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NORTHCENTRAL UNIVERSITY ASSIGNMENT COVER SHEET
Learner: Stephen W Watts
THIS FORM MUST BE COMPLETELY FILLED IN
Academic Integrity: All work submitted in each course must be the Learner’s own. This
includes all assignments, exams, term papers, and other projects required by the faculty mentor.
The known submission of another person’s work represented as that of the Learner’s without
properly citing the source of the work will be considered plagiarism and will result in an
unsatisfactory grade for the work submitted or for the entire course, and may result in academic
dismissal.
EDU7006-8
Dr. Theresa Thonhauser
Quantitative Research Design
6 Contributing to Theory
Assignment: Examine the literature in your topic area and identify five articles published
within the past five years that investigate mediating, moderating, or independent variables in an
attempt to contribute to theory in the topic area. Write a paper in which for each article, you: (a)
describe the theory the researchers explore. What are the key constructs in the theory? How are
they related? Identify which ones are cause, effect, mediating, or moderating constructs. How are
the constructs operationalized? (b) Briefly describe the study, including the number of
participants and research methods. (c) Briefly describe the statistical analyses used (d) Briefly
describe the findings and how the researchers interpreted them and their contribution to theory.
Using some or all of the five articles, argue for a gap in the knowledge in the topic area and
briefly describe a study involving mediator and or moderator variables that can contribute to
theory. Length: 5-7 pages (app. 350 words per page)
Faculty Use Only
Steve: Thank you for your revisions to this paper. The articles you selected here were much more
appropriate for the assignment. Please see my feedback below for more detailed comments. I can see
improvement in your writing since we first started our course, but there are still some small writing issues
here (see my edits/comments throughout the paper for details). Have you ever tried the Online Writing
Lab at NCU? If not, I encourage you to consider it – through the Smarthinking services at NCU, you can
submit your writing to the Online Writing Lab for writing feedback—you can find information about it in
the Writing Center. Thanks!
Don’t forget to submit your research questions or hypotheses in the next assignment. I won’t be able to
evaluate if ANOVA and t-tests are appropriate for your study unless I see those questions/hypotheses.
Theresa Thonhauser
Content Score: 100%
Writing Score: 93%
August 22, 2012
Running head: WattsSEDU7006-8-6
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Contributing to Theory: Independent, Mediating, Moderating, and Dependent Variables
Stephen W. Watts
Northcentral University
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Contributing to Theory: Independent, Mediating, Moderating, and Dependent Variables
The rapid advances of technology over the past decade have led to a dramatic shift in the
demographics of post-secondary students, as about 40% are over the age of 25 and a majority of
these more mature learners are increasingly choosing e-learning to pursue higher education (Ke
& Xie, 2009) and professional development (Gunawardena, Linder-VanBerschot, LaPointe, &
Rao, 2010). Adults, or nontraditional students, learn differently than traditional students or
younger adults who enter post-secondary education straight from secondary education (Bye,
Pushkar, & Conway, 2007; Ke & Xie, 2009; Kenner & Weinerman, 2011; Zemke & Zemke,
1995). Historically, these differences have been ignored in higher education, and in online
courses, where the same pedagogies and curriculum face both the traditional and non-traditional
learner (Ke & Xie, 2009). There has also been little research outside of higher education
regarding how mature adults learn best in a virtual classroom (Chen & Lien, 2011; Donavant,
2009). Articles specific to professional development and e-learning, published within the past
five years, have been chosen for analysis regarding their contributions to online learning theory
through operationalized independent, dependent, moderating, and mediating variables.
Article Analysis
The New, Modern Practice of Adult Education
In a three phase, quasi-experimental quantitative study of American police officers,
Donavant (2009) looked at the “efficacy of online education for professional development” (p.
239) and found that learning took place with respect to both online and traditional instruction and
that there was no “statistically significant difference in the effectiveness of the two delivery
methods” (p. 239). This study also showed no significant differences between these modes with
respect to gender, race, age, number of years on the force, or previous exposure to online
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education, but did show a significant association between level of formal education and potential
success with online learning. Phase one consisted of historical data of performance from various
courses without descriptive information. In phase three, open-ended questions were asked of
150 participants, and they indicated four attractive features of online education, which were; (a)
general convenience, (b) flexibility in scheduling, (c) remote access, and (d) self pacing of
learning. The least attractive feature was “the lack of personal interaction or face-to-face contact
with the facilitator or other learners” (p. 239). One problem noted was that “little research has
been conducted within the professional development environment, that arena involving training
relative to the current occupation of the adult learner” (p. 227).
