ºÝºÝߣ

ºÝºÝߣShare a Scribd company logo
From Silver Bullets to First
Principles
Effectively Leveraging Technology in Higher Education
Peter E. Doolittle
Assistant Provost for Teaching and Learning
Executive Director, Center for Instructional Development and Educational Research
Professor, Educational Psychology
Virginia Tech
Anticipation Guide
1. Teaching involves presenting students with material
and holding students accountable for learning the
material.
2. Technology allows teachers to teach more
powerfully, more efficiently, and with less effort.
3. In online teaching/learning, students connect with
peers, near and far, to construct knowledge.
Yes? No? What would you
change?
Introductory Frame
So¡­
a philosopher,
a monk, and
a researcher
walk into my mind¡­
David Stearns
Matthieu Ricard
Jessica Chittum
balance
responsibility
student development
3 Questions to Avoid Silver Bullets
1.
2.
3.
Part 1
A Change in Perspective
https://www.youtube.com/watch?v=Weq_sHxghcg
Introductory Frame
technological
determinism
social
determinism
David Stearns, U of Washington
social-shaping of
technology
techno-optimism ?
techno-pessimism ?
Introductory Frame
technological
determinism
social
determinism
David Stearns, U of Washington
social-shaping of
technology
techno-optimism ?
techno-pessimism ?
SCOT
Responsibility
technology is
neither good nor
bad, but using it
makes it so
MOOCs v1.0
Introductory Frame
technological
determinism
social
determinism
David Stearns, U of Washington
social-shaping of
technology
techno-optimism ?
techno-pessimism ?
SCOT
Responsibility
technology is
neither good nor
bad, but using it
makes it so
MOOCs v1.0
In 50 years there will only be
10 institutions in the world
delivering education, and
Udacity has a shot at being
one of them.
- Sebastian Thrun
(Udacity)
We found that the majority of
MOOCs scored poorly on
most [learning]
principles¡­[but] highly on
organization and presentation
of course material¡­although
most MOOCs are well-
packaged, their [learning]
quality is low.
Hype, Hope, Rhetoric & Research
technological
trigger
peak of inflated
expectations
Gartner Hype Cycle
trough of
disillusionment
slope of
enlightenment
plateau of
productivity
Hype, Hope, Rhetoric & Research
peak of inflated
expectations
Gartner Hype Cycle
slope of
enlightenment
plateau of
productivity
techno-optimism
rhetoric-based
hype
techno-pragmatism
research-based
theory
Silver Bullet: ePortfolios
Google Trends
2007 2009 2011 20132005 2015
techno-optimism
rhetoric-based
Silver Bullets: ePortfolios
Bryant, L., & Chittum, J. (2013). ePortfolio effectiveness: A(n ill-fated) search
for empirical support. International Journal of ePortfolio, 3(2),189-198.
Chittum, J., Woodyard, J., & Bryant, L. (2015).
Article Type N %
Descriptive (examples, do/don¡¯t) 92 42
Affective (opinions, perceptions) 63 29
Outcomes (learning, motivation) 36 17
Technology (user interface, platform) 18 8
Assessment (use of rubrics/tools) 8 4
Total 217
1996-2014
Silver Bullet: ePortfolios
Google Trends
2007 2009 2011 20132005 2015
techno-optimism
rhetoric-based
Frequency of
ePortfolio Pubs
Silver Bullet: Others
Google Trends
2007 2009 2011 20132005 2015
techno-optimism
rhetoric-based
3 Questions to Avoid Silver Bullets
1. Where¡¯s the research?
Part 2
The Need for Clarity
https://www.youtube.com/watch?v=VSdxqIBfEAw
Silver Bullets: ePortfolios
Bryant, L., & Chittum, J. (2013). ePortfolio effectiveness: A(n ill-fated) search
for empirical support. International Journal of ePortfolio, 3(2),189-198.
Chittum, J., Woodyard, J., & Bryant, L. (2015).
