IADIS: Shanghai


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IADIS: Shanghai

  1. 1. Envisioning a system-widelearning analytics platform George Siemens December 8, 2011 Shanghai, China
  2. 2. Data is an asset
  3. 3. Data revealsour sentiments,our attitudes,our social connections,our intentions,and what we might do next.
  4. 4. http://online.wsj.com/article/SB1000142405311190388560 4576486330882679982.html
  5. 5. What’s different today?volume (apparently, there’s lots of data)velocity (processing capacity)variety (internet of things, social media)
  6. 6. Applying big data and analytics in education
  7. 7. Learning analytics is themeasurement, collection, analysis andreporting of data about learners and theircontexts, for purposes of understanding andoptimizing learning and the environments inwhich it occurs. Society of Learning Analytics Research
  8. 8. “A university where staff and studentsunderstand data and, regardless of its volumeand diversity, can use it and reuse it, store andcurate it, apply and develop the analytical toolsto interpret it.”
  9. 9. Roots of learning analytics Statistical methods Intelligent EDM Tutors Big Data Personalization Business Learning AdaptiveIntelligence learning Analytics
  10. 10. We can make great progress with analytics asindividuals, but the nature of ‘big data’ requiresa systemic focus
  11. 11. SNA: in Moodle introduction forumLimitedinteraction.Most areisolated
  12. 12. Source: King James Bible Old and New Testaments
  13. 13. What is behind a simple visualization?
  14. 14. Tools for analytics- Single functionality tools (SNAPP)- Multi-function tools (ManyEyes, Gephi)- Visualization (Tableau)- Existing research tools (SPSS, Wolfram)
  15. 15. Acquisition: how do we get the data – structuredand unstructured?Storage: how do we store large quantities?Cleaning: how do we get the data in a workingformatIntegration: How do we “harmonize” varying datasets togetherAnalysis: which tools and methods should be used?Representation/visualization: tools and methods tocommunicate important ideas
  16. 16. Many tools are currently stand alone and singlefunctionality(anyone remember learning managementsystems in the late 1990’s?)
  17. 17. PlayersStartups (Grockit, Knewton)Existing vendors (Cisco, Catatel)Systemic learning analytics players (iStrategy)(they get bought up quickly)
  18. 18. Check my activity Predictive Analytics Reporting
  19. 19. To date, asystem-wide open source analytics platformis NOT available.We want to change that.
  20. 20. Given how important analyticsare…maybe we should start with openness
  21. 21. The Vision:Open Learning Analytics Architecture
  22. 22. OLA: An open, extensible platform for researchers, educators, and administrators for broad-scale analytics in education and learning.
  23. 23. Principles of a systems-wide analytics tool1. Algorithms should be open, customizable forcontext2. Students should see what the organization sees3. Analytics engine as a platform: open for allresearchers and organizations to build on4. Specific analytics strategies and tools: APIs5. Integrate and connect with existing open tools6. Modularized and extensible
  24. 24. 33
  25. 25. Privacy & EthicsJust because we can…should we? Particularly due to the exponential insightPossible with integration of multiple data sets
  26. 26. Getting involved
  27. 27. http://www.solaresearch.org/
  28. 28. http://lak12.sites.olt.ubc.ca/ April 29-May 2, 2012 Vancouver
  29. 29. Open online course: Learning Analytics January 23 - March 17, 2012 http://www.solaresearch.org/ Simon Shane Dawson Erik Duval Dragan Gasevic George SiemensBuckingham Shum
  30. 30. http://www.educationaldatamining.org/
  31. 31. change.mooc.ca Twitter: gsiemens www.learninganalytics.nethttp://www.solaresearch.org/