Andragogy and Online Course Satisfaction: A Correlation Study
Dissertation Proposal
Submitted to Northcentral University
Graduate Faculty of the School of Education
in Partial Fulfillment of the
Requirements for the Degree of
DOCTOR OF PHILOSOPHY
by
STEPHEN W. WATTS
Prescott Valley, Arizona
December 2013
Abstract
The high rate of online course dropout has instigated several studies focused on learner
satisfaction with online learning. This study seeks to identify whether adult learner
characteristics and instructional process design elements facilitate online learner
satisfaction, thereby providing means of mitigating online dropout. The purpose of this
quantitative correlation study is to investigate relationships between adult learner
characteristics, instructional process design elements, and learner satisfaction among
adult learners in a postsecondary online. This study will evaluate the predictive value of
14 predictor variables; six adult learner characteristics and eight instructional process
design elements on the criterion variable of learner satisfaction. Participants will be
chosen using stratified random sampling at the school level to ensure a proportional mix
of qualifying learners from public state universities, public universities, and private
universities or colleges. Each participant will be over the age of 24, who has taken at least
one online course from an HLC-NCA accredited program with at least one physical
facility in the state of Missouri.
ii
Acknowledgements
Here I’d like to acknowledge all who have helped in this process. Thank you.
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Table of Contents
List of Tables ..................................................................................................................... vi
List of Figures ................................................................................................................... vii
Chapter 1: Introduction ....................................................................................................... 1
Background ................................................................................................................... 3
Statement of the Problem .............................................................................................. 3
Purpose of the Study ..................................................................................................... 4
Theoretical Framework ................................................................................................. 5
Research Questions ....................................................................................................... 8
Hypotheses (Quantitative/Mixed Studies Only) ............................................................ 8
Nature of the Study ....................................................................................................... 9
Significance of the Study ............................................................................................ 10
Definition of Key Terms ............................................................................................. 11
Summary ..................................................................................................................... 15
Chapter 2: Literature Review ............................................................................................ 17
Documentation ............................................................................................................ 17
Theme/Subtopic [repeat as needed] .............................Error! Bookmark not defined.
Summary ..................................................................................................................... 19
Chapter 3: Research Method ............................................................................................. 23
Research Methods and Design(s)................................................................................ 23
Population ................................................................................................................... 24
Sample......................................................................................................................... 25
Materials/Instruments ................................................................................................. 25
Operational Definition of Variables............................................................................ 28
Data Collection, Processing, and Analysis ................................................................. 33
Assumptions................................................................................................................ 35
Limitations .................................................................................................................. 35
Delimitations ............................................................................................................... 35
Ethical Assurances ...................................................................................................... 36
Summary ..................................................................................................................... 36
Chapter 4: Findings ........................................................................................................... 38
Results ......................................................................................................................... 38
Evaluation of Findings ................................................................................................ 38
Summary ..................................................................................................................... 38
Chapter 5: Implications, Recommendations, and Conclusions ........................................ 39
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Implications................................................................................................................. 39
Recommendations ....................................................................................................... 39
Conclusions ................................................................................................................. 39
References ......................................................................................................................... 40
Appendixes ....................................................................................................................... 57
Appendix A: Title ............................................................................................................. 58
Appendix B: Title ............................................................................................................. 61
Appendix N:…: Title ........................................................................................................ 64
v
List of Tables
Table 1 Factors in the API and Learner Satisfaction scale on the LSTQ ..........................27
vi
List of Figures
vii
1
Chapter 1: Introduction
Since 2000, technological advances in information and communication
technology have caused profound changes in the way many people communicate,
socialize, work, and receive training or education (Bala, 2010; Bolinger & Halupa, 2012).
Leaders of 65% of institutions of higher education consider online learning critical to
their long-term strategies (Allen & Seaman, 2011). The number of new online students is
outpacing the number of new traditional students by a proportion of 5 to 1, with 31% of
all college-level students taking at least one online class (Allen & Seaman, 2011).
These high numbers represent the abundant benefits that electronic learning
(eLearning) provides to learners. These benefits include the improvement of learning
efficiency (Cabrera-Lozoya, Cerdan, Cano, Garcia-Sanchez, & Lujan, 2012; Huang, Lin,
& Huang, 2012), improvements in learner behavior (Bhuasiri, Xaymoungkhoun, Zo, Rho,
& Ciganek, 2011), enhanced communication (Abrami, Bernard, Bures, Borokhovski, &
Tamim, 2010; Alshare, Freeze, Lane, & Wen, 2011), convenience (Bollinger & Halupa,
2012), time efficiencies (Pastore, 2012), and improved learning (Ismail, Gunasegaran, &
Idrus, 2010). Despite these benefits, the incidence of dropout or failure in online courses
is larger than for traditional courses. Although the percentages vary between programs;
dropout rates ranging between 2 and 5 times larger than rates for traditional courses have
been reported (Brown, 2012; Lee & Choi, 2011; Wilson & Allen, 2011). This high rate
of dropout in online courses has led to several studies that have focused on satisfaction
with online learning (Bollinger & Halupa, 2012; Gunawardena, Linder-VanBerschot,
LaPointe, & Rao, 2010); because satisfaction is considered to be the largest determinant
in reducing dropout (Chen & Lien, 2011; Kozub, 2010; Martinez-Caro, 2011).
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According to the theory of andragogy, adult students learn differently than do children
(Holton, Wilson, & Bates, 2009; Knowles, 1984; McGrath, 2009), and the successful
teaching of adults is optimized when (a) instructors engender an environment where the
learner is properly prepared, (b) the climate is encouraging, and (c) there is coordination
between instructor and student in planning learning, (d) diagnosing the learner’s specific
needs, (e) agreeing on learning objectives and (f) designing the necessary experience
through (g) learning activities and (h) evaluation (Gilbert, Schiff, & Cunliffe, 2013).
When adult students possess an intrinsic motivation to learn, prior experience, a need to
know, readiness to learn, are self-directed and learning is immediately applied to realworld situations, they may learn better (Cox, 2013).
Knowles (1995, 2005) originally codified these instructional process design
elements and adult learner characteristics and the theory of andragogy has had a strong
influence on distance and online education (Blaschke, 2012) as the theory addresses the
facilitation of a climate where students can learn (Marques, 2012; McGrath, 2009). Some
dropout factors have been mitigated by specific adult learner characteristics, including
(a) motivation (Omar, Kalulu, & Belmasrour, 2011; Park & Choi, 2009; Travis &
Rutherford, 2012), (b) self-efficacy (Chen & Lien, 2011; Gunawardena et al., 2010), and
(c) increased interaction (learner-to-learner and faculty-to-learner; Ali & Ahmad, 2011;
Alshare et al., 2011; Boling, Hough, Krinsky, Saleem, & Stevens, 2011; Donavant, 2009;
Morrow & Ackermann, 2012). When emphasized in online learning, researchers have
demonstrated that performance, participation, and satisfaction of adult learners increased
(Cacciamani, Cesareni, Martini, Ferrini, & Fujita, 2012; Cercone, 2008; Huang, Lin, &
Huang, 2012; Keengwe & Georgina, 2011).
