Faculty Satisfaction in ALNs: A Dependent or Independent Variable

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Faculty Satisfaction in ALNsA Dependent
orIndependent Variable?

• University of Central Florida
• Joel Hartman - Charles Dziuban
• Sloan Summer ALN Conference
• Urbana, Illinois August 17, 1999

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Orlando, Florida
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DUVAL
LEON

ALACHUA
MARION
VOLUSIA
CHANGE
PROJECTED
IN NUMBER OF
25 to 44-YEAR-OLDS
OSCEOLA
FROM 1995 to 2010
HILLS-
POLK
BOROUGH

ST
MANATEE
LUCIE

15,000 to 19,999
MAIN CAMPUS
PALM
5,000 to 9,999
BEACH
LEE

BRANCH
0 to 4,999
BROWARD
COLLIER
-1 to -5,000
CENTER
-10 to -20,000
DADE
STATEWIDE CHANGE -81,559

-25,000 to -30,000
SOURCE FL Demographic Est. Conf. (Jun 97)
C\HGW\popmap97/5
C/MD/HGW/HGW4/MPJulyPresentation
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• FEEDS Statewide access to graduate engineering
  programs

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• W Courses delivered entirely over the Web,
  with no regular class meetings
• M Courses delivered partially in classroom and
  partially over the Web, generally with reduced
  seat time
• E Web enhanced (Web presence)

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UCF Online Programs

• BA in Liberal Studies
• BA or BS in Vocational Education
• RN to BSN in Nursing
• MS in Vocational Education
• MS in Forensic Science

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Virtual Campus W Enrollments
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Virtual Campus M Enrollments
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Institutionalizing ALN

• Experiential learning for faculty
• Cross-discipline sharing of techniques
• Builds faculty learning communities
• Stimulates evaluation of teaching and learning
• Exposes faculty to best practices
• Peer evaluation of successes and failures
• Leads to transformation

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UCF Organization
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• DL course and program development
• Marketing of DL courses and programs
• Long-range planning
• Schedule development
• Accreditation
• Institutional contact
• Facilitate faculty research

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• Internet tools
• Browser test
• Tutorials
• Assessment
• UCF information
• Connection to campus computer network

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• Technical Issues
• Capacity/growth
• Reliability
• Performance
• Access
• Faculty and staff to production resources
• Students to the network and content

• Servers
• Production facilities
• Modem pool
• Help desk

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Factors Leading toFaculty Satisfaction

• Reliable infrastructure
• Institutionalization of ALN effort
• High quality faculty development and support
• Recognition and incentives
• Interdisciplinary approach
• Web vets
• Student support
• Ongoing assessment faculty involvement
• Continuous improvement

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Some Principles That GuideOur Evaluation

• Evaluation should conform to the culture of your
  institution.
• Uncollected data cannot be analyzed.
• Data do not equal information.
• Qualitative and quantitative approaches must
  complement each other.

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Distributed Learning Impact Evaluation components
Faculty
Students
Critical thinking
Real time surveys
Success rates
Attitudes
Effective instructional tools
Demographics
Withdrawal rates
Quasi-experiments
Strategies for success
Accreditation
Learning styles
Assessment techniques
Personal theorizing
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Faculty Workload Compared to Face-to-face
Courses, Spring 1998
90
88
63
25
13
13
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Reduced seat time (N8)
Media enhanced (N8)
Fully on-line (N30)
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Hours Spent by Faculty Developing ALN Courses --
Spring 98
Searching for existing web resources n Reengineer
ing instructional materials x Reengineering
activities assignments Developing new means
of assessment
Developing new instructional materials
(n48)
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Amount of Interaction Compared With Face-to-face
Course, Spring 1998
97
75
50
38
13
13
13
3
Reduced seat time (N8)
Media enhanced (N8)
Fully on-line (N31)
Exact probability.00
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Quality of Interaction Compared With Face-to-face
Course, Spring 1998
94
75
71
29
25
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Reduced seat time (N8)
Media enhanced (N8)
Fully on-line (N31)
Exact probability.07
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Faculty Overall Satisfaction With ALN Course
Compared With F2F Course, Spring 1998
88
83
63
25
13
13
13
3
Reduced seat time (N8)
Media enhanced (N8)
Fully on-line (N30)
Exact probability.32
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Faculty Willingness to Continue Teaching ALN
Courses, Spring 1998
100
94
88
13
3
3
Reduced seat time (N8)
Media enhanced (N8)
Fully on-line (N31)
Exact probability.12
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Five Positive Components Faculty Cited in On-line
Teaching

