Innovations in Higher Education Learning
Bror Saxberg
CLO, Kaplan, Inc.



February 8, 2012
What’s new for learning?

Overview

Cognitive Task Analysis

Kaplan Way – Kaplan University Course Redesigns

Q and A




                                                  1
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




                                                                                    2
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.




                                                                                                   3
To respond, consider structuring key initiatives to take
advantage of what’s known about learning – and data




                           Rapidly test
                            and scale
                             learning
                           innovations




                                                           4
What’s new for learning?

Overview

Cognitive Task Analysis

Kaplan Way – Kaplan University Course Redesigns

Q and A




                                                  5
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.

                                                                                                                  6
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




                                                                           7
Medical Assistant current course content:
                                                        Pharmacology course

                                                                   Diseases - human body




           X = substantial content; x = ancillary content
                                                                                     8
MA CTA: Identifies key tasks/skills performed by experts
    Original content        New focus

                                         • Tie to domain tasks as
                                           identified by experts




                                                              9
MA Program: Skills addressed in new sequence
                           New focus

                                        • Tie to domain tasks as
                                          identified by experts




                                                            10
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
                                                                11
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




                                                           12
What’s new for learning?

Overview

Cognitive Task Analysis

Kaplan Way – Kaplan University Course Redesigns

Q and A




                                                  13
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)




                                                                                        14
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




                                                                                             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)


                      • 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
                                                                                                                                          16
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


                                                                              17
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


                                                                                                                       18
Impact is not small!
                             1 sd
                       50%          84%!




                                           19
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




                                                                                     20
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




                                                                   21
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

                                                                        22
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



                                                                                                     23
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


                                                                                                         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   •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



                                                                                                    25
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.”


                                                                             26
What’s new for learning?

Overview

Cognitive Task Analysis

Kaplan Way – Kaplan University Course Redesigns

Q and A




                                                  27
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




                                                                                                        28

BISG's MIP for Higher Ed 2012 -- SAXBERG

  • 1.
    Innovations in HigherEducation Learning Bror Saxberg CLO, Kaplan, Inc. February 8, 2012
  • 2.
    What’s new forlearning? Overview Cognitive Task Analysis Kaplan Way – Kaplan University Course Redesigns Q and A 1
  • 3.
    Bror Saxberg Chief LearningOfficer, 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 2
  • 4.
    What Our StudentsTold 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. 3
  • 5.
    To respond, considerstructuring key initiatives to take advantage of what’s known about learning – and data Rapidly test and scale learning innovations 4
  • 6.
    What’s new forlearning? Overview Cognitive Task Analysis Kaplan Way – Kaplan University Course Redesigns Q and A 5
  • 7.
    Employers actually expectjob 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. 6
  • 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 7
  • 9.
    Medical Assistant currentcourse content: Pharmacology course Diseases - human body X = substantial content; x = ancillary content 8
  • 10.
    MA CTA: Identifieskey tasks/skills performed by experts Original content New focus • Tie to domain tasks as identified by experts 9
  • 11.
    MA Program: Skillsaddressed in new sequence New focus • Tie to domain tasks as identified by experts 10
  • 12.
    MA Program: Skillsaddressed in new sequence • Tie to domain tasks as identified by experts • Repeated use of skills across courses B: Begin; A: Advanced; R: Reinforce 11
  • 13.
    MA Program: Newcourses 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 12
  • 14.
    What’s new forlearning? Overview Cognitive Task Analysis Kaplan Way – Kaplan University Course Redesigns Q and A 13
  • 15.
    A lot isknown about what drives learning now Instructional Events Student Learning Events (in the learning (hidden - inside students’ Performance environment) minds) (observable -indicates knowledge) 14
  • 16.
    A lot isknown 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 15
  • 17.
    A lot isknown 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 16
  • 18.
    Task-centered instruction • Movefrom simple to increasingly difficult tasks – NOT “PBL” sink or swim • Teach everything needed for each task • Fade coaching/support over time 17
  • 19.
    ID can changeinstructional 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 18
  • 20.
    Impact is notsmall! 1 sd 50% 84%! 19
  • 21.
    Instructional Design processshould 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 20
  • 22.
    In 2011 KUand 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 21
  • 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 22
  • 24.
    Results: Significant learningand 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 23
  • 25.
    The pilot coursesdelivered 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 24
  • 26.
    Results: Significant learningand 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 25
  • 27.
    Student feedback onthe 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.” 26
  • 28.
    What’s new forlearning? Overview Cognitive Task Analysis Kaplan Way – Kaplan University Course Redesigns Q and A 27
  • 29.
    Appendix: Initial readingsfor “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 28