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Background
Statement of the Problem
Dropout rates in online courses often exceed 30%; 2 to 5 times larger than
corresponding rates for traditional courses (Brown, 2012; Lee & Choi, 2011; Wilson &
Allen, 2011). The specific problem to be addressed is the low satisfaction among adults
in online postsecondary courses (Donavant, 2009; Huang et al., 2012; Watkins, 2005)
since learner satisfaction has been considered the largest determinant in reducing online
dropout (Chen & Lien, 2011; Kozub, 2010; Martinez-Caro, 2009). Determining factors
that engender learner satisfaction with online courses, which may reduce dropout, would
be a benefit to higher education (Lee & Choi, 2011; Levy, 2007; Willging & Johnson,
2009). Past researchers have affirmed that when specific learner characteristics and
instructional process design elements are present learner satisfaction is increased (Cox,
2013; Gilbert et al., 2013; Knowles, Holton, & Swanson, 2005), which may reduce the
incidence of dropout (Beqiri, Chase, & Bishka, 2010; Deil-Amen, 2011; Lee & Choi,
2011). Researchers have called for continued research to examine the learner
characteristics and instructional process design elements associated with learner
satisfaction (Abrami & Bernard, 2006; Burke & Hutchins, 2007; Gunawardena et al.,
2010; Holton et al., 2009). Therefore, online dropouts may be mitigated (Ali & Ahmad,
2011; Alshare et al., 2011; Boling et al., 2011; Chen & Lien, 2011; Morrow &
Ackermann, 2012; Omar et al., 2011; Travis & Rutherford, 2012) by establishing which
learner characteristics and instructional process design elements affect learner satisfaction
4
(Donavant, 2009; Gunawardena et al., 2010; Holton et al., 2009; Huang et al., 2012;
Taylor & Kroth, 2009).
Purpose of the Study
The purpose of this quantitative correlation study is to investigate relationships
between adult learner characteristics, instructional process design elements, and learner
satisfaction among adult learners in a postsecondary online environment with at least one
physical facility in Missouri. The specific adult learner characteristics and instructional
process design elements were selected based on Knowles’ (1973, 1975, 1980, 1984,
1995) theory of andragogy as the theoretical framework for the study. The 14 predictor
variables include six adult learner characteristics: (a) intrinsic motivation to learn, (b)
prior experience, (c) need to know, (d) readiness to learn, (e) self-directed learning, and
(f) orientation to learn; and eight instructional process design elements: (g) preparing the
learner, (h) climate setting, (i) mutual planning, (j) diagnosis of learning needs, (k) setting
of learning objectives, (l) designing the learning experience, (m) learning activities, and
(n) evaluation and serve as predictor variables (Knowles, 1995, 2005). The criterion
variable is learner satisfaction. The study target population includes adult (over age 24)
online learners attending a postsecondary institution accredited by the Higher Learning
Commission of the North Central Association of Colleges and Schools (HLC-NCA; see
Appendix A) with at least one physical facility in Missouri. According to a G*Power
analysis a minimum sample size of 194 is required (Faul, Erdfelder, Buchner, & Lang,
2009). Participants will be selected through stratified random sampling by first selecting
10 schools from Appendix A followed by a random selection of 1 in 5 qualifying students
from each of the participating postsecondary institutions. The 14 predictor variables will
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be measured by the 66-item Andragogy in Practice Inventory (API; Holton et al., 2009;
see Appendix B). The API is a psychometrically pre-validated instrument that will be
used to collect quantitative data for the characteristics and design elements (Holton et al.,
2009), and has been used in other studies with regression analysis with demonstrated
validity and reliability (Holton et al., 2009; Wilson, 2005). The criterion variable of
learner satisfaction will be measured by the pre-validated Satisfaction subscale of the
Learner Satisfaction and Transfer-of-Learning Questionnaire (LSTQ) that also has
demonstrated high reliability (Gunawardena et al., 2010). The 14 predictor variables will
be grouped into two sets, with six variables constituting learner characteristics and eight
variables constituting instructional process design elements. Hierarchical regression
analysis will be used for hypothesis testing to determine whether either or both of the two
sets significantly add to the prediction of the criterion variable satisfaction. Minimal
demographic characteristics of the study sample will be collected and reported. Study
results may offer information for instructors to determine which learner characteristics or
instructional process design elements predict online adult learner satisfaction.
Theoretical Framework
Andragogy, “the art and science of helping adults learn,” (Knowles, 1980, p. 43;
see also 1973, 1975, 1984, & 1995), is a foundational educational theory that has many
supporters and will serve as the theoretical framework for this study. The term was
originally coined by Kapp (1833) and philosophically flowed from Plato’s theory
regarding education (Abela, 2009). Knowles (1973, 1975, 1980, 1984, 1995) was the
leading proponent of andragogy as a theory of adult learning in the United States and
developed a number of tenets describing the adult learner. As the theoretical framework
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for the proposed study, andragogy focuses attention on certain salient characteristics for
teaching and learning while ignoring others (Young, 2008). Several other authors
(Karge, Phillips, Dodson, & McCabe, 2011) have used the term andragogy to identify
methods for teaching adult learners, and others (Baran, Correia, & Thompson, 2011) have
argued for the positive influence of andragogy in online learning.
Andragogy has had its critics. Blaschke (2012) noted that andragogy was
outmoded because of new technology and teaching methods, and Cercone (2008) and
McGrath (2009) argued that the theory had done almost nothing to provide clarity or
understanding of how learning occurs. According to Newman (2012), transformative
learning has replaced andragogy as the preeminent theory of adult learning. Other
authors (Guilbaud & Jerome-D’Emelia, 2008; McGrath, 2009; Taylor & Kroth, 2009)
have argued that andragogy is not a theory but rather a framework or a set of
assumptions. Specific criticisms of andragogy include (a) critiques of self-direction,
(b) critiques regarding motivation, (c) lack of reflection, (d) lack of accounting for
learning context, and (e) lack of empirical evidence. Knowles (1984) stated that adults
became more self-directed as they matured and that this self-direction guided their
learning; however, self-direction has been shown to not be unique to adults (Clapper,
2010; Taylor & Kroth, 2009). Cercone (2008) noted that all adults were not
automatically self-directed and that many may require assistance to become so. In the
United States, growth towards self-direction was found to be inhibited by a lack of desire
on the part of many learners to accept greater responsibility for learning (Dibiase &
Kidwai, 2010). These arguments were similar to critiques regarding motivation. Both
Abela (2009) and McGrath (2009) noted that andragogy lacked adequate explication
7
regarding motivation, did not include mention of extrinsic motivation, was inconsistent
regarding intrinsic motivation, and omitted an exploration of the role of instructors as an
important cause of motivation in learners.
