded back to the teacher
before the lesson
18

19. 19
Why do you subtract 4/9? The students can stop the video and
write questions if needed

20. Regional initiative on drop-outs
• Western parts of Sweden
• When do student drop-out from upper
secondary school?
• Can we discover a pattern?
• Using the data – analysing
20

21. www.laceproject.eu
Learning Analytics Community Exchange
• Coordination and Support
• Evidence Hub
• Events
• Publications, briefings, webinars

22. Activities and Achievements
• Capturing the Latest Thinking
– 18 blog posts on LACE website
– Infographic
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23. Evidence Hub
23
• Manage content and
metadata of the web
presence and knowledge
base (the Evidence Hub) to
create a valued and used
resource
• Identify, collect and
synthesise claims and
evidence for the benefits of
learning analytics

24. Evidence Hub – Rationale
• Add value on top of bibliographies (Mendeley)
& machine analysis of LAK Dataset
• Support for practitioners, researchers, managers,
policymakers
• Evidence for or against a proposition / hypothesis
• Propositions developed among partners & at SoLAR
Flare UK
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Photo (CC)-BY Inessa Achmedova https://www.flickr.com/photos/kooklanekookla/1816753147

25. Evidence Hub – Propositions
A. Learning analytics improve learning
outcomes
B. Learning analytics improve learning
support and teaching, including
retention, completion and
progression
C. Learning analytics are taken up and
used widely, including deployment
at scale.
D. Learning analytics are used in an
ethical way
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26. Evidence Hub – Evidence Flow map
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27. Evidence Hub – Map of Evidence
27

28. Evidence Hub – Outlook
• Also capture material with
a lower threshold
– Projects
– Activity
– Opinion and policy
• Easier to submit &
quality control
• Broader view of field
• Not already available elsewhere
• Broader interest
– Helps sustainability beyond
the project
28

29. State of the art of LA in school sector
• little systematic use of data at school level
• more at national and municipal level
• lack of knowledge in the school community
• some interest
• increasing vendor interest – new products
• privacy big issue
• little research found
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30. Thanks!
• Slides made by Doug Clow, Jan Hylén and
myself
30

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