High level overview of Moodle and analytics presented by Mark Drechsler at the 2012 Moodleposium conference in Canberra, Australia.

1. Moodle and Analytics
A question of perspective

2. So does Moodle 'do' analytics, or what?
Yes.
Or no.
Depending on your idea
of 'analytics'.

3. Wikipedia has a nice definition:
"exploring the unique types of data that come
from educational settings, and using those
methods to better understand students"
- Wikipedia entry for Educational Data Mining

4. Or another way to look at it...
Looking at
behaviours in the
past
In order to predict
the future.

5. Such a broad definition...
Right now: less interested in telling people
what learning analytics are...
...more interested in understanding some of
the dimensions which make up people's
perceptions.

6. Learning analytics: Dimensions
The level of automation
The consumer
The target
The scope

7. Level of automation
Manual Automated inference
inference System uses
Raw data shown, predefined rules to
users draw their predict behaviour.
own conclusions.

8. The consumer
Personal Systemic
Academic System
Student Organisation

9. The target
Personal Systemic
Subject Organisation
Student Faculty

10. The scope
Integrated
Isolated Data extracted from
Data sourced solely the LMS and
from within the combined with other
LMS. sources.

11. Which data drive Moodle's
analytics?
Moodle logs:
Capture in real time most actions a user
performs within the system.

13. From these data, lots of
'localised' reports are
possible.

14. Four questions to ponder:
1. Are all areas of my subject getting traffic?
2. Are my students active in critical parts of the
subject?
3. Are my students completing the important
parts of the subject?
4. Can I set up an automated early warning
system?

15. Live demonstration of four tools:
1. Activity report
2. Participation report
3. Activity completion report
4. Engagement analytics report

16. Engagement Analytics
in more detail

17. Engagement Block

18. Engagement report

19. Engagement 'trigger' settings
Set with
'sensible'
defaults,
but can be
modified at
the course
level.

20. Dimensions for these analytics?
Automation: Mostly no,
a little yes.
Consumer: Mainly
Lecturer focused.
Target: Subject focused.
Scope: Isolated.

21. In other words, where to from here?
A few paths of attack:
1. More Moodle plugins
2. Third-party tools with integration points
3. Data Warehouses

22. Moodle plugins
1. Moodle Progress Bar
2. Configurable reports
3. Analytics & Recommendations block
4. Totara reports (under investigation)
5. Course Dedication block
6. Probably others...

23. Dimensions for these analytics?
Automation: A mixture
of both.
Consumer: Mainly
Lecturer focused.
Target: Subject or
individual focused.
Scope: Isolated.

24. Third-party products
1. Blackboard Analytics
2. Starfish EARLY ALERT
3. Probably others...

25. Dimensions for these analytics?
Automation: Mostly
automated.
Consumer: More
focused at decision-
makers.
Target: Various.
Scope: Integrated.

26. Data Warehouses
Virtual
Moodle
Rooms
e-
SIS
Portfolio
Lecture Library
Capture Data System
Warehouse +
Analytics

27. Data Warehouses:
Probably the right way of doing learning
analytics 'properly'...
... and also the hardest.
Numerous NetSpot clients already undertaking
DW projects with data sourced from Moodle.

28. Dimensions for these analytics?
Automation: Various.
Consumer: More
focused at decision-
makers.
Target: Various.
Scope: Integrated.

29. Question:
Where do we focus our efforts in 2013?