The study’s theoretical framework was based on Andragogy, and Donavant (2009)
sought to expand knowledge of techniques for professional development in adult education since
empirical research “is almost nonexistent” (Donavant, 2009, p. 229). In effect, however, the
Donavant (2009) did not study techniques of adult education, but rather delivery methods and
their effect on learning. Two delivery methods were identified as the independent variable,
while effect on learning, the dependent variable, was based on participant perceptions regarding
willingness to continue to use, experience with, and practicality of online learning for delivery of
professional development training as mediating variables. Several analyses were run on the data,
including descriptive statistics, chi-squared, t-tests, and analysis of covariance.
The contributions of this study to theory are three-fold. First, Donavant (2009) noted that
there is little empirical research regarding professional development courses in online adult
education, as opposed to a large amount of online adult education research in higher education.
Of importance to theory is whether there is a difference between types of adult education. Do
adults seeking professional development learn differently or have different motivations than do
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adults in higher education programs? While this article does not directly look at this contribution
to theory; it does demonstrate that the mode of delivery for professional development courses
does not appear to matter. This result is similar to numerous studies in higher education showing
the same thing. Second, Donavant (2009) identified that online learning may not be effective or
practical in terms of certain types of learning. This article thus contributes to theory in
documenting that for law enforcement, online education is “an appropriate method of delivery
for professional development” (p. 238). Finally, Donavant (2009) contributed to theory and
more effective online training by documenting the factors of satisfaction and dissatisfaction with
online education. Without knowing what works, and what does not, it is impossible to improve.
Length of Online Course and Student Satisfaction
Ferguson and DeFelice (2010) presented an exceptional review of the literature regarding
the factors effecting satisfaction with courses taught online, concluding “that connectedness to
the course, either by participating collaboratively with other students or by interacting with the
professor, will likely impact student satisfaction” (p. 75) the most. Equivalency theory, which
posits that regardless of delivery mode “course learning experiences . . . should be designed in
order to provide equivalent learning” (p. 75), was utilized as the theoretical framework for this
study to determine if “there were differences in online student satisfaction, perceived learning,
and performance” (p. 76) when the independent variable was length of the course; in this case
five-weeks versus fifteen-weeks, while all other pedagogical factors were kept constant. The
dependent variable learning, was measured using “final grades from a total of 114 students . . .
from three summer [(5-week)] sessions and four full-semester [(15-week)] sessions” (p. 77).
Equivalency theory was supported in this study because students were taught the same material,
in the same ways, utilizing the same professor, in both formats. In part one of the study, 75
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graduate students were administered a 15-question Likert scale survey to measure the moderating
variables of student satisfaction and perceived learning. Statistical analyses of the data included
descriptive and t-tests to determine if there were differences between the 5-week and 15-week
formats regarding learning, student satisfaction, and perceived learning.
Students were significantly more satisfied with the interaction with the teacher in the
longer format, while students were significantly more satisfied with the interaction with fellow
students in the shorter format. No significant difference was found for perceived learning or
desire to take additional online classes between the two format lengths. Students in the shorter
sessions showed significantly stronger “academic performance than the full-semester students”
(Ferguson & DeFelice, 2010, p. 81). Improvements to the pedagogy of the class were identified
for both formats. In regard to the shorter format a shift needs to be made “to emphasize
interaction with the professor” (p. 81) and several possibilities were proposed. Limitations to the
study were that students in the shorter format (summer semester) may have been different from
those attending the longer format (regular semesters) and that students were not randomly
selected. This article contributes to adult learning theory by being “the first to explore how
different formats . . . influence student attitudes and academic performance” (p. 81).
Predictors of Learner Satisfaction and Transfer of Learning
In a mixed-methods design, Gunawardena et al. (2010) conducted a survey, face-to-face,
and phone interviews, and administered an open-ended questionnaire to gather data on the
perceptions of students, instructors, and instructional designers to determine that “online selfefficacy [was the] strongest predictor of learner satisfaction; [while] collegial support was the
strongest predictor of transfer of learning” (p. 207) in a professional development program. The
major problems in?? the current literature in terms of distance education in the corporate sector is
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that they describe only “specific contexts and programs” (p. 208) and there is a need to move
beyond case studies to determine the characteristics of training that “lead to learning gains,
transfer of learning, and satisfaction” (p. 208).
