Launching and leveraging adaptive learning: research, efficacy, and results presentation at GlobalMindset Sydney, Australia

1. Artificial Intelligence (AI),
Personalization and Learning:
Will it Work?
Karen Vignare, PhD, MBA
CEO & Founder, KV Consulting
17th Global Mindset conference on
Emerging Trends in Learning & Working
Sydney - 03rd August 2016

2. Agenda
• About me
• Separating fact from fiction in AI
• What do we know about adaptive learning technologies?
• Piloting adaptive learning tools
• The research results
• Lessons Learned

3. Karen Vignare, PhD, MBA
• 20 years experience online, emerging technologies in learning
• Started online programs, worked with international universities
• Managed blended learning, MOOCs, and adaptive learning projects
• Extensive research portfolio
• More about me at LinkedIn, https://www.linkedin.com/in/karen-
vignare

4. AI for Learning: Definitions
• The central problems (or goals) of AI research
include reasoning, knowledge, planning, learning, natural language
processing (communication), …….Approaches include statistical
methods, computational intelligence, soft computing (e.g. machine
learning), and traditional symbolic AI.
• Many tools are used in AI, including versions of search and
mathematical optimization, logic, methods based on probability and
economics. The AI field draws upon computer
science, mathematics, psychology, linguistics, philosophy,
neuroscience and artificial psychology.
Source: Wikipedia

5. New technologies for learning
• Personalization does not have to mean technology but it most cases
organizations are leveraging technologies
• (planning, advising, relationship management, courses, analytics and tracking to personalize)
• Adaptive learning and digital courseware technologies focus more on
personalizing or adapting the course content and assessments to the
individual students
• The tools rely on algorithms that direct learners based on the content and
the paths they choose
• For implementers/instructors reading the analytics and using that
information is a critical new role

6. What does the research say?
• Connected to progress made in Computer Aided Instruction (circa
1980s) and research pointed to increased effectiveness
• Meta-analyses showed promise and effectiveness but disagreement
on approach and value remained
• Internet slowed gains as more people explored constructivism,
connectivism
• Current online tools seem to be at same effectiveness as three
decades ago…
• Costs could be lower, algorithms more powerful, but design and computer
modeling are still debatable

7. Current State: Most Rely on LMS Technology
• LMS is still key to supporting online learning in higher education and
other tools are slowly being tested and brought in

8. © 2016 IMS Global Learning Consortium, Inc. All Rights Reserved
The Challenge & The Opportunity
The future is
Now:
Leveraging
digital tools
& resources
to improve
instruction &
outcomes

9. Another View of Digital Learning Environment

10. © 2016 IMS Global Learning Consortium, Inc. All Rights Reserved
Current State of Adaptive Learning Success
Next Generation Digital
Learning Environment
Courseware in Context
Framework
Reported pilots
Interoperability and
Integration
Latest version compliance
LTI
Most report easy
interoperability
Personalization Critical within system No clear standard match
so reports are more on
reported outcome success
Analytics, Advising, and
Learning Assessment
Caliper and LTI Needs improvement as
data exchange is not
widely used (yet)
Collaboration Currently not as important
Accessibility and Universal
Design
Critical to scale Major concerns (not just a
vendor issue)

11. Gartner Education Hype Cycle 2015

12. Some of the Companies in the Space
Source: Tyton Partners

13. Source: https://www.edsurge.com/higher-ed/special-projects/dl/orientation

14. Source: http://coursewareincontext.org/

15. Leaders/Managers are Underprepared
• The business is changing—accountability, stakeholders are all
demanding more
• Outdated systems and processes
• Very little training for administrators
• Many became leaders decades ago and are not capable in current
business operations, technologies and processes
• Higher education does not always attract the best “business” people
but does attract “researchers/scholars”

16. Piloting Adaptive Learning
• At last job, used six different adaptive tools
• Vendors range from publishers, platform tools, to university created
ones
• Increased technology sophistication
• Focus is on content variety, assessment breadth, and immediacy
• As technology substitutions for online learning, mixed results
• Within tool correlations are very promising

20. Content Map
for Types of
statistical
studies
Source:
https://www.khanaca
demy.org/exerciseda
shboard

23. Lessons Learned
The future of adaptive learning in higher education depends on the
commitment level of universities
• Preparation...really take the time to understand the power of the tool, take
a class
• Skill up faculty, instructional staff and technology team
• Pick your course(s) based on solving problems (is content difficult, would
more student practice help, does immediacy help students
• Build content maps and you will need more content than you currently
have (unless you use pre-packaged)
• Learn to use the dashboard
• Iterate probably at least three times....

24. Questions
Karen Vignare, PhD, MBA
kvignare@gmail.com
240.462.2160