1. Innovations in Higher Education Learning
Bror Saxberg
CLO, Kaplan, Inc.
February 8, 2012

2. What’s new for learning?
Overview
Cognitive Task Analysis
Kaplan Way – Kaplan University Course Redesigns
Q and A
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3. Bror Saxberg
Chief Learning Officer, Kaplan, Inc.
• Integrating the design, building, monitoring, and improvement of learning
environments; individualize learning experiences using our scale; and,
ultimately, drive greater student career success.
• Former CLO for K12, Inc. – structured use of technology, cognitive
science, on-line and off-line materials for 1,700 teachers, 55k students
• Former Publisher and General Manager for DK Multimedia, Inc.
• Management consultant with McKinsey & Company
• Education:
• Ph.D. in Electrical Engineering and Computer Science from MIT
• M.D. from Harvard Medical School
• M.A. in Electrical Engineering and Computer Science from MIT
• M.A. in Mathematics from Oxford University
• B.S. in Electrical Engineering and B.S. with Honors in Mathematics from the
University of Washington
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4. What Our Students Told Us They Want
Brand
Promise
Brand
Pillars
We strive to make We are dedicated We move quickly We are here to
education as to getting you the with constant help you achieve
personalized to you results that matter innovation to success at critical
Pillar as in the time that better meet your milestones along
Definitions possible−tailoring matters. needs. your educational
our courses around journey.
your individual
needs.
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5. To respond, consider structuring key initiatives to take
advantage of what’s known about learning – and data
Rapidly test
and scale
learning
innovations
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6. What’s new for learning?
Overview
Cognitive Task Analysis
Kaplan Way – Kaplan University Course Redesigns
Q and A
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7. Employers actually expect job applicants to lack the
occupational/technical skills required to do the job…
Do you expect job applicants to be lacking specific occupational
skills or technical skills?
• Slightly over half of all
respondents (52.8%) expected
that job applicants would lack
occupational skills
• In healthcare, where
occupational certifications and
licensures are required, over
68% of respondents expect that
job applicants would lack
occupational skills
March 2011 Workforce Connections, Inc. survey of employers in western Wisconsin. Over 400 employers from
all 8 counties responded to the survey. All sizes of businesses were represented with the majority of responses
coming from businesses with less than 50 employees.
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8. Cognitive Task Analysis (CTA) may provide answers
• CTA is an interview strategy for capturing how highly successful
experts perform complex tasks in a variety of settings
• Goal is to develop authentic demonstration and practice
opportunities for how to perform at expert levels
• Experts are interviewed who 1) have recent (past 2-3 mo.)
experience, 2) are consistently successful, and 3) are NOT trainers.
• Interviews are done with 3-4 experts to unpack their strategies;
these are merged to make an efficient approach suitable for training
• A range of problem examples or performance scenarios are
collected from the experts for use in instruction as well
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9. Medical Assistant current course content:
Pharmacology course
Diseases - human body
X = substantial content; x = ancillary content
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10. MA CTA: Identifies key tasks/skills performed by experts
Original content New focus
• Tie to domain tasks as
identified by experts
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11. MA Program: Skills addressed in new sequence
New focus
• Tie to domain tasks as
identified by experts
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12. MA Program: Skills addressed in new sequence
• Tie to domain tasks as
identified by experts
• Repeated use of skills
across courses
B: Begin; A: Advanced; R: Reinforce
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13. MA Program: New courses include previous content
• Tie to domain tasks as
identified by experts
• Repeated use of skills
across courses
• Original concepts spread
across task instruction,
not confined to courses
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14. What’s new for learning?