Article Type N %
Descriptive (examples, do/don¡¯t) 92 42
Affective (opinions, perceptions) 63 29
Outcomes (learning, motivation) 36 17
Technology (user interface, platform) 18 8
Assessment (use of rubrics/tools) 8 4
Total 217
1996-2014
Rest
Tired
Awake
Dream
Snore
Bed
Eat
Slumber
Sound
Comfort
Wake
Night
(Word Activity)
Learning & Meaning
1. Knowledge/meaning is constructed during
experience and reconstructed during recall.
2. Knowledge is organized.
3. When specifics are lost, meaning remains.
4. Cognitive strategies are used to function more
effectively.
5. We can assess the effectiveness of our thinking.
What we process
we learn.
Cognitively
Socially
Behaviorally
Affectively
awareness
control
Segmentation
The Effects of Segmentation and Personalization on
Superficial and Comprehensive Strategy Instruction
Authors: Doolittle. P. (2010)
Design: 3 min multimedia tutorial or
2.5 hour multimedia tutorial over 4 days
Topic: Historical Inquiry
Variables: Segmentation
Reduces cognitive load, facilitate processing
Publication: Journal of Educational Multimedia and
Hypermedia, 19(2), 5-21
Segmentation
The Effects of Segmentation and Personalization on
Superficial and Comprehensive Strategy Instruction
Non-Segmented Segmented
12
10
8
6
4
2
0
Recall
Application
Segmentation
Multimedia Learning and Individual Differences: Mediating
the Effects of Working Memory Capacity with Segmentation
Authors: Lusk, D., Evans, A., Jeffery, T. Palmer, K.
Wikstrom, C., & Doolittle, P. (2009)
Design: 11 min multimedia tutorial
Topic: Historical Inquiry
Variables: Segmentation
Low/High Working Memory Capacity
Publication: British Journal of Educational Technology,
40(4), 636-651
Working Memory Capacity
? Crucible of Thought
? Stores Immediate Experiences
? Access Long-Term Memory
? Processes Experience and Memory
? Maintains Current Goal for Processing
? (especially in the presence of distraction)
Working Memory Capacity
? Storage + Processing = Attentional Control
? Positive impacts include:
? Fluid Intelligence
? LTM Activation
? Attentional Control
? Reading/Language Comprehension
? Reasoning
? Storytelling
Working Memory Capacity
(3 + 7) / 2 = 5 ? Cow
(8 - 3) + 1 = 7 ? Star
Recall the words out loud, in order.
Operation Span Task
(explain directions)
Working Memory Capacity
(9 - 6) / 3 = 2 ? Grass
(5 + 3) - 6 = 2 ? Phone
Recall the words out loud, in order.
Working Memory Capacity
(7 + 2) + 1 = 9 ? White
(3 + 4) + 2 = 9 ? Cement
Recall the words out loud, in order.
(2 - 0) / 2 = 2 ? Pony
Working Memory Capacity
(9 - 2) - 2 = 4 ? System
(1 + 7) / 4 = 2 ? Explore
Recall the words out loud, in order.
(2 + 1) * 3 = 9 ? Lips
(6 - 4) * 3 = 8 ? Wired
(5 + 5) - 6 = 4 ? Spring
Segmentation
Multimedia Learning and Individual Differences: Mediating
the Effects of Working Memory Capacity with Segmentation
Authors: Lusk, D., Evans, A., Jeffery, T. Palmer, K.