• Student and teacher interaction is enhanced
• The teaching and learning environment is much
  more flexible
• The environment forced continuous improvement
• The teachers role changes to that of a
  facilitator
• Students are more actively involved in their
  learning

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Five Negative Components Faculty Cited in On-line
Teaching

• Time demands are very severe
• Technology problems will occur
• There is decreased face-to-face student contact
• Students evaluations of teachers are lower
• Faculty feel an uneasiness about how this fits
  into the university culture of teaching,
  research, service

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Comparison of Success Rates in POS 2041Am.
Natl. Govt., Traditional and M Sections
25th percentile
50th percentile
75th percentile
81.6
85.1
88.5
M
68.9
78.1
85.1
T
Exact probability.099
60
70
80
90
Success rates
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Comparison of Withdrawal Rates in POS 2041 Am.
Natl. Govt., Traditional and M Sections
25th percentile
50th percentile
75th percentile
.6
2.1
3.6
M
1.9
3.1
6.9
T
Exact probability.22
0
2
4
7
1
3
5
6
Withdrawal rates
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A Comparison of Class Sizes in POS 2041Am.
Natl. Govt., Traditional and M Sections
25th percentile
50th percentile
75th percentile
82
85
94.5
M
15
71.5
86
T
Exact probability.055
10
30
50
80
20
40
60
70
90
100
Class sizes
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Confidence Intervals for Success Rate in POS
2041 Am. Natl. Govt., Traditional and M Sections
Note success rates for M courses are higher and
less variable
M01
M02
M03
M04
M05
9
10
Course sections
11
12
13
14
15
16
17
18
50
60
70
80
90
100
Success rates
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Segmentation Model for Predicting Success Rates
Using Class Modality and Gender -- Spring 99
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Success Rates for Matched M and Traditional, and
W and Traditional Sections -- Fall 98
88.6
85.5
78.8
75.7
M 1,321
T 2,255
W 251
T 861
p.00
p.00
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Withdrawal Rates for Matched Pairs of M and
Traditional and W and Traditional Sections --
Fall 98
9.0
5.9
4.5
3.4
M 1,321
T 2,255
W 251
T 861
p.00
p.00
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Success Rates for Cohort of 8 Web Courses Offered
in Fall 97 and Repeated in Fall 98
1.0
.90
Success rate
.80
.70
.60
1997
1998
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Withdrawal Rates for Cohort of 8 Web Courses
Offered in Fall 97 and Repeated in Fall 98
.30
Withdrawal rate
?
.20
.10
.00
1997
1998
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Student Reactions RegardingOnline Learning
Positive
Less positive

• UCF responsiveness
• Active learning
• Educational empowerment

• Modified student role
• Modified instructor role
• Technology challenges

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Research on StudentBehavior Types
Based on Long (1985)
Types
Traits

• Aggressive Independent
• Aggressive Dependent
• Passive Independent
• Passive Dependent

• Phobic
• Impulsive
• Compulsive
• Hysteric

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Distribution of Long Types and Traits for On-line
Students
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PD 5
AI 23
AD 60
25
26
13
PI 12
(n301)
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Distribution of Long Types and Traits for CHM 1020
PD 19
60
55
AI 27
AD 37
31
22
PI 18
(n133)
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Typical Results From Significant Difference
Studies
Student final exam scores Mean N Std Dev. ITV
Remote 395 16 52 ITV On-campus 374 34 48 Tradition
al 364 21 38
What they didnt look at Variances ITV
Remote 2704 ITV On-campus 2304 Traditional 1444
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A Model of Interacting Faculty Satisfaction and
Student Outcomes
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UCF Distributed Learning Impact Evaluation Website
http//reach.ucf.edu/research
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Contacts at the University of Central Florida
For information regarding UCFs institutional
approach to distributed learning
Joel L. Hartman, Vice Provost for
Information Technologies Resources University
of Central Florida P.O. Box 2800 Orlando, FL
32816-2800 joel_at_mail.ucf.edu
For information regarding UCFs Distributed
Learning Impact Evaluation
Chuck Dziuban, Ph.D. University of Central
Florida Distributed Learning Impact
Evaluation P.O. Box 161250 Orlando, FL
32816-1250 dziuban_at_pegasus.cc.ucf.edu
Patsy D. Moskal, Ed.D. University of Central
Florida Distributed Learning Impact
Evaluation P.O. Box 161250 Orlando, FL
32816-1250 pdmoskal_at_pegasus.cc.ucf.edu