Overview
Cognitive Task Analysis
Kaplan Way – Kaplan University Course Redesigns
Q and A
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15. A lot is known about what drives learning now
Instructional Events Student
Learning Events
(in the learning (hidden - inside students’ Performance
environment) minds) (observable -indicates
knowledge)
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16. A lot is known about what drives learning now
Instructional Events Student
Learning Events
(in the learning (hidden - inside students’ Performance
environment) minds) (observable -indicates
knowledge)
Knowledge
Motivation
Metacognition
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17. A lot is known about what drives learning now
Instructional Events Student
Learning Events
(in the learning (hidden - inside students’ Performance
environment) minds) (observable -indicates
knowledge)
• Explicit: Information, Explanation, • Explicit/Declarative/Conceptual/What • Response accuracy/errors
Examples, Demos • Implicit/Procedural/How • Response fluency/speed
• Implicit: Practice tasks/activities • Knowledge Components (Procedures • Number of trials
Knowledge (prompts and response) + Facts, Concepts, Principles, • Amount of assistance (hints)
• Diagnosis and feedback Processes) • Reasoning
• Orientation/Inoculation • Value beliefs • Behavior related to
• Monitoring • Self-efficacy beliefs • Starting
Motivation • Diagnosis and treatment: • Attribution beliefs • Persisting
Persuasion, Modeling, • Mood/Emotion • Mental Effort
Dissonance • Self-reported beliefs
• Structure • Planning, Monitoring • Amount of guidance
• Guidance • Selecting, Connecting required/requested
Metacognition
See: Koedinger, K.R., Corbett, A.T., and Perfetti, C. (2010). The Knowledge-Learning-Instruction (KLI) Framework:
Toward Bridging the Science-Practice Chasm to Enhance Robust Student Learning
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18. Task-centered instruction
• Move from simple to increasingly difficult tasks – NOT “PBL” sink or swim
• Teach everything needed for each task
• Fade coaching/support over time
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19. ID can change instructional outcomes at scale
Principle Description Effect size
(s.d. units)
Multimedia Use relevant graphics and text to communicate content 1.5
Contiguity Integrate the text nearby the graphics on the screen – avoid covering or separating 1.1
integrated information
Coherence Avoid irrelevant graphics, stories, videos, media, and lengthy text 1.3
Modality Include audio narration where possible to explain graphic presentation 1.0
Redundancy Do not present words as both on-screen text and narration when graphics are present .7
Personalization Script audio in a conversational style using first and second person 1.3
Segmenting Break content down into small topic chunks that can be accessed t the learner’s 1.0
preferred rate
Pre-training Teach important concepts and facts prior to procedures or processes 1.3
Etc. Worked examples, self-explanation questions, varied-context examples and ??
comparisons, etc.
Source: E-learning and the Science of Instruction, Clark and Mayer, 2nd ed., 2008
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20. Impact is not small!
1 sd
50% 84%!
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21. Instructional Design process should follow evidence
The evidence about learning points to a sequence of activities that
optimizes learning. Design goes one way, delivery the other.
Design
Learning
Overviews Information Examples Practice Assessment
Outcomes
Guidance (for motivation and metacognition)
Delivery
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22. In 2011 KU and KLI launched a course redesign pilot
1. Apply “Kaplan Way” evidence-based instructional design to several
Kaplan University courses (high volume, needed improving):
