Mootnz13 Moodle Analytics
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The document discusses various perspectives on analytics within the Moodle LMS, including definitions and classifications of learning and academic analytics, and their benefits to different stakeholders. It highlights challenges related to data reliability, the need for enhanced data standards, and ongoing projects aimed at improving analytics capabilities. It also outlines Moodle's roadmap for building foundational elements necessary for effective educational analytics.
Mootnz13 Moodle Analytics
- 1. Moodle & Analytics – a matter of perspective Mark Drechsler
- 2. What do we mean by ‘analytics’? How can we classify different kinds of analytics? What are the challenges we face in the LMS? What is happening in the Moodle project (and beyond) in relation to analytics? This session
- 3. “…exploring the unique types of data that come from educational settings, and using those methods to better understand students.” A broad definition Source: Wikipedia entry on Educational Data Mining
- 4. However – many different perspectives
- 6. Type Level/object Who benefits? Learning Analytics Course level Learners, Academics Faculty level Learners, Academics Academic Analytics Institutional Administrators, Funders, Marketing Regional Funders, Administrators National and international National governments, Educational authorities Multiple perspectives Source: http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and-education Penetrating the Fog: Analytics in Learning and Education – Phillip Long & George Siemens
- 7. Type Level/object Who benefits? Learning Analytics Course level Learners, Academics Faculty level Learners, Academics Academic Analytics Institutional Administrators, Funders, Marketing Regional Funders, Administrators National and international National governments, Educational authorities Multiple perspectives Target Consumer Source: http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and-education Penetrating the Fog: Analytics in Learning and Education – Phillip Long & George Siemens
- 11. One extreme: LMS only data analysis Simple to implement Losing ‘market share’ of data over time leading to lower reliability of analysis Other extreme: Learning ecosystem Complex – needs open standards model and external repository The holy grail of educational analytics? Analytics Scope
- 13. One extreme: Manual analysis Run reports, analyse data, take actions Other extreme: Automated analysis Automated analysis against known metrics Alerts & notifications to consumers Analytics automation
- 14. Goal: Finding out you have a problem Before you have a problem.
- 15. This gives us a framework for considering perspectives on analytics
- 17. 1. Engagement Analytics http://docs.moodle.org/22/en/Engagement_Analytics_Plugin
- 19. Where to from here?
- 20. Only one part of the story Lecture capture? Library systems? Virtual classroom? Social learning? Logs in Moodle are good, but not comprehensive ‘LMS only’ analysis problems
- 21. Data gets big(gish) ‘Typical’ Moodle uni generates between 50,000,000 and 100,000,000 log records in a year LMS only analysis problems
- 22. Moodle analytics roadmap: ‘Foundation building’
- 23. Solution part 1: abstraction Log store Adapted from http://docs.moodle.org/dev/Logging_2 Log data
- 24. What they are saying: SOLAR: “Development of a common language for data exchange*” – first item on their roadmap IMS: “The … ‘holy grail’ of data interoperability is an agreed upon “learning/progress map” that all tools and assessments could populate.**” Solution part 2 - standards * source: http://solaresearch.org/OpenLearningAnalytics.pdf ** source: http://www.imsglobal.org/blog/?p=258
- 25. Increase amount of data gathered in Moodle’s logs to support more in-depth analytics. Solution part 3 – more data!
- 27. Once ‘foundation’ is stronger, more plugins can be built more easily for more purposes And then…
- 28. Plug-in analytics Log store Adapted from http://docs.moodle.org/dev/Logging_2 Log data In-LMS analytics Externalanalytics
- 29. Earlier effort: Monash Uni/NetSpot project implementing ‘engagement analytics’ plugin in 2012: http://bit.ly/MoodleAnalytics
- 30. This year’s project: Macquarie Uni, UNSW and NetSpot initiating a project to develop student centric analytics in Moodle