Wikstrom, C., & Doolittle, P. (2009)
Design: 11 min multimedia tutorial
Topic: Historical Inquiry
Variables: Segmentation
Low/High Working Memory Capacity
Publication: British Journal of Educational Technology,
40(4), 636-651
Segmentation
Multimedia Learning and Individual Differences: Mediating
the Effects of Working Memory Capacity with Segmentation
Non-Segmented Segmented
12
10
8
6
4
2
0
Recall
Application
Segmentation
Multimedia Learning and Individual Differences: Mediating
the Effects of Working Memory Capacity with Segmentation
Non-Segmented Segmented
12
10
8
6
4
2
0
High WMC
Low WMC
Application
Segmentation
Effect of Segmentation and Learner Disposition on Learning in
a Multimedia Instructional Environment
Authors: Doolittle, P., Bryant, L., & Chittum, J. (2014)
Design: 9 min multimedia tutorial
Topic: Historical Inquiry
Variables: Segmentation
1, 7, 14, & 28 segments
Publication: British Journal of Educational Technology
Segmentation
Effect of Segmentation and Learner Disposition on Learning
in a Multimedia Instructional Environment
12
10
8
6
4
2
0
1 7 14 28
Application
Recall
Segmentation
Effect of Active Segmentation and Processing on Learning in a
Multimedia Instructional Environment
Authors: Doolittle, P. (2015)
Design: 9 min multimedia tutorial
Topic: Historical Inquiry
Variables: Segmentation
Recognition Processing vs Recall Processing
Publication: Submitted
Segmentation
Effect of Active Segmentation and Processing on Learning in
a Multimedia Instructional Environment
12
10
8
6
4
2
0
Non-
Segmented
Segmented Segmented
w/Recognition
Processing
Application
Segmented
w/Recall
Processing
3 Questions to Avoid Silver Bullets
1. Where¡¯s the research?
2. Where¡¯s the processing?
When Hype & Research Collide
Multitasking
Multitasking: The Myth
? Tapscott, 1998
? Frand, 2000
? ¡°multitasking way of life¡±
? Prensky , 2001
? ¡°digital natives accustomed to the twitch-speed, multitasking ¡°
Watson, C. E., Terry, K.,& Doolittle, P. (2012). Please read while texting and
driving. In J. Groccia (Ed.), To improve the academy (vol. 31) (pp. 295-310).
Bolton, MA: Anchor.
Was Any Research Available?
¡°The greater the number of objects to which our
consciousness is simultaneously extended, the
smaller is the intensity with which it is able to
consider each.¡±
Hamilton, Mansel, & Veitch 1861
Students, Professionals,
Multitasking
Group A
Basic Math +
Challenging Video
10
8
6
4
2
Group B
Applied Math +
Challenging Video
Students
Professionals
24 year olds 50 year olds
Negangard, Ozlanski, Pyzoha, & Doolittle (2015)
Students, Faculty, Multitasking
Group A
Challenging Video
10
8
6
4
2
Group B
Survey +
Challenging Video
Students
Faculty
19 year olds 44 year olds
500+ 150+
Doolittle, Woodyard, & Chittum (2015)
3 Questions to Avoid Silver Bullets
1. Where¡¯s the research?
2. Where¡¯s the processing?
Part 3
The Need to Plan
https://www.youtube.com/watch?v=CQUyPYitbJQ
Learning, Teaching, Assessment
Assessment for Free
Active Learning
Engaged Students
Hands On Minds On
Flipping: Design Beyond Video
Before During
Video Inquiry
content
The ¡°Flip¡±
Moving from
Teacher-Centered
to
Learner-Centered
active
learning
Learning is not magic, it¡¯s by design.