Although andragogy is highly regarded as a theory, it has also been widely
criticized for its lack of empirical verification, despite having been presented as early as
1968 (Cercone, 2008; Henschke, 2011; Holton et al., 2009; McGrath, 2009; Taylor &
Kroth, 2009). Additionally, researchers have argued that the acceptance of andragogy as
the primary theory of adult learning is inappropriate (Holton et al., 2009; Taylor & Kroth,
2009). Since 1980, researchers have noted that the field of adult learning is dominated by
descriptive and qualitative research studies, particularly with regard to andragogy
(Brookfield, 1986; Holton et al., 2009; Long, Hiemstra, & Associates, 1980; Rachel,
2002). Merriam et al. (2007) stated that determining whether the theory of andragogy
engendered learner’s achievement and satisfaction in an empirical setting was overdue.
In the proposed study, the principles of andragogy provide the theoretical lens for
examination of the variables. Knowles (1984, 1995) and Knowles et al. (2005)
propounded that the presence of these adult learner characteristics and instructional
process design elements may provide an optimal learning environment for adults;
accordingly, the study objective is to examine these adult learner characteristics and the
instructional process design elements and their relationship to learner satisfaction in a
postsecondary online environment from the theoretical perspective of Knowles’ (1973,
1975, 1980, 1984, 1995) andragogy.
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Research Questions
This quantitative correlation study will be conducted to assess relationships
between learner characteristics, instructional process design elements, and learner
satisfaction within a diverse postsecondary online population. Following are the
questions that will guide this inquiry:
Q1. Do adult learner characteristics of (a) intrinsic motivation to learn, (b) prior
experience, (c) need to know, (d) readiness to learn, (e) self-directed learning, and (f)
orientation to learn predict learner satisfaction in a Missouri HLC-NCA accredited
postsecondary online environment?
Q2. Do the instructional process design elements (a) preparing the learner, (b)
climate setting, (c) mutual planning, (d) diagnosis of learning needs, (e) setting of
learning objectives, (f) designing the learning experience, (g) learning activities, and (h)
evaluation predict learner satisfaction in a Missouri HLC-NCA accredited postsecondary
online environment?
Hypotheses (Quantitative/Mixed Studies Only)
H10. The six learner characteristics of (a) intrinsic motivation to learn, (b) prior
experience, (c) need to know, (d) readiness to learn, (e) self-directed learning, and (f)
orientation to learn, collectively, are not predictors of postsecondary online learner
satisfaction.
H1a. The six learner characteristics of (a) intrinsic motivation to learn, (b) prior
experience, (c) need to know, (d) readiness to learn, (e) self-directed learning, and (f)
orientation to learn, collectively, are significant predictors of postsecondary online
learner satisfaction.
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H20. The eight instructional process design elements; (a) preparing the learner,
(b) climate setting, (c) mutual planning, (d) diagnosis of learning needs, (e) setting of
learning objectives, (f) designing the learning experience, (g) learning activities, and (h)
evaluation, collectively, are not predictors of postsecondary online learner satisfaction.
H2a. The eight instructional process design elements: (a) preparing the learner,
(b) climate setting, (c) mutual planning, (d) diagnosis of learning needs, (e) setting of
learning objectives, (f) designing the learning experience, (g) learning activities, and (h)
evaluation, collectively, are significant predictors of postsecondary online learner
satisfaction.
Nature of the Study
A quantitative, correlational design will be used to investigate the relationships
between adult learning characteristics and instructional design elements as predictor
variables and learner satisfaction as the criterion variable. A correlational design is most
appropriate for determining whether relationships between study variables exist, the
strength of those relationships, and the mechanisms by which they relate (Aiken & West,
1991; Miles & Shevlin, 2001). This study will evaluate the predictive value of 14
predictor variables; six adult learner characteristics and eight instructional process design
elements on the criterion variable of learner satisfaction (Aiken & West, 1991; Miles &
Shevlin, 2001). The API will be used to isolate and measure the presence or absence of
the adult learner characteristics of (a) intrinsic motivation to learn, (b) prior experience,
(c) need to know, (d) readiness to learn, (e) self-directed learning and (f) orientation to
learn and the instructional process design element of (g) preparing the learner, (h) climate
setting, (i) mutual planning, (j) diagnosis of learning needs, (k) setting of learning
10
objectives, (l) designing the learning experience, (m) learning activities, and (n)
evaluation in the online classroom (Holton et al., 2009).
A stratified random sample will be chosen to participate in the study from
postsecondary HLC-NCA accredited programs with at least one physical facility in the
state of Missouri. Each participant, who will have taken at least one online course, either
successfully or unsuccessfully, and be over the age of 24, will complete an online survey
after confirming acceptance of the informed consent. De-identified data will be retrieved
for analysis in encrypted form. The data will be analyzed using hierarchical regression
analysis (Aiken & West, 1991; Miles & Shevlin, 2001) to assess the relationships, if any,
between the predictor variables and the criterion variable (Hair, Black, Babin, &
Anderson, 2009). Hierarchical regression analysis will assess any variance explained in
online learner satisfaction by the adult learner characteristics and instructional process
design elements and determine whether either set is a significant predictor on the
criterion variable (Cohen, Cohen, West, & Aiken, 2003).
Significance of the Study
Because of the vast differences in dropout rates for online courses as compared to
traditional courses (Brown, 2012; Lee & Choi, 2011; Wilson & Allen, 2011) it is
important to identify factors that may minimize this phenomenon. One of the largest
determinants for reducing online dropout is learner satisfaction (Chen & Lien, 2011;
Kozub, 2010; Martinez-Caro, 2009). This study, by seeking more specific evidence
regarding factors that contribute to and engender learner satisfaction, may be useful in
reducing or curtailing the dropout rates of online programs (Ali & Ahmad, 2011; Alshare
et al., 2011; Boling et al., 2011; Morrow & Ackermann, 2012; Omar et al., 2011; Travis
11
& Rutherford, 2012) by seeking to stimulate in learners certain characteristics or engage
in specific instructional processes (Donavant, 2009; Gunawardena et al., 2010; Holton et
al., 2009; Huang et al., 2012; Taylor & Kroth, 2009).
Definition of Key Terms
Climate setting. For the purposes of this study, climate setting refers to one of
the eight andragogical instructional process design elements. Climate setting includes (a)
the physical setting (e.g., “temperature, ventilation, easy access to refreshments and rest
rooms, comfortable chairs, adequate light, good acoustics;” Knowles, 1995, p. 118); (b)
access to a rich supply of both human and material resources; and (c) a psychological
setting that is “relaxed, trusting, mutually respectful, informal, warm, collaborative,
supportive,” open, and authentic (Knowles et al., 2005, p. 116).
Designing the learning experience. Designing the learning experience refers to
one of the eight instructional process design elements. Designing the learning experience
consists of (a) focusing on areas of challenge identified by learners through selfdiagnostic techniques, (b) selecting the most appropriate format for learning, (c)
employing appropriate experiential learning methods and materials, and (d) sequencing
these methods and materials based on the learners’ needs (Knowles et al., 2005).
