Big Data Toronto 2013

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<cs
Binder
&
Mobile
Apps
Capture
&
Mul<media
Other
Analy<cs
and
Data
Sources
3rd
Party
Applica<ons
Publisher
Content
Authen<ca<on
Systems
SIS
and
HR
Systems
Desire2Learn
Valence
-­‐
Open
Web
Services,
APIs,
Integra<on
Packs
and
Standards

7. Why?∳

8. “As a disruptive innovation—an
innovation that transforms a sector from one
that was previously complicated and
expensive into one that is far simpler and
more affordable—the 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, here’s 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, financial services, health
care, and then ultimately government—
the huge swaths of the economy that
historically have not been addressable
by technology, that haven’t been
amenable to the entrance of Silicon
Valley-style software companies. But
increasingly I think they’re 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 won’t remain
in class?
who won’t re-register?
who won’t pass
a class?
who won’t have
a high GPA?
who won’t pass
a class?
who won’t remain
in a program?
who won’t
graduate?
who won’t get
a job
who won’t 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. Let’s Make Education Dance!
Thank You∳ aessa@mit.edu
http://alfredessa.com
linkedin: alfred essa
twitter: @malpaso