After
Flipped
Three opportunities for students to process¡­
3 Questions to Avoid Silver Bullets
1. Where¡¯s the research?
2. Where¡¯s the processing?
3. Where¡¯s the design?
Flipping ? Learning Spaces ? Microcredentialing ? MOOCs
Social Web ? Data Visualization ? Feedback ? Questions
Faculty Development ? Learning at Scale ? Gaming
Learning Analytics ? Apple TV ? 3D Modeling ? Personalizing
Schoology ? VoiceThread ? Respondus ? MobLab ? Artstor
3 questions to
ask at every
session
The End
So¡­
a philosopher,
a monk, and
a researcher
walk into my mind¡­
David Stearns
Matthieu Ricard
Jessica Chittum
the evils of blindly
adopting & advocating
the use of edu tech
balance
responsibility
student development

More Related Content

From Silver Bullets to First Principles: Effectively Leveraging Technology in Higher Education

  • 1. From Silver Bullets to First Principles Effectively Leveraging Technology in Higher Education Peter E. Doolittle Assistant Provost for Teaching and Learning Executive Director, Center for Instructional Development and Educational Research Professor, Educational Psychology Virginia Tech
  • 2. Anticipation Guide 1. Teaching involves presenting students with material and holding students accountable for learning the material. 2. Technology allows teachers to teach more powerfully, more efficiently, and with less effort. 3. In online teaching/learning, students connect with peers, near and far, to construct knowledge. Yes? No? What would you change?
  • 3. Introductory Frame So¡­ a philosopher, a monk, and a researcher walk into my mind¡­ David Stearns Matthieu Ricard Jessica Chittum balance responsibility student development
  • 4. 3 Questions to Avoid Silver Bullets 1. 2. 3.
  • 6. A Change in Perspective https://www.youtube.com/watch?v=Weq_sHxghcg
  • 7. Introductory Frame technological determinism social determinism David Stearns, U of Washington social-shaping of technology techno-optimism ? techno-pessimism ?
  • 8. Introductory Frame technological determinism social determinism David Stearns, U of Washington social-shaping of technology techno-optimism ? techno-pessimism ? SCOT Responsibility technology is neither good nor bad, but using it makes it so MOOCs v1.0
  • 9. Introductory Frame technological determinism social determinism David Stearns, U of Washington social-shaping of technology techno-optimism ? techno-pessimism ? SCOT Responsibility technology is neither good nor bad, but using it makes it so MOOCs v1.0 In 50 years there will only be 10 institutions in the world delivering education, and Udacity has a shot at being one of them. - Sebastian Thrun (Udacity) We found that the majority of MOOCs scored poorly on most [learning] principles¡­[but] highly on organization and presentation of course material¡­although most MOOCs are well- packaged, their [learning] quality is low.
  • 10. Hype, Hope, Rhetoric & Research technological trigger peak of inflated expectations Gartner Hype Cycle trough of disillusionment slope of enlightenment plateau of productivity
  • 11. Hype, Hope, Rhetoric & Research peak of inflated expectations Gartner Hype Cycle slope of enlightenment plateau of productivity techno-optimism rhetoric-based hype techno-pragmatism research-based theory
  • 12. Silver Bullet: ePortfolios Google Trends 2007 2009 2011 20132005 2015 techno-optimism rhetoric-based
  • 13. Silver Bullets: ePortfolios Bryant, L., & Chittum, J. (2013). ePortfolio effectiveness: A(n ill-fated) search for empirical support. International Journal of ePortfolio, 3(2),189-198. Chittum, J., Woodyard, J., & Bryant, L. (2015). Article Type N % Descriptive (examples, do/don¡¯t) 92 42 Affective (opinions, perceptions) 63 29 Outcomes (learning, motivation) 36 17 Technology (user interface, platform) 18 8 Assessment (use of rubrics/tools) 8 4 Total 217 1996-2014
  • 14. Silver Bullet: ePortfolios Google Trends 2007 2009 2011 20132005 2015 techno-optimism rhetoric-based Frequency of ePortfolio Pubs
  • 15. Silver Bullet: Others Google Trends 2007 2009 2011 20132005 2015 techno-optimism rhetoric-based
  • 16. 3 Questions to Avoid Silver Bullets 1. Where¡¯s the research?