Diagnosis of learning needs. Diagnosis of learning needs refers to an
instructional process design element. Diagnosing learning needs consists of collaborative
work between the learner and the instructor to create an accurate gap analysis regarding
what is known versus what is needed to know from the learning opportunity. This
assessment of needs can be simple, elaborate, or somewhere in between (Knowles, 1995;
Knowles et al., 2005).
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Dropout. A dropout is a postsecondary learner who fails to complete a course
either by earning an incomplete or an “F” on the transcript or by withdrawing voluntarily
from a course after the school drop period, thereby incurring a financial penalty (Lee &
Choi, 2011).
Evaluation. Evaluation refers to an instructional process design element.
Optimally, evaluation occurs in four steps; (a) an ongoing collection of data as learning
occurs, (b) structured pre and posttests to ascertain learning gains, (c) assessment of
behavior changes consonant with the learning, and (d) identifying the effect of the new
behavior or learning on the organization (Knowles et al., 2005).
Intrinsic motivation to learn. For the purposes of this study, intrinsic
motivation to learn is an adult learner characteristic. Intrinsic motivation to learn refers
to a motivation to learn for its own sake, rather than for the sake of external drives,
rewards, or punishment avoidance (Abela, 2009; Blaschke, 2012; Chan, 2010; Clapper,
2010; Harper & Ross, 2011; Karge, Phillips, Dodson, & McCabe, 2011; Minter, 2011;
Wang & Kania-Gosche, 2011).
Learning activities. Learning activities are collaborative and based on
experiential techniques where the teacher or facilitator helps learners or students to
organize themselves to facilitate mutual inquiry and share responsibility and an
instructional process design element (Knowles et al., 2005).
Mutual planning. Mutual planning is a process element in an andragogical
classroom whereby the instructor and the learner identify and agree to the learning focus
of the course (Knowles, 1995; Knowles et al., 2005). This process element is based on
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engaging the learner and encouraging participation not only for the topic, but also in the
process of learning itself (Knowles, 1995; Knowles et al., 2005).
Need to know. Need to know is an adult learner characteristic and refers to the
evolution from subject-centered learning to problem-centered learning as people mature
(Keengwe & Georgina, 2011; McGrath, 2009) that is life-focused and task-oriented
(Chan, 2010; Kenner & Weinerman, 2011; Moore, 2010), and suggests that the demands
of life and family, drive adults to seek learning that is relevant to their home and working
lives (Cheng, Wang, Yang, Kinshuk, & Peng, 2011; Karge et al., 2011; Taylor & Kroth,
2009).
Online learning. Online learning consists of higher education courses that
typically have no face-to-face meetings between faculty and learners, and where at least
80% of the content is delivered online (Allen & Seaman, 2011).
Online learner satisfaction. Online learner satisfaction is a learner’s perception
of how well eLearning was received, accepted, and esteemed in an online educational
setting (Bollinger & Halupa, 2012; Gunawardena et al., 2010). Satisfaction is a complex
construct that researchers have shown leads to increases in motivation, engagement,
performance, learning, and success (Bollinger & Halupa, 2012; Gunawardena et al.,
2010; Kozub, 2010; Martinez-Caro, 2009; McGlone, 2011).
Orientation to learn. For the purposes of this study, orientation to learn is an
adult learner characteristic. Orientation to learn suggests “more effective learning will
occur when the adult learner can transfer the new knowledge to a real life problem”
(Wilson, 2005, p. 32). Adult learners are more problem-centered rather than subjectcentered in their approach to learning, and are oriented to learn about topics that will
14
complement their daily lives, rather than seeking knowledge just for the sake of
knowledge (Knowles, 1995; Knowles et al., 2005).
Prepare the learner. Prepare the learner is an instructional process design
element. Knowles (1995) identified that the modern adult needs to learn to become selfdirected, and preparation consists of receiving (a) training regarding proactive versus
reactive learning, (b) an introduction into the available resources for a course whether
those resources are people or materials, and (c) utilizing the proactive skills learned
(Knowles et al., 2005).
Prior Experience. Prior experience is an adult learner characteristic. Experience
allows three things in mature learners; it can be used as a resource in the learning process
(Green & Ballard, 2011), allows integration of new learning with past experience and
events (Cercone, 2008; Marques, 2012), and may be used to validate and build the selfconcept of the learner (Fidishun, 2011; Harper & Ross, 2011).
Readiness to learn. For the purposes of this study, readiness to learn is an adult
learner characteristic. Adults want (Cercone, 2008) and are ready to learn (Clapper,
2010; Kenner & Weinerman, 2011; Marques, 2012), but they want to have a reason for
learning something (Blaschke, 2012; Harper & Ross, 2011; Strang, 2009) and need to
know how it will benefit them (Cercone, 2008; McGrath, 2009; Moore, 2010).
Self-directed learning. Self-direction is an adult learner characteristic that
means that adults are independent (Kenner & Weinerman, 2011), responsible (Blaschke,
2012; Harper & Ross, 2011; Keengwe & Georgina, 2011; McGlone, 2011; Minter, 2011),
autonomous (Cercone, 2008; Chan, 2010), and expect to have some say in what they will
15
learn, and oppose learning that is foisted upon them (McGrath, 2009; Moore, 2010;
Taylor & Kroth, 2009).
Setting of learning objectives. Setting of learning objectives is an instructional
process design element and constitutes the process of mutually formulating activities and
learning based on the needs of the learner, the facilitator, the institution, and society
(Knowles et al., 2005).
Traditional learning. Traditional learning comprises higher education courses
where content is delivered either orally or through writing in a physical setting, and
where little to no online technology is utilized (Allen & Seaman, 2011).
Summary
Electronic learning has numerous advantages and is becoming more and more
popular in higher education. Dropout from eLearning programs, however, is significantly
higher than from more traditional programs. A primary determinant of dropout from
eLearning programs is learner satisfaction, and a number of studies have identified some
of the factors that contribute to this satisfaction. The problem to be addressed in this
study is the low satisfaction among adults in online postsecondary courses, and
determines factors that engender learner satisfaction with online courses, which may
reduce dropout and benefit higher education. The purpose of this quantitative correlation
study is to investigate relationships between adult learner characteristics, instructional
process design elements, and learner satisfaction among adult learners in a postsecondary
online environment with at least one physical facility in Missouri. This study will
evaluate the predictive value of 14 predictor variables; six adult learner characteristics
and eight instructional process design elements on the criterion variable of learner
16
satisfaction. The API will be used to isolate and measure the presence or absence of the
adult learner characteristics of (a) intrinsic motivation to learn, (b) prior experience, (c)
need to know, (d) readiness to learn, (e) self-directed learning and (f) orientation to learn
and the instructional process design element of (g) preparing the learner, (h) climate
setting, (i) mutual planning, (j) diagnosis of learning needs, (k) setting of learning
objectives, (l) designing the learning experience, (m) learning activities, and (n)
evaluation in the online classroom using a stratified random sample.
