big data in education, desire2learn inc

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Big Data Toronto 2013

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  • 1. Alfred Essa Director, Analytics Research and Strategy Desire2Learn Inc. aessa@mit.edu http://alfredessa.com B(ig) D(ata) in E(ducation)
  • 2. Why? problems we expect to solve What? approach in education Demo student success system
  • 3. Less Data, More Insights
  • 4. Preliminaries
  • 5. Education needs an enduring technology partner Supporting learners lifelong 24/7 service and support 14 available languages Now over 800 employees worldwide Global SaaS capabilities Over 8 Million Clients WW Desire2Learn Inc.
  • 6. Full Suite of Learning Technology Desire2Learn Learning Pla.orm Learning Environment Lifelong ePor.olio Repository & Discovery Advanced Analy
  • 7. Why?
  • 8. As a disruptive innovationan innovation that transforms a sector from one that was previously complicated and expensive into one that is far simpler and more affordablethe rise of online learning carries with it an unprecedented opportunity to transform the schooling system into a student-centric one that can affordably customize for different student needs by allowing all students to learn at their appropriate pace and path, thereby allowing each student to realize her fullest potential. Clayton Christensen
  • 9. Seth Godin As we get ready for the ninety-third year of universal public education, heres the question every parent and taxpayer needs to wrestle with: Are we going to applaud, push, or even permit our schools (including most of the private ones) to continue the safe but ultimately doomed strategy of churning out predictable, testable, and mediocre factory workers?
  • 10. The next stops, I believe, are education, nancial services, health care, and then ultimately government the huge swaths of the economy that historically have not been addressable by technology, that havent been amenable to the entrance of Silicon Valley-style software companies. But increasingly I think theyre going to be. Marc Andreessen
  • 11. Problem: Iron Triangle in Education
  • 12. Quality Cost Access
  • 13. solution: analytics at scale
  • 14. problem: changing business model
  • 15. volume value
  • 16. solution: analytics as accountability
  • 17. problem: diversity of learners
  • 18. homogeneous heterogeneous
  • 19. solution: analytics as personalization
  • 20. problem: education sucks
  • 21. solution: analytics powers interactive, immersive learning
  • 22. conclusion: analytics is focal point of innovation in education
  • 23. +
  • 24. What?
  • 25. Every breath you take Every move you make Every bond you break Every step you take I will be watching you Data Internet Philosopher Sting
  • 26. informationvalue insight Risk Forecasting Predictive Modeling what will happen? STAGE TWO ReportingData Access what happened? what is happening? STAGE ONE Optimization Strategy what do i want to happen? STAGE THREE Analytics Maturity
  • 27. optimization means finding the best path among multiple options
  • 28. who is under-prepared for college? who is under-prepared for class? who wont remain in class? who wont re-register? who wont pass a class? who wont have a high GPA? who wont pass a class? who wont remain in a program? who wont graduate? who wont get a job who wont get a high-paying job? Student Success Lifecycle Identify the Students Understand the Cause Apply Intervention Track Success
  • 29. Demonstration
  • 30. a 360-view of student academic progress, including risk Student Success System
  • 31. interrogate the data understand the problem consult with others prescribe a course of treatment track the success https://fusion2012demo.desire2learn.com/
  • 32. Lets Make Education Dance! Thank You aessa@mit.edu http://alfredessa.com linkedin: alfred essa twitter: @malpaso