2. So many users…So much data!But where are the analytics?
3. What is it that we actuallymean when we say‘analytics’?
4. 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
5. Or another way to look at it... Looking at behaviours in the past In order to predict the future.
6. Such a broad definition...Right now: we’re less interested in telling people what learning analytics are... ...more interested in understanding some of the dimensions which make up peoples perceptions.
7. Learning analytics: DimensionsThe level of automation The consumer The target The scope
8. 1. Level of automation Manual Automated inference inferenceRaw data shown, System uses users draw their predefined rules to own conclusions. predict behaviour.
9. 2. The consumer Personal Systemic Academic SystemStudent Organisation
10. 3. The target Personal Systemic Unit OrganisationStudent Faculty
11. 4. The scope Isolated Integrated Data extracted fromData sourced solely the LMS and from within the combined with other LMS. sources.
12. Which data drive Moodlesanalytics?Moodle logs: Capture in real time most actions a user performs within the system.
13. Question: can we draw more sophisticated inferences?
14. Extension Example:Engagement Analytics Courtesy of a joint project between Phillip Dawson of Monash University and NetSpot, supported by the NetSpot Innovation Fund.
15. Engagement trigger settings Set with sensible defaults, but can be modified at the course level.
16. Engagement Block
17. Engagement report
18. Dimensions for these analytics? Automation: Mostly no, a little yes. Consumer: Mainly Lecturer focused. Target: Subject focused. Scope: Isolated.
19. Where to from here?A few paths of attack:1. More Moodle plugins2. Third-party tools with integration points3. Integrated Data Stores