Andragogy and Online Course Satisfaction: A
Correlation Study
Stephen W. Watts
School of Education, Northcentral University
Prescott Valley, AZ
December 2014
Robin Throne, Ph.D., Committee Chair
, David Britton, Ed.D., Nicole Avena, Ph.D.
1
Agenda
• Background
• Problem and Purpose
• Significance of the Study
• Theoretical Framework
• Research Question(s)
• Literature Review
• Method
• Findings
• Limitations and Implications
• Recommendations for Practice
• Recommendations for Future Research
• Conclusions
2
Background
•
Learner factors have the greatest impact on drop out decisions
(Lee & Choi, 2011).
•
Course-program factors come next (Lee and Choi, 2011).
•
Optimal learning environment included learner characteristics
and design elements (Knowles, 1973, 1975, 1980, 1984, 1990,
1995)
3
Problem and Purpose
• Low satisfaction of adults in online postsecondary
courses (Donavant, 2009; Huang et al., 2012; Watkins,
2005)
• Learner satisfaction largest determinant in reducing
online dropout (Chen & Lien, 2011; Kozub, 2010;
Johnson et al., 2014; Martinez-Caro, 2009).
• Investigate relationships between
• adult learner characteristics,
• instructional process design elements, and
• learner satisfaction.
4
Significance of the Study
•
Need to identify factors that minimize dropout rates in online
classes (Brown, 2012; Lee & Choi, 2011; Wilson & Allen, 2011).
•
The link between retention and learner satisfaction has been
established (Chen & Lien, 2011).
•
Identify predictive value of learner characteristics and specific
instructional processes from which strategies and interventions
may be derived (Donavant, 2009; Gunawardena et al., 2010;
Holton et al., 2009; Huang et al., 2012; Taylor & Kroth, 2009b).
5
Theoretical Framework
• Malcolm S. Knowles
• Andragogy
6
Research Questions
• The following research questions guided the study:
Q1. Do adult learner characteristics predict learner
satisfaction in a Missouri HLC-NCA accredited postsecondary
online environment?
Q2. Do the instructional process design elements predict
learner satisfaction in a Missouri HLC-NCA accredited
postsecondary online environment?
7
Literature Review
• Online Technological Advances
• Purported Benefits of eLearning
• Factors that Bring eLearning Success
• Learner Factors of Dropout
• Online Course or Program Factors of Dropout
•
Learner Satisfaction and Online Course Dropout
•
Factors that Engender eLearner Satisfaction
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Method
 Quantitative Correlational Study
 Postsecondary students over the age of 24 using a stratified
random sample of students from 13 HLC-NCA universities and
colleges in Missouri.
 Online survey through Survey Gizmo, which was a
combination of two pre-validated instruments.
 Hierarchical multiple regression analysis was used for
hypothesis testing
9
Findings: Model 1
Unique
Common
Total
%R2
.000
.073
-.000
.073
96.9
1.336
.182
.001
.002
.002
3.0
-.010
-.460
.545
.000
.000
.000
0.0
Gender
.006
.273
.785
.000
.000
.000
0.1
Ethnicity
.009
.427
.669
.000
.000
.000
0.0
Education Level
-.056
-2.518
.012
.003
-.003
.000
0.5
Variable
Beta
t
p
Constant
2.161
26.783*
.000
Number of Courses
.271
12.598*
Age Range
.029
School Type
R2
.076*
F
27.622*
Cohen’s f 2
.081
Note. N = 2,058; *p < .01; Unique = x’s unique effect on learner satisfaction, Common = Σ x’s common effects; Total = Unique +
Common; %R2 = Total/R2.