  • 18. The Need for Clarity https://www.youtube.com/watch?v=VSdxqIBfEAw
  • 19. Silver Bullets: ePortfolios Bryant, L., & Chittum, J. (2013). ePortfolio effectiveness: A(n ill-fated) search for empirical support. International Journal of ePortfolio, 3(2),189-198. Chittum, J., Woodyard, J., & Bryant, L. (2015). Article Type N % Descriptive (examples, do/don¡¯t) 92 42 Affective (opinions, perceptions) 63 29 Outcomes (learning, motivation) 36 17 Technology (user interface, platform) 18 8 Assessment (use of rubrics/tools) 8 4 Total 217 1996-2014
  • 21. Learning & Meaning 1. Knowledge/meaning is constructed during experience and reconstructed during recall. 2. Knowledge is organized. 3. When specifics are lost, meaning remains. 4. Cognitive strategies are used to function more effectively. 5. We can assess the effectiveness of our thinking.
  • 22. What we process we learn. Cognitively Socially Behaviorally Affectively awareness control
  • 23. Segmentation The Effects of Segmentation and Personalization on Superficial and Comprehensive Strategy Instruction Authors: Doolittle. P. (2010) Design: 3 min multimedia tutorial or 2.5 hour multimedia tutorial over 4 days Topic: Historical Inquiry Variables: Segmentation Reduces cognitive load, facilitate processing Publication: Journal of Educational Multimedia and Hypermedia, 19(2), 5-21
  • 24. Segmentation The Effects of Segmentation and Personalization on Superficial and Comprehensive Strategy Instruction Non-Segmented Segmented 12 10 8 6 4 2 0 Recall Application
  • 25. Segmentation Multimedia Learning and Individual Differences: Mediating the Effects of Working Memory Capacity with Segmentation Authors: Lusk, D., Evans, A., Jeffery, T. Palmer, K. Wikstrom, C., & Doolittle, P. (2009) Design: 11 min multimedia tutorial Topic: Historical Inquiry Variables: Segmentation Low/High Working Memory Capacity Publication: British Journal of Educational Technology, 40(4), 636-651
  • 26. Working Memory Capacity ? Crucible of Thought ? Stores Immediate Experiences ? Access Long-Term Memory ? Processes Experience and Memory ? Maintains Current Goal for Processing ? (especially in the presence of distraction)
  • 27. Working Memory Capacity ? Storage + Processing = Attentional Control ? Positive impacts include: ? Fluid Intelligence ? LTM Activation ? Attentional Control ? Reading/Language Comprehension ? Reasoning ? Storytelling
  • 28. Working Memory Capacity (3 + 7) / 2 = 5 ? Cow (8 - 3) + 1 = 7 ? Star Recall the words out loud, in order. Operation Span Task (explain directions)
  • 29. Working Memory Capacity (9 - 6) / 3 = 2 ? Grass (5 + 3) - 6 = 2 ? Phone Recall the words out loud, in order.
  • 30. Working Memory Capacity (7 + 2) + 1 = 9 ? White (3 + 4) + 2 = 9 ? Cement Recall the words out loud, in order. (2 - 0) / 2 = 2 ? Pony
  • 31. Working Memory Capacity (9 - 2) - 2 = 4 ? System (1 + 7) / 4 = 2 ? Explore Recall the words out loud, in order. (2 + 1) * 3 = 9 ? Lips (6 - 4) * 3 = 8 ? Wired (5 + 5) - 6 = 4 ? Spring
  • 32. Segmentation Multimedia Learning and Individual Differences: Mediating the Effects of Working Memory Capacity with Segmentation Authors: Lusk, D., Evans, A., Jeffery, T. Palmer, K. Wikstrom, C., & Doolittle, P. (2009) Design: 11 min multimedia tutorial Topic: Historical Inquiry Variables: Segmentation Low/High Working Memory Capacity Publication: British Journal of Educational Technology, 40(4), 636-651
  • 33. Segmentation Multimedia Learning and Individual Differences: Mediating the Effects of Working Memory Capacity with Segmentation Non-Segmented Segmented 12 10 8 6 4 2 0 Recall Application