17
Chapter 2: Literature Review
The purpose of this quantitative correlation study is to investigate relationships
between adult learner characteristics, instructional process design elements, and learner
satisfaction among adult learners in a postsecondary online environment with at least one
physical facility in Missouri. A complete review of the germane literature identified nine
important themes for the development and exposition of the study topic. The context of
this study is online learning, so the technological advances contributing to this context are
essential to understand. This leads to a need to comprehend and fathom the benefits that
derive from eLearning to gain an even greater perspective of the milieu for this study.
Studies from the eLearning literature have sought to identify factors that engender
eLearning success; some of these factors constitute the variables that will be explored.
The foundational problem for this study is the larger dropout rates experienced by
providers of eLearning programs. The remaining sections of the literature review will
focus on the prevalence of dropout in eLearning programs, and factors and theories that
appear to contribute to this problem; learner, course or program, and environmental
factors. Finally, a review of what the literature says about learner satisfaction and its
mitigating effect on dropout, along with the factors that appear to produce and stimulate
learner satisfaction in online courses and programs will be conducted.
Documentation
The search for pertinent literature for this research was accomplished in two
stages. Initially, searches were conducted through Northcentral University’s Roadrunner
Search, utilizing the keywords of e-learning, online learning, computer-assisted learning,
web-based learning, and distributed learning, along with andragogy, adult learning,
18
satisfaction, and dropout within the interval 2009 through 2014. These searches focused
on the EBSCOhost, ERIC, ProQuest, SAGE Journals, and SpringerLink databases. After
a careful review and choosing of articles appropriate to the subject of adult online
learning and learner satisfaction, the references of the chosen articles were further
searched for additional articles apposite to the current study.
Online Technological Advances
Purported Benefits of eLearning
Factors that Bring eLearning Success
Learner–instructor relationship.
Learner-learner interactions.
Learner-content interaction and reflection.
Collaboration and development of a sense of community.
Immediate real world application of learning.
Learner motivation.
19
eLearning and Dropout
Learner Factors
Academic background.
Relevant experiences.
Relevant skills.
Learner psychological attributes.
Adult eLearning characteristics
Learner’s intrinsic motivation to learn.
Acknowledging prior experience.
Learner’s need to know.
Learner’s readiness to learn.
Learner’s self-direction and self-determination.
20
Learner’s orientation to learn.
Course or Program Factors
Institutional support.
Learner interactions.
Course design.
Preparing the learner to learn.
Setting the climate for learning.
Learner-instructor mutual planning.
Diagnosing the learner’s learning needs.
Setting of learning objectives.
Designing the learning experience.
21
Implementation of learning activities.
Evaluating learning.
Environmental Factors
Work commitments.
Supportive environment.
Learner Satisfaction and Dropout
Factors that Engender eLearner Satisfaction
Summary
To determine if instruction is successful, it is necessary to accurately measure
whether learning has occurred. Because learning is an internal process and its effects are
not usually visible to the outward observer, several elements have been researched to
determine how well they measure actual learning. Learner satisfaction has been
demonstrated to be an important construct regarding the efficacy of learning and learning
transfer, of learner motivation, engagement, and success, and is a strong predictor of
learner persistence in online programs. Successful eLearning programs have been shown
to have many andragogical characteristics in their assumptions and design considerations.
22
Many instructors subscribe to the principles of andragogy as the theory of adult learning,
or at minimum the basis for their implementation of teaching. Hundreds of anecdotal and
descriptive reports identify uses and support for andragogy in adult online education, but
there are few empirical studies that corroborate andragogy as a theory that has specific
applicability (Holton et al., 2009; Taylor & Kroth, 2009). Hunches, instinct, and intuition
rule the field, where “the art of andragogy may be dominant over the science” (Rachel,
2002, p. 212). There has been an emphasis on practice without determining whether the
learner characteristics and instructional process design elements influence credible
outcome measures (Holton et al., 2009). In terms of adult learning outcomes, there are
few studies that definitively identify whether andragogy makes a difference (Henschke,
2011; Holton et al., 2009; Merriam et al., 2007).
23
Chapter 3: Research Method
The purpose of this quantitative, correlational study is to investigate relationships,
if any, between adult learner characteristics, instructional process design elements, and
learner satisfaction among adult learners in a postsecondary online environment with at
least one physical facility in Missouri. The problem to be addressed is the low
satisfaction among adults in online postsecondary courses since learner satisfaction has
been considered the largest determinant in reducing online dropout (Chen & Lien, 2011;
Kozub, 2010; Martinez-Caro, 2009). This study seeks to extend current knowledge in the
mitigation of adult online dropout through determining which adult learner characteristics
and instructional process design elements engender improvement in learner satisfaction
(Donavant, 2009; Gunawardena et al., 2010; Holton et al., 2009; Huang et al., 2012;
Taylor & Kroth, 2009).
Research Methods and Design(s)
A correlational design is most appropriate for determining whether relationships
between the study variables exist, the strength of existing relationships, and the
mechanisms by which they relate (Aiken & West, 1991; Miles & Shevlin, 2001);
therefore, a correlation design will be used to explain the study constructs as
operationalized variables (Licht, 1995). A quantitative correlational design is appropriate
to evaluate the predictive value of 14 predictor variables: six adult learner characteristics
and eight instructional process design elements on the criterion variable of learner
satisfaction (Aiken & West, 1991; Miles & Shevlin, 2001). Results of this study may
support the applicability of the adult learner characteristics; (a) intrinsic motivation to
learn, (b) prior experience, (c) need to know, (d) readiness to learn, (e) self-directed
24
learning, and (f) orientation to learn, and the eight andragogical process design elements
of (g) preparing the learner, (h) climate setting, (i) mutual planning, (j) diagnosis of
learning needs, (k) setting of learning objectives, (l) designing the learning experience,
(m) learning activities, and (n) evaluation in instructional models for adult online higher
education courses, and thereby improve the predictability of theory, characteristics, and
process elements.
Descriptive and qualitative studies dominate the field of adult learning, especially
with regards to andragogy; therefore, another qualitative study is not an optimal choice
for furthering knowledge in the field of adult education (Brookfield, 1986; Long et al.,
1980; Merriam et al., 2007; Rachel, 2002; Taylor & Kroth, 2009). An experimental or
quasi-experimental study involves variables that are manipulated while all others are held
constant can be problematic in an educational setting and not appropriate for the number
of variables required for this study. Correlational studies are specifically useful in
situations where prediction of the effects of variables upon one another or for further
exploration and explication of these variables is desirable (Aiken & West, 1991; Licht,
1995; Miles & Shevlin, 2001). The proposed study will seek to determine whether the
variables are associated and predict online learner satisfaction.
Population
The population for this study consists of online postsecondary students who are
over age 24 and who attend a postsecondary institution accredited by the HLC-NCA with
at least one physical facility in Missouri who will access an online survey through a link
sent to them by e-mail. In the State of Missouri there are four schools in the state
university system with an enrollment of 73,565 (University of Missouri, 2011), there are
25
nine public universities with an enrollment of 68,851 (U.S. Department of Education,
2009), and there are 23 private colleges and universities with an enrollment of 87,369
(U.S. Department of Education, 2009). Of the almost 230,000 students enrolled in
Missouri, about 37.2% are adults over the age of 24 (U.S. Department of Education,
2009), and 31.3% have taken at least one course online (Hoskins, 2012).
