2. “Improvement in post secondary
education will require converting
teaching from a solo sport to a
community based research activity.”
Herbert Simon
Nobel Laureate & CMU Professor
oli.cmu.edu
3. OLI Generously Funded by:
LearnLab is funded by The
National Science Foundation
award number SBE-0836012.
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5. What is the Open Learning Initiative?
Scientifically-based online learning environments based on the
integration of technology and the science of learning with
teaching. OLI is designed to simultaneously improve learning
and facilitate learning research.
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9. The Open Learning Initiative
Established in 2002 to produce and improve exemplars of
scientifically-based online courses that enact instruction
and support instructors. Current goals:
• Support better learning and instruction with highquality, scientifically-based, classroom-tested online
courses and materials.
• Share our courses and materials openly and freely so
that anyone can learn.
• Develop a community of use, research, and
development.
oli.cmu.edu
10. Science
An approach to
designing, developing, d
elivering and improving
learning experiences
Technology
Teams
Data
• Science of Learning
• Evaluation
• Improvement
• Platform
• In-course Affordances
• Team-based Development
• Communities of Research and Use
•
•
•
•
Capture
In-course Use
Iterative Improvement
Research
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13. What is a Cognitive Tutor?
A computerized learning environment whose
design is based on cognitive principles and whose
interaction with students is based on that of a
(human) tutor—i.e., making comments when the
student errs, answering questions about what to
do next, and maintaining a low profile when the
student is performing well.
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14. Principles Derived from Learning Science
•
Goal directed practice and
targeted feedback are critical to
learning
Learners receive support in the
problem-solving context
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16. Benefits of Personalized & Adaptive Learning
Strong evidence that personalized and adaptive technologies can improve student
outcomes
Potential Pedagogical Benefits*
Formative Evaluation (d=.90)
Acceleration (.88)
Effective Feedback (.73)
Meta-cognition (.69)
Mastery Based Learning (.58)
Concept Mapping (.57)
Interactive content (.52)
800+ meta analysis on
achievement
Standard deviation is effect
size where d = 1.0
(i.e. improvement of
learning by at least 50%)
Average effect size d=.40
When d is > .40
excellent achievement gains
*Source: John Hattie’s Visible Learning
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25. OLI Review:
• Apply learning science research and scientific method to
course development, implementation and evaluation.
• Develop interactive learning environments
collaboratively (teams of content experts and
novices, learning scientists, HCI, software engineers).
• Feedback loops for continuous improvement.
• Communities of use, evaluation and improvement.
What Difference Does it Make?
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26. Accelerated Learning Results
• OLI students completed course in half the time with half the
number of in-person course meetings
• OLI students showed significantly greater learning gains (on
the national standard “CAOS” test for statistics knowledge)
and similar exam scores
• No significant difference between OLI and traditional
students in the amount of time spent studying statistics
outside of class
• No significant difference between OLI and traditional
students in follow-up measures given 1+ semesters later
M. Lovett, O. Meyer, & C. Thille, C., “The Open Learning Initiative: Measuring the effectiveness of the OLI
statistics course in accelerating student learning,” Journal of Interactive Media in Education (2008).
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28. Other Class Results
Large Public University: OLI Online vs. traditional. OLI
99% completion rate vs 41% completion rate traditional.
Community College accelerated learning study in Logic:
An instructor with minimal experience in logic. Students
obtained high levels of performance on more advanced
content (~33%) not covered in traditional instruction.
OLI stoichiometry course: The number of interactions with
the virtual lab outweighed ALL other factors including gender
and SAT score as the predictor of positive learning outcome.
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29. Since 2006
Course Use
Development
• 117,963 Course Enrollments
(Academic)
• 44 Academic and 9 CMU
service courses have been
created.
• Used by 1809 Instructors in
1050 Institutions
• By 104 contributing Faculty
from 55 Institutions
• 1,148,807 Independent
Learner Enrollments
(Registered and Anonymous)
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30. In Practice at Carnegie Mellon
• Computing @ Carnegie Mellon
• Visual Communications
Design
• Biochemistry
• French I and II
• Engineering Statics
• Empirical Research Methods
• Logic and Proofs
• Casual and Statistical
Reasoning
• Speech
• Prose Style
• Immunology
• Secure Coding
•
•
•
•
•
•
•
•
•
•
•
Media Programming
Chemistry
Chinese
Arabic
Spanish
Cloud Computing
Statistical Reasoning
Economics
Argument and Interpretation
Principles of Computing
Anatomy and Physiology
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33. Looking Ahead
•
•
•
•
Extending the Community
Larger Consortium
Spectrum of Use
Adapt and Extend
•
•
•
•
Platform
Opening the Approach
Tools (research, data, development and science)
Frameworks for Maturity and Evaluation
• Key: Meeting Where They Live
oli.cmu.edu
42. “Changing circumstances
mandate that we shift the
focus of higher education
policy away from how to
enable more students to afford
higher education to how we
can make a quality
postsecondary education
affordable.”
- Clayton Christensen
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43. Not only is there a need to seek entirely new
approaches, insights and models, but that need
is urgent. New approaches offer scalable
processes that help colleges lower cost-perdegree and make significant improvements to
student learning outcomes and retention rates.
Insights from the science of learning
combined with advances in information
technology and alternative models of
course design, implementation, and
evaluation show promise in supporting
traditional higher education to change
the production function and meet the
seemingly impossible challenge.
-Candace Thille, Director OLI
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44. I was one of ten university presidents
invited to the White House to meet with
President Barack Obama and Secretary of
Education Arne Duncan to discuss a
critical issue: how to reduce costs and
improve the productivity of U.S. higher
education. The other presidents there
represented some of the nation’s largest
public university systems (Maryland, New
York, and Texas among them).
I was there because Carnegie Mellon
is the leader in creating technology
for education.
-Dr. Jared L. Cohen, CMU President
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45. I am not a futurist but rather a maddeningly practical
person who rarely has visions—and when I do they are
usually the result of having had a bad meal! But let me
put such predilections to one side and ask you to join me
in imagining, just for a moment, how the intelligent
harnessing of information technology through the
medium of online learning might alter aspects of
university life as we know it. Can we imagine a university
in which:
•
faculty collaborate more on teaching (with technology
serving as the forcing function)?
•
faculty devote more of their time to promoting the
“active learning” of their students and are freed from
much of the tedium of grading
•
students receive more, and more timely, individualized
feedback on assignments
•
technology extends the educational process
throughout one’s life through the educational
equivalence of booster shots? And, ideally:
•
a university in which institutional costs and tuition
charges rise at a slower rate?
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Editor's Notes
Soo-mee-mah-sengNihongoga hah-nah-shmaseng
Specific learning challenges as defined by faculty, explored by learning scientists