2. Deliver the courses in a simplified e-College template.
3. Develop replicable/scalable process, templates, technology.
4. Evaluate the impact on student outcomes
•Pilot 1: August 3 – October 12
•Pilot 2: October 19 – December 28
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23. The student experience: before and after
Read, Write, Discuss
• Outcomes and content sometimes Prepare, Practice, Perform
loosely aligned • Outcomes and content precisely aligned
• Limited demonstrations, worked • Frequent demonstrations,
examples, and practice worked examples, practice, feedback
• General assessment rubrics • Detailed scoring guides
• Reliance on discussion boards • Evidence-based support for motivation
• Limited support for motivation • Instructor coaching
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24. Results: Significant learning and business impact from KU
course redesigns – and more to come
Learning impact Financial impact
Higher instructor satisfaction: 3% retention gain
• Instructors see benefits of design; instructor •Significant benefit to learners and university
materials/support for facilitator role
14% gain in “student success”
Lower student satisfaction:
• Courses more demanding and time
consuming
Higher retention, less withdrawals:
• Support for at-risk students to stay engaged
More time-on-task:
• Students in pilot versions of courses spend
more time online in course
Better learning outcomes:
• Pilot students earn higher CLA scores and
higher scores on common assessments
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25. The pilot courses delivered an 14% difference in student
success rate—a 50% increase over control courses
Pilots 1 and 2 combined analysis: Group differences in student “success”
“Success” = CLA Average >=4 AND passed course AND retained to next term
Controlling for differences in course, students, instructors and seasonality
42% Statistical Significance
Least Squares Means for effect grp
Pr > |t| for H0: LSMean(i)=LSMean(j)
Dependent Variable: success
i/j n 1 2 3 4
28% 1 23,748 0.9795 <.0001 0.914
2 6,121 0.9795 <.0001 0.9584
3 508 <.0001 <.0001 <.0001
4 582 0.914 0.9584 <.0001
1 2 3 4
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26. Results: Significant learning and business impact from KU
course redesigns – and more to come
Learning impact Financial impact
Higher instructor satisfaction: 3% retention gain
• Instructors see benefits of design; instructor •KU OIE’s team estimates a return of $1.5M in
materials/support for facilitator role OI annually from an investment of $375K
Lower student satisfaction: 14% gain in “student success”
• Courses more demanding and time •Success” = CLA Ave>4, Passed, and Retained
consuming •Analysis controlled for variations in course,
student, instructor and seasonality
Higher retention, less withdrawals: •Translates to a 50% increase over control
• Support for at-risk students to stay engaged courses
More time-on-task:
• Students in pilot versions of courses spend
more time online in course
Better learning outcomes:
• Pilot students earn higher CLA scores and
higher scores on common assessments
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27. Student feedback on the benefits of extra practice
“Something I found to be interesting was the degree of
understanding between me and another individual that wasn’t in this
class. A girl I had met in a previous term that has a similar degree
plan but ended up in a regular medical terminology course, still we
would discuss the differences and similarities between are assigned
classes. During our unit 8 test she called me hysterical about all the
different elements of the final tests and couldn’t seem to grasp the
concept of the 1st part of the test i.e., analysis diagram, creating new
terms from word roots etc. I w as m ystified that som ething that
had becom e 2 nd nature to m e m ainly due to the tim e spent
every w eek filling out the Analysis Tables w as so difficult for
her to com prehend. I t w as at that point I realized all the
griping I had done w as actually the reason m y level of
understanding is m ore evolved than som ebody w ho never
ex perienced it.”
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28. What’s new for learning?
Overview
Cognitive Task Analysis
Kaplan Way – Kaplan University Course Redesigns
Q and A
27

29. Appendix: Initial readings for “learning engineers”
• Why Students Don’t Like School, Daniel Willingham – highly readable! ;-)
• Talent is Overrated, Geoffrey Colvin – highly readable! ;-)
• E-Learning and the Science of Instruction, Clark and Mayer, 3rd ed.
• “First Principles of Learning,” Merrill, D., in Reigeluth, C. M. & Carr, A. (Eds.), Instructional
Design Theories and Models III, 2009.
• How People Learn, John Bransford et al, eds.
• “The Implications of Research on Expertise for Curriculum and Pedagogy”, David Feldon,
Education Psychology Review (2007) 19:91–110
• “Cognitive Task Analysis,” Clark, R.E., Feldon, D., van Merrienboer, J., Yates, K., and Early,
S.. in Spector, J.M., Merrill, M.D., van Merrienboer, J. J. G., & Driscoll, M. P. (Eds.),
Handbook of research on educational communciatinos and technology (3rd ed., 2007)
Lawrence Erlbaum Associates
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