technology-enhanced learning: opportunities and challenges · technology-enhanced learning:...
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![Page 1: Technology-Enhanced Learning: Opportunities and Challenges · Technology-Enhanced Learning: Opportunities and Challenges Chuck Dziuban Patsy Moskal University of Central Florida](https://reader033.vdocument.in/reader033/viewer/2022051804/5fec3f9cdfc47c71061ccbd6/html5/thumbnails/1.jpg)
Technology-Enhanced Learning: Opportunities and Challenges
Chuck DziubanPatsy Moskal
University of Central Florida
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The University of Central Florida
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500,000
700,000
900,000
1,100,000
1,300,000
1,500,000
1,700,000
1995-96 2000-01 2005-06 2010-11
Sources of UCF SCH Growth
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A value-added model of technology-enhanced learning
TechnologyAugmented
(E)
Faculty Initiative Institutional Initiative
Blended(M)
FullyOnline
(W)Access and
TransformationEnhancement Engagement
Learning Management
Systems
Web 2.0
Lecture Capture
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Shirky, C. (2009)
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Some Interesting Models
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Web 2.0 Blending
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Public RelationsRobert French
Auburn University
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New Media BlendingGardner Campbell
Virginia Tech
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Laureate International Universities Network
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An Evaluation Plan
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Evidence of ImpactStudents Faculty
Learning preferences
SuccessSatisfaction
DemographicsRetention
Blended Academic Life
Blended Theater
Blended Assessment
Blended WritingInformation
fluencyGenerations
Personal geographies
Predictive models Case narratives
Blended Algebra
Blended PersonaWeb 2.0
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Success
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Success rates by modality Spring 2009 through Summer 2010
87 91 87 88 918895 91 91 94
88 88 86 88 88
0102030405060708090
100
Perc
ent
Spring 09 Summer 09 Fall 09 Spring 10 Summer 10
F2F(n=618,899)
Blended(n=39,021)
Fully Online(n=109,421)
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Predicting Success and Withdrawal
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Prediction DomainsDomains Dependent
Demographics
Ability
AcademicPerformance
Success &Withdrawal
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Domain Prediction for Success in Online Learning (n range 32,000- 72,000)
Domains Dependent
Successr2 = .01
Ethnicity Age, Gender,
Etc.
SAT/ACT
GPA
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Domain Prediction for Withdrawal in Online Learning (n range 33,000- 73,000)
Domains Dependent
Withdrawalr2 = .01
Ethnicity Age, Gender,
Etc.
SAT/ACT
GPA
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Student Satisfaction
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Satisfaction with fully online courses
44 47
5 3 10
102030405060708090
100
Verysatisfied
Satisfied Neither Unsatisfied Veryunsatisfied
Perc
ent
(n=1197)
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Satisfaction with blended courses
35
53
93 1
0102030405060708090
100
Verysatisfied
Satisfied Neither Unsatisfied Veryunsatisfied
Perc
ent
(n=811)
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Student Satisfaction with Technology Enhanced Learning
• Convenience
• Reduced Logistic Demands
• Increased Learning Flexibility
• Technology Enhanced Learning
Reduced OpportunityCosts for Education
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Less Positives with Technology Enhanced Learning
• Reduced Face-to-Face Time
• Technology Problems
• Reduced Instructor Assistance
• Overwhelming
• Increased Workload
Increased OpportunityCosts for Education
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Tolstoy and Student Satisfaction
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Satisfaction Components
Ambivalence
Enriched Learning Environment
Role Expectation(Rules of Engagement)
CommitmentAmbiguity
Engagement
LearningLatitude
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Generations
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Some characteristics of the generations
• Matures (prior to 1946)• Dedicated to a job they
take on• Respectful of authority• Place duty before
pleasure
• Baby boomers (1946-1964)• Live to work• Generally optimistic• Influence on policy &
products
• Generation X (1965-1980)• Work to live• Clear & consistent
expectations• Value contributing to the
whole
• Millennials (1981-1994)• Live in the moment• Expect immediacy of
technology• Earn money for
immediate consumption
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Student Generations
311
86
0102030405060708090
100
Perc
ent
Boomers1946-1964
Gen X1965-1980
Millennial1981-1994
(n=1217)
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11
55
33
10
102030405060708090
100
Perc
ent
Faculty Generations
Boomers1946-1964
Gen X1965-1980
Millennial1981-1994
(n=689)
MaturePrior to 1946
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Non-ambivalent satisfaction with fully online courses
6556
42
0102030405060708090
100
Perc
ent
Gen X1965-1980
Boomers 1946-1964
Millennial1981-1994
(n=526)
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DisruptiveInnovation!
• There’s one in YOUR future!!
• And another one right behind it!
Wayne Hodgins, 2007
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Wikipedia
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Student Ratings
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Facilitation of learning
Communication of ideas
Excellent Very Good Good Fair Poor
Then...The probability of an overall rating of Excellent = .97 &
The probability of an overall rating of Fair or Poor =.00
If...
A decision rule for the probability of faculty member receiving an overall rating of Excellent
Respect and concern for students
n=1,280,890
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Then...The probability of an overall rating of Poor = .90 &
The probability of an overall rating of Very Good or Excellent =.00
If...
A decision rule for the probability of faculty member receiving an overall rating of Poor
Facilitation of learning
Communication of ideas
Excellent Very Good Good Fair Poor
Respect and concern for students
n=1,280,890
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A comparison of excellent ratings by college unadjusted and adjusted for instructors satisfying Rule 1
Overall If Rule 1College % Excellent % Excellent
Education 58.6 97.9Molecular & Microbiology 49.9 97.6Health & Public Affairs 49.8 97.6Arts & Humanities 49.1 96.7Sciences 44.5 96.8Hospitality Management 44.1 96.6Business Administration 39.5 96.9Engineering 39.0 96.8
n=1,280,890
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A comparison of excellent ratings by coursemodality--unadjusted and adjusted for instructors satisfying Rule 1
Blended 48.9 97.2Online 47.6 97.3Enhanced 46.8 97.5F2F 45.7 97.2
Course Overall If Rule 1Modality % Excellent % Excellent
n=1,171,664
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And the Challenges…Opportunities Abound
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“I have an opportunity for you”Academic Integrity
Assessment models and more authentic
assessment
Adrift in Academia
Information Fluency and Information
Toxicity
Alone Together
Proofiness
Multitasking or Partial Attention
Cognitive Abundance
or The
Shallows?
Dangerous Ideas
Explosive Growth
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Technology-Enhanced Learning and Black Swans
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Taleb: The Black Swan
Unpredicted9/11
Harry Potter
Y2KUndetectable
Outliers
Back-Filled Narrative
Monumental Impact
Retrospective Prediction
Market crash
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Research Initiative for Teaching Effectiveness
For more information contact:
Dr. Chuck Dziuban(407) 823-5478
Dr. Patsy Moskal(407) 823-0283
http://rite.ucf.eduhttp://www.if.ucf.edu/