  • 34. Segmentation Multimedia Learning and Individual Differences: Mediating the Effects of Working Memory Capacity with Segmentation Non-Segmented Segmented 12 10 8 6 4 2 0 High WMC Low WMC Application
  • 35. Segmentation Effect of Segmentation and Learner Disposition on Learning in a Multimedia Instructional Environment Authors: Doolittle, P., Bryant, L., & Chittum, J. (2014) Design: 9 min multimedia tutorial Topic: Historical Inquiry Variables: Segmentation 1, 7, 14, & 28 segments Publication: British Journal of Educational Technology
  • 36. Segmentation Effect of Segmentation and Learner Disposition on Learning in a Multimedia Instructional Environment 12 10 8 6 4 2 0 1 7 14 28 Application Recall
  • 37. Segmentation Effect of Active Segmentation and Processing on Learning in a Multimedia Instructional Environment Authors: Doolittle, P. (2015) Design: 9 min multimedia tutorial Topic: Historical Inquiry Variables: Segmentation Recognition Processing vs Recall Processing Publication: Submitted
  • 38. Segmentation Effect of Active Segmentation and Processing on Learning in a Multimedia Instructional Environment 12 10 8 6 4 2 0 Non- Segmented Segmented Segmented w/Recognition Processing Application Segmented w/Recall Processing
  • 39. 3 Questions to Avoid Silver Bullets 1. Where¡¯s the research? 2. Where¡¯s the processing?
  • 40. When Hype & Research Collide Multitasking
  • 41. Multitasking: The Myth ? Tapscott, 1998 ? Frand, 2000 ? ¡°multitasking way of life¡± ? Prensky , 2001 ? ¡°digital natives accustomed to the twitch-speed, multitasking ¡° Watson, C. E., Terry, K.,& Doolittle, P. (2012). Please read while texting and driving. In J. Groccia (Ed.), To improve the academy (vol. 31) (pp. 295-310). Bolton, MA: Anchor.
  • 42. Was Any Research Available? ¡°The greater the number of objects to which our consciousness is simultaneously extended, the smaller is the intensity with which it is able to consider each.¡± Hamilton, Mansel, & Veitch 1861
  • 43. Students, Professionals, Multitasking Group A Basic Math + Challenging Video 10 8 6 4 2 Group B Applied Math + Challenging Video Students Professionals 24 year olds 50 year olds Negangard, Ozlanski, Pyzoha, & Doolittle (2015)
  • 44. Students, Faculty, Multitasking Group A Challenging Video 10 8 6 4 2 Group B Survey + Challenging Video Students Faculty 19 year olds 44 year olds 500+ 150+ Doolittle, Woodyard, & Chittum (2015)
  • 45. 3 Questions to Avoid Silver Bullets 1. Where¡¯s the research? 2. Where¡¯s the processing?
  • 47. The Need to Plan https://www.youtube.com/watch?v=CQUyPYitbJQ
  • 48. Learning, Teaching, Assessment Assessment for Free Active Learning Engaged Students Hands On Minds On
  • 49. Flipping: Design Beyond Video Before During Video Inquiry content The ¡°Flip¡± Moving from Teacher-Centered to Learner-Centered active learning Learning is not magic, it¡¯s by design. After Flipped Three opportunities for students to process¡­
  • 50. 3 Questions to Avoid Silver Bullets 1. Where¡¯s the research? 2. Where¡¯s the processing? 3. Where¡¯s the design? Flipping ? Learning Spaces ? Microcredentialing ? MOOCs Social Web ? Data Visualization ? Feedback ? Questions Faculty Development ? Learning at Scale ? Gaming Learning Analytics ? Apple TV ? 3D Modeling ? Personalizing Schoology ? VoiceThread ? Respondus ? MobLab ? Artstor 3 questions to ask at every session
  • 51. The End So¡­ a philosopher, a monk, and a researcher walk into my mind¡­ David Stearns Matthieu Ricard Jessica Chittum the evils of blindly adopting & advocating the use of edu tech balance responsibility student development