Sample
The sample will be chosen through stratified random sampling. Based on an
assumed response rate of 5% a total of 3,900 students in the target population will need to
be solicited. Schools will be chosen through stratified random sampling based on the
stratum listed above from the list of all qualifying schools that will serve as the sampling
frame (see Appendix A), selecting sufficient schools so that the number of potential
subjects is three times larger than is needful for the sample, with the same proportion as
total enrollments; public state university (3,750), public university (3, 510), and private
university or college (4,440). From each of these schools, 1 in 3 randomly selected
qualifying students will receive an email inviting them to participate in the study,
providing a representative sample of the target population. Each email will briefly
describe the study, along with the school’s endorsement and request to participate. The
questions will be presented to the user in blocks of ten and will be encrypted on the
download, while answers will be encrypted and stored on the servers at Survey Gizmo.
De-identified data will be retrieved for analysis in encrypted form.
Materials/Instruments
An online version of the API will be presented to the study sample and used to
collect demographic data as well as responses regarding the study’s 14 predictor
26
variables. Since 2005, researchers have focused on the creation of a measurement
instrument to assess the validity of adult learner characteristics and instructional process
design elements empirically (Holton et al., 2009; Taylor & Kroth, 2009; Wilson, 2005).
The API was created with this need in mind and is used for isolating and measuring these
adult learner characteristics and instructional process design elements and their
application in the classroom (Holton et al., 2009). The API has been found to provide
sound psychometric qualities that measure many of the adult learner characteristics and
instructional process design elements with validity and reliability. The six adult learner
characteristics that are measured in the API are (a) intrinsic motivation to learn, (b) prior
experience, (c) need to know, (d) readiness to learn, (e) self-directed learning, and (f)
orientation to learn (Holton et al., 2009). The eight instructional process design elements
are (g) preparing the learner, (h) climate setting, (i) mutual planning, (j) diagnosis of
learning needs, (k) setting of learning objectives, (l) designing the learning experience,
(m) learning activities, and (n) evaluation (Holton et al., 2009). The API was originally
produced because of a perceived lack of empirical rigor in the practice of andragogy in
the field. The current version of the API consists of 60 five-point Likert-type scale
questions. Of these, 24 questions determine the learner’s assessment of whether a course
conforms to the adult learner characteristics propounded by Knowles and his associates,
while 36 questions determine conformity with andragogical instructional process design
elements. A factor analysis of the questions and constructs measured by the API was
previously conducted. From that analysis, the eigenvalues and Cronbach’s coefficient
alpha showing each factor’s reliability are presented in Table 1. In addition, Table 1
shows the variance explained between the various learner characteristics and process
27
design elements and two student outcomes, learning and satisfaction in a single MBA
degree program (Holton et al., 2009).
Table 1
Factors in the API and Learner Satisfaction scale on the LSTQ
Factor
Eigenvalue
Intrinsic motivation to learn
Prior Experience
Need to Know
Readiness to learn
Self-directed learning
Orientation to learn
Prepare the learner
Climate setting
Mutual planning
Diagnosis of learning needs
Setting of learning objectives
Designing the learning experience
Learning activities
Evaluation
Learner online satisfaction
15.69
1.63
1.51
1.26
1.10
-1.53
3.14
--17.38
1.48
1.29
1.82
--
Variance
Explained
44.8%
4.7%
4.3%
3.6%
3.2%
-4.6%
7.5%
--41.4%
3.5%
3.1%
4.3%
--
Cronbach’s Alpha
.93
.84
.76
.81
.74
-.88
.91
--.90
.94
.68
.86
.83
In a previous study in which the API was validated, three of the constructs did not
emerge, and one had weaker reliability than is optimal (Holton et al., 2009). The
orientation to learn construct was undifferentiatable from the motivation construct and
was included in that construct in the previous study (Holton et al., 2009). In this version
of the API, the questions regarding orientation to learn have been modified to
operationalize the construct (R. Bates, personal communication, February 19, 2013). The
mutual planning construct was excluded from the earlier API as it was perceived that it
would be inappropriate in a higher education setting (Holton et al., 2009; Wilson, 2005).
Questions have been added to represent the construct of mutual planning in this version
of the API to determine if the original assumption regarding applicability in higher
28
education was correct (R. Bates, personal communication, February 19, 2013). The
diagnosis of learning needs construct did not emerge from the data in the previous study
because the questions were weak and cross loaded with other factors and did not provide
sufficient reliability (Holton et al., 2009; Wilson, 2005). The questions representing the
construct of diagnosis of learning needs have been modified to better represent the
construct in this version of the API (R. Bates, personal communication, February 19,
2013). The learning activities construct in the API had a lower Cronbach’s alpha than is
normally acceptable for internal consistency (Hair et al., 2009; Nunnaly, 1978).
Questions have been added to operationalize the construct of learning activities in this
version of the API (R. Bates, personal communication, February 19, 2013), and a post
hoc Cronbach’s alpha will be calculated prior to data analysis to determine the reliability
of the instrument.
The LSTQ was originally designed with eight subscales to identify levels of
online learner satisfaction in relationship to other predictor variables in a separate study
from the validation performed on the API (Gunawardena et al., 2010). In the present
research study only the learner satisfaction subscale will be utilized to measure the
criterion variable of learner satisfaction, and the corresponding validated Cronbach’s
alpha for that subscale is reported in Table 1.
Operational Definition of Variables
In this study, the relationship of six adult learner characteristics and eight
instructional process design elements will be examined for their grouped and individual
impact on learner satisfaction in an online environment. The internal reliability of these
learner characteristics and instructional process design elements will also be calculated to
29
determine how well appropriate questions measure each construct. The 14 predictor
variables (a) intrinsic motivation to learn, (b) prior experience, (c) need to know, (d)
readiness to learn, (e) self-directed learning, (f) orientation to learn, (g) prepare the
learner, (h) climate setting, (i) mutual planning, (j) diagnosis of learning needs, (k) setting
of learning objectives, (l) designing of learning experience, (m) learning activities, and
(n) evaluation are operationally defined below, as is the single criterion variable, learner
online satisfaction.
Intrinsic motivation to learn. The andragogical learner characteristic of
intrinsic motivation to learn is an interval-level predictor variable (Miles & Shevlin,
2001) and will measure the amount of motivation the learner had to apply what was
learned to their life or work (Ali & Ahmad, 2011; Bye et al., 2007; Galbraith & Fouch,
2007; Kalyuga, 2011; Karge et al., 2011; Simonson et al., 1999). Intrinsic motivation to
learn is a construct that will be derived from the API and consists of four (1, 4, 5, & 9) 5point Likert-type questions that range from 1 (strongly disagree) to 5 (strongly agree).