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Findings: Model 2 (Hypothesis 1)
Unique
Common
Total
%R2
.000
.010
.0626
.0727
12.9
-1.147
.251
.000
.002
.002
0.4
-.022
-1.463
.144
.001
-.001
.000
0.0
Gender
.026
1.772
.077
.001
-.001
.000
0.0
Ethnicity
-.009
-.611
.541
.000
.000
.000
0.0
Education Level
-.052
-3.322*
.001
.003
-.002
.000
0.1
Intrinsic Motivation
.326
10.418*
.000
.024
.471
.495
88.0
Self-directed Learning
.110
5.773*
.000
.007
.219
.226
40.3
Prior Experience
.125
5.658*
.000
.007
.356
.363
64.6
Need to Know
.113
5.234*
.000
.006
.320
.326
58.0
Readiness to Learn
.161
5.243*
.000
.006
.449
.456
81.1
Orientation to Learn
.004
.246
.806
.000
.090
.090
16.1
Variable
Beta
t
p
Constant
.529
6.215*
.000
Number of Courses
.103
6.681*
Age Range
-.017
School Type
R2
.562*
F
369.73*
Cohen’s f 2
1.28
Note. N = 2,058; * p < .01, ΔR2 = .486; Unique = x’s unique effect on learner satisfaction, Common = Σ x’s common effects; Total =
Unique + Common; %R2 = Total/R2.
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Findings: Model 3 (Hypothesis 2)
Variable
Constant
Beta
.333
t
4.130*
p
.000
Unique
Common
Total
%R2
Number of Course
.085
6.191*
.000
.007
.066
.073
11.2
Age Range
-.010
-.722
.471
.000
.002
.002
0.4
School Type
Gender
Ethnicity
Education Level
Intrinsic Motivation
-.024
.017
-.005
-.040
.269
-1.731
1.294
-.385
-2.826*
9.529*
.084
.196
.700
.005
.000
.000
.000
.000
.000
.016
.000
.000
.000
.000
.479
.000
.000
.000
.000
.495
0.0
0.0
0.0
0.0
76.0
Self-directed Learning
Prior Experience
Need to Know
Readiness to Learn
Orientation to Learn
Prepare the Learner
Mutual Planning
Climate Setting
Setting of Objectives
Diagnosis of Needs
Learning Activities
Designing Experience
.078
.071
-.074
.084
.009
.115
-.129
.223
-.009
-.096
.046
.034
4.803*
3.545*
-2.806*
3.000*
.586
4.234*
-4.704*
8.658*
-.321
-4.206*
2.632*
1.181
.000
.000
.005
.003
.558
.000
.000
.000
.749
.000
.009
.238
.004
.002
.002
.002
.000
.003
.004
.013
.000
.003
.001
.000
.223
.361
.324
.454
.090
.362
.183
.400
.175
.218
.266
.344
.226
.363
.326
.456
.090
.366
.188
.410
.175
.220
.268
.344
34.7
55.7
50.0
70.0
13.9
56.2
28.8
62.9
26.8
33.9
41.1
52.8
Evaluation
.274
12.167*
.000
.027
.446
.473
72.6
.651*
F
64.939*
2
Cohen’s F
1.833
2
Note. N = 2,058; * p < .01, ΔR = .089; Unique = x’s unique effect on learner satisfaction, Common = Σ x’s common effects;
Total = Unique + Common; %R2 = Total/R2.
R2
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Limitation of Results
• Potential self-selection bias
• Schools in Missouri, potentially limiting generalizability
• Potential inaccuracy in answers given, or intentional
misreports
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Implications
•
Instructors implement adult learning principles (Knowles, 1973, 1975, 1984,
1995).
•
The Andragogy in Practice Inventory may strengthen andragogy’s empirical
research (Brookfield, 1986; Holton et al., 2009; Long et al., 1980; Rachel,
2002).
•
Instructors apply the instructional process design elements
•
Course designers may use to design online offerings
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Recommendations for Practice
• By employing the Andragogy in Practice Inventory,
instructors may hone their instructional skills
• Encourage instructors to better and more consciously
apply andragogy in their online classroom settings.
• Online course and instructional designers may
incorporate more of the instructional process design
elements
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Recommendations for Future Research
• A quantitative experimental study focused on specific or single elements of
the adult learning characteristics and instructional process design elements
• Further confirmatory correlational studies
• Further quantitative correlational studies to determine other factors
• Future quantitative correlational or experimental studies based on learning
setting
• Further experimental, correlational, and qualitative case studies to identify
the specific behaviors that correlate with each of the instructional process
design elements individually
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Conclusions
• The theoretical framework of
andragogy was inferentially
supported.
• The API has predictive abilities with
regard to online learner
satisfaction.
• The findings of the study provided
evidence of significant, positive,
predictive relationships
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Thank You!
Questions
Complete References list can be found in the dissertation
manuscript
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