Prior experience. The andragogical learner characteristic of prior experience is
an interval-level predictor variable and will measure whether the learner’s prior
experience was utilized in the learning experience (Allen et al., 2009; Blaschke, 2012;
Cabrera-Lozoya et al., 2012; Chen & Lien, 2011; Hurtado & Guerrero, 2009; Lee &
Choi, 2011; Tapscott & Williams, 2010). Prior experience is a construct that will be
derived from the API and consists of three (3, 10, & 17) 5-point Likert-type questions
that range from 1 (strongly disagree) to 5 (strongly agree).
Need to know. The andragogical learner characteristic of need to know is an
interval-level predictor variable and will measure how well the learning corresponded to
30
the learner’s needs (Baskas, 2011a; Fidishun, 2011; Gibbons & Wentworth, 2001;
Kenner & Weinerman, 2011; Kiliç-Cakmak, 2010; Strang, 2009). Need to know is a
construct that will be derived from the API and consists of four (6, 7, 18, & 24) 5-point
Likert-type questions that range from 1 (strongly disagree) to 5 (strongly agree).
Readiness to learn. The andragogical learner characteristic of readiness to learn
is an interval-level predictor variable and will measure how well the learner took
responsibility for their learning (Cercone, 2008; Chyung & Vachone, 2005; Kenner &
Weinerman, 2011; Taylor & Kroth, 2009). Readiness to learn is a construct that will be
derived from the API and consists of four (11, 15, 20, & 23) 5-point Likert-type questions
that range from 1 (strongly disagree) to 5 (strongly agree).
Self-directed learning. The andragogical learner characteristic of self-directed
learning is an interval-level predictor variable and will measure the amount of control the
learner had over the learning (Blanchard et al., 2011; Guilbaud & Jermoe-D’Emilia,
2008; Kistler, 2011; McGlone, 2011). Self-directedness is a construct that will be
derived from the API and consists of five (2, 8, 12, 14, & 16) 5-point Likert-type
questions that range from 1 (strongly disagree) to 5 (strongly agree).
Orientation to learn. The andragogical characteristic of orientation to learn is an
interval-level predictor variable and will measure how applicable the learner felt the
learning was to his or her needs and problems (Ghost Bear, 2012, Goddu, 2012, Knowles,
1995, Knowles et al., 2005; Lee et al., 2011; Taylor & Kroth, 2009). Orientation to learn
is a construct that will be derived from the API and consists of four (13, 19, 21, & 22) 5point Likert-type questions that range from 1 (strongly disagree) to 5 (strongly agree).
31
Prepare the learner. The andragogical instructional process design element of
prepare the learner is an interval-level predictor variable and will measure how well
prepared the learner felt he or she was for the learning experience (Knowles et al., 2005;
Lee & Choi, 2011). Prepare the learner is a construct that will be derived from the API
and consists of five (25, 27, 29, 32, & 51) 5-point Likert-type questions that range from 1
(strongly disagree) to 5 (strongly agree).
Climate setting. The andragogical instructional process design element of
climate setting is an interval-level predictor variable and will measure the comfort level
of the learner during the learning experience (Cercone, 2008; Jackson et al., 2010; Omar
et al., 2011). Climate setting is a construct that will be derived from the API and consists
of six (28, 30, 33, 35, 38, & 40) 5-point Likert-type questions that range from 1 (strongly
disagree) to 5 (strongly agree).
Mutual planning. The andragogical instructional process design element of
mutual planning is an interval-level predictor variable and will measure the amount of
planning the learner took part in with the instructor and other learners to determine what
was to be learned (Holton et al., 2009; Revere et al., 2012). Mutual planning is a
construct that will be derived from the API and consists of four (26, 37, 39, & 56) 5-point
Likert-type questions that range from 1 (strongly disagree) to 5 (strongly agree).
Diagnosis of learning needs. The andragogical instructional process design
element of diagnosis of learning needs is an interval-level predictor variable and will
measure whether analysis occurred to assist the learner determine his or her learning
needs (Knowles et al., 2005; Taylor & Kroth, 2009; Wilson, 2005). Diagnosis of
learning needs is a construct that will be derived from the API and consists of four (34,
32
41, 42, & 49) 5-point Likert-type questions that range from 1 (strongly disagree) to 5
(strongly agree).
Setting of learning objectives. The andragogical instructional process design
element of setting of learning objectives is an interval-level predictor variable and will
measure the learners experience in setting individualized learning objectives (Lee &
Choi, 2011; Mezirow, 1997; Wang & Kania-Gosche, 2011). Setting of learning
objectives is a construct that will be derived from the API and consists of five (31, 43, 44,
45, & 47) 5-point Likert-type questions that range from 1 (strongly disagree) to 5
(strongly agree).
Designing the learning experience. The andragogical instructional process
design element of designing the learning experience is an interval-level predictor variable
and will measure how flexible the learning experience was regarding its design
(Bransford et al., 2005; Cornelius et al., 2011; Kash & Dessinger, 2010). Designing the
learning experience is a construct that will be derived from the API and consists of four
(36, 46, 50, & 52) 5-point Likert-type questions that range from 1 (strongly disagree) to 5
(strongly agree).
Learning activities. The andragogical process element of learning activities is an
interval-level predictor variable and will measure the interactivity of the learning
environment (Allen et al., 2009; Baran et al., 2011; Chickering & Gamson, 1987; Revere
& Kovach, 2011). Learning activities is a construct that will be derived from the API and
consists of five (48, 53, 55, 57, & 59) 5-point Likert-type questions that range from 1
(strongly disagree) to 5 (strongly agree).
33
Evaluation. The andragogical instructional process design element of evaluation
is an interval-level predictor variable and will measure the utility of the evaluation
methods regarding the learner’s learning (Ally, 2008; Bradley, 2009; Bransford et al.,
2005; George, 2013; Ghost Bear, 2012). Evaluation is a construct that will be derived
from the API and consists of three (54, 58, & 60) 5-point Likert-type questions that range
from 1 (strongly disagree) to 5 (strongly agree).
Learner online satisfaction. Learner satisfaction is the interval-level criterion
variable. Researchers have shown that as learner satisfaction increases so does
persistence (Gunarwardena et al., 2010; Hoskins, 2012; Joo et al. 2011; Lee & Choi,
2011) and learning outcomes (Gunawardena et al., 2010; Kozub, 2010; Martinez-Caro,
2009; McGlone, 2011). Learner satisfaction will be calculated from the Learner
satisfaction subscale of the LSTQ; consisting of five 5-point Likert-type questions that
range from 1 (strongly disagree) to 5 (strongly agree).
Data Collection, Processing, and Analysis
Data collection. The provosts of postsecondary HLC-NCA accredited programs
with physical facilities in the state of Missouri will be approached, the study explained,
and permission requested to include learners from their schools in the study.
Participating school’s provosts will be requested to write a letter of endorsement to their
learners requesting them to volunteer for the study. The provosts will also be requested
to send an e-mail with this endorsement and an electronic link to an online survey to all
learners who have taken at least one online course, either successfully or unsuccessfully,
and who are over the age of 24. The survey will be a combination of two pre-validated
instruments, Holton et al.’s (2009) 66-item API, which measures six adult learner
34
characteristics, eight andragogical instructional process design elements, and six
demographic questions (see Appendix B), and the 5-item Satisfaction subscale of the
LSTQ to determine learner satisfaction (Gunawardena et al., 2010) with their most recent
online course (see Appendix B). Using an a priori analysis the total number of
participants will need to exceed 194 to have sufficient power to be assured of obtaining a
significant result if one exists (delta = 0.15, alpha = .05, beta = .05).
Data analysis. Data collected will be reviewed to ensure completeness, and
analyzed using hierarchical regression analysis for hypothesis testing (Aiken & West,
1991; Miles & Shevlin, 2001) to assess the relationship of the predictor variables to the
criterion variable (Hair et al., 2009) using IBM SPSS Statistics Package Version 21.
Hierarchical regression analysis will assess any variance explained in online learner
satisfaction by the adult learner characteristics and instructional process design elements
and determine whether either set is a significant predictor on the criterion variable
(Cohen et al., 2003). Hierarchical regression analysis allows for measuring the total
variance of a set of variables, while controlling for the effects of the other set on online
learner satisfaction (Cohen et al., 2003). The results of the regression analysis will be
used to determine the predictor relationship between the six learner characteristics and
eight process design elements and the criterion variable collectively (Cohen et al., 2003).
As part of the data analysis, the reliability of the modified API and the Satisfaction
subscale of the LSTQ will also be analyzed using confirmatory factor analysis (Albright
& Park, 2008; Bartholomew, Steele, Moustaki, & Galbraith, 2008). Although previous
studies have determined that demographic variables such as gender, ethnicity, and level
of education are not significant predictors of learner satisfaction (Bhusasiri et al., 2012) a
35
separate analysis will be conducted to determine whether any significant differences exist
among the demographic data and the criterion variable.
Assumptions
Limitations
Surveys have many advantages, but they cannot measure the population exactly
on any indices, but provide an estimate of the true population. With surveys it is possible
that participants may not answer all questions, may intentionally misreport, or may have
poor recall of the events or circumstances requested (Glasow, 2005).
Delimitations
Several choices have been made to narrow the scope of this study; namely,
participants will be postsecondary students, have attended at least one online course, be
over the age of 24, and the school where they attended will have at least one physical
facility in the state of Missouri and be HLC-NCA accredited. A theoretical framework of
andragogy implies that the sample will consist of adults, hence the strictures of the
participants attending a postsecondary institution and being over the age of 24. The topic
of interest is online course satisfaction, indicating that participants must have some
experience with this method of delivery. An HLC-NCA accredited program ensures that
an accredited school has a clearly stated mission, and its operations are based on that
mission, that the school acts in an ethical manner, provides a high quality education
through all of its delivery methods, is always seeking to improve its offerings, and has
sufficient resources to continue with these criterion (HLC-NCA, 2013). Because of the
expected high standards and quality of an accredited school, the researcher may
36
determine that the online program meets certain minimal requirements. Finally, there are
many accredited programs, so to narrow the scope of the study it was determined to only
include postsecondary schools that have at least one physical facility in the state of
Missouri.
Ethical Assurances
Before collecting any data, the appropriate forms will be completed and submitted
to Northcentral University’s Institutional Review Board (IRB), along with the IRB’s of
each participating school, and approval to conduct the research will be received from all.
Following IRB approvals, solicitation emails will be sent to potential participants. Each
participant will be presented with an informed consent page written at an eighth grade
comprehension level, and the following elements; (a) an explanation of the research
being conducted, (b) associated risks, (c) what the study is designed to determine, (d) a
statement regarding confidentiality, (e) researcher contact information, and (f) a
statement regarding voluntary participation and non-consequential withdrawal
(USDHHS, 1979). An option will be provided for the learner to print the informed
consent page. Since the informed consent will be entered online, acceptance will consist
of the participant typing their full name and clicking on a link to enter the study. No
possibility will exist for collecting data unknowingly from participants since informed
consent will be presented to each participant before collection of data, and participant
names will not be collected as part of the data.
Summary
The purpose of this quantitative correlational study is to investigate relationships
between the six adult learner characteristics and eight instructional process design
37
elements in an adult online learning environment, jointly and severally, and learner
satisfaction. The population of interest in this study consists of postsecondary learners
who have taken at least one online course from an HLC-NCA accredited program with
physical facilities in the state of Missouri (see Appendix A). Data will be collected from
participants, after obtaining appropriate informed consent, through access to an online
survey with 72 questions consisting of two pre-validated instruments; the API (Holton et
al., 2009) and the Satisfaction subscale of the LSTQ (Gunawardena et al., 2010). This
data will be analyzed using hierarchical regression analysis to determine the relationship
that the six learner characteristics and eight instructional process design elements have,
individually or collectively, with learner satisfaction (Aiken & West, 1991; Cohen et al.,
2003; Miles & Shevlin, 2001). The study results may add to the limited store of
quantitative empirical research on the effect of andragogy on learning outcomes
(Henschke, 2011; Holton et al., 2009; Taylor & Kroth, 2009), and specifically, whether
adult learner characteristics and instructional process design elements predict and
enhance learner satisfaction in a postsecondary online environment.
38
Chapter 4: Findings
Results
Evaluation of Findings
Summary
39
Chapter 5: Implications, Recommendations, and Conclusions
Implications
Recommendations
Conclusions
40
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Appendixes
58
Appendix A: Higher Learning Commission of the North Central Association of
Colleges and Schools Institutions with Physical Facilities in Missouri
University of Missouri System
Missouri University of Science and Technology
University of Missouri – Columbia
University of Missouri – Kansas City
University of Missouri – St. Louis
Public Universities
DeVry University – Missouri
Harris-Stowe State University
Missouri Southern State University
Missouri State University - Springfield
Missouri State University – West Plains
Northwest Missouri State University
Southeast Missouri State University
Missouri Western State University
University of Central Missouri
University of Phoenix – Kansas City Campus
University of Phoenix – Springfield Campus
University of Phoenix – St. Louis Campus
Private Colleges and Universities
Central Methodist University – College of Graduate and Extended Studies
Columbia College
59
Cottey College
Cox College
Crowder College
Culver-Stockton College
Drury University
East Central College
Fontbonne University
Hannibal-Lagrange College
Jefferson College
Lindenwood University
Linn State Technical College
Maryville University of Saint Louis
Metropolitan Community College – Longview
Metropolitan Community College – Penn Valley
Missouri Southern State University
Missouri State University - Springfield
Missouri State University – West Plains
Missouri Valley College
National American University – Independence
National American University – Zona Rosa
North Central Missouri College
Saint Louis Community College – Florissant Valley
Saint Louis Community College – Forest Park
60
Saint Louis Community College – Meramac
Saint Louis Community College – Wildwood
Saint Louis University
Saint Charles Community College
State Fair Community College
Stephens College
Three Rivers Community College
Webster University
William Woods University
61
Appendix B: Permission to Use Instruments
Learner Satisfaction and Transfer of Learning Survey
62
Andragogy in Practices Inventory
63
64
Appendix N:…: Title