Four independent variables were measured in part one of the study, “online self-efficacy,
course design, learner-instructor interaction, and learner-learner interaction” (Gunawardena et
al., 2010, p. 211), with the dependent variable being online learning success. Mediating
variables were learner satisfaction and transfer of learning. All variables were operationalized as
scores on the Learner Satisfaction and Transfer-of-learning Questionnaire (LSTQ) developed by
the authors and validated prior to the study. Regression analysis identified a close relationship
between the independent variables and the dependent variable, with “88 percent of the total
variability” (p. 217) associated with the four factors. Gunawardena et al. (2010) contributed to
theory by adding to knowledge regarding adult professional development and “moved online
education research in corporate settings beyond descriptive case studies to understanding factors
that promote learner satisfaction and transfer of learning” (p. 224).
What Types of Learning Style Leads to Online Participation
Huang, Lin, and Huang (2012) extended previous research by testing a model that
examined the mediating process of prior knowledge in the relationship between learning style
and e-learning performance. They posited that (a) learning style is positively related to online
participation, (b) that online participation is positively related to e-learning performance, and (c)
the greater the prior knowledge, the stronger the relationship between online participation and
learning performance. This study included 219 college students in a single course and measured
(a) student learning style using the Index of Learning Styles (ILS) survey, (b) student online
participation through “recorded student online trails” (p. 344), (c) student performance as
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measured by scores on tests, (d) prior knowledge of the tool used in the course based on a 5point Likert scale, and (e) the control variables of gender, computer experience, and Internet
experience.
Huang et al. (2012) used structured equation modeling (SEM) to analyze the data.
Support was found that online participation is a mediating construct between learning style and
performance. The study also found that sensory learning style individuals tend to participate
more frequently and for a longer duration. Prior knowledge was shown to moderate the
relationship between participation and learning performance only in terms of passive
participation. Several recommendations were made by the Huang et al. (2012). First, “although
it is difficult to determine the degree of influence of the mediating construct, educational
institutions should take action to boost ‘students’ online participation in e-learning courses” (p.
347). Second, “most learners appear to be able to benefit [from e-learning] immediately” (p.
347). The authors also commented on several suggestions for further research, namely (a) the
model needs to be tested in different subject contexts, (b) additional mediating processes that
link learning styles and learning performance should be explored, and (c) a more mature,
professional, and autonomous set of online learners should be enlisted.
Faculty Actions that Result in Student Satisfaction in Online Course
This quantitative research study by Jackson, Jones, and Rodriguez (2010)???? correlated
faculty actions with student satisfaction in online classes at two community colleges in Texas.
Data for the study was obtained from student responses to each institution’s existing online
course evaluation. All online students were requested to fill out the online evaluation, and 426
students (30%) from College 1 and 1004 students (69%) from College 2 participated.
Descriptive statistics, bivariate correlations, and multiple regressions were used to identify the
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faculty actions that affected student satisfaction in online courses. Jackson, Jones, and
Rodriguez (2010) determined that “student satisfaction with online courses appears to be
impacted by instructor actions within the course” (p. 91). The highest correlations with student
satisfaction were “timeliness/accessibility of instructor, clearly stated expectations, instructor
enthusiasm, and comfortable climate” (p. 91) and a moderate correlation existed with activities.
Multiple regression analysis indicated that 69% of the variance of student satisfaction could be
explained by those independent variables.
Jackson et al. (2010) utilized a theoretical framework drawn from Chickering and
Gamson (1987) and “sought to clarify the relationship between student satisfaction and student
learning in the online classroom” (Jackson et al., 2010, p. 82). The data was analyzed separately
for each college, as well as across institutions, due to each college’s online evaluation being
different. For College 1, seven independent variables were selected, including directions,
timeliness, expectations, enthusiasm, classroom or campus?? climate, and activities that were
measured using a 5-point Likert scale. The dependent variable for College 1 was value, which
was also measured using a 5-point Likert scale. College 2 measured two independent variables,
timeliness and activities, and one dependent variable, value; all measured with a 5-point Likert
scale. The across institution interaction was analyzed using Levene’s test for equality of
variances, a one-way analysis of variance (ANOVA) to identify differences, and t-tests to
confirm the differences.
Jackson et al.’s (2010) article contributes to theory by identifying specific actions that
instructors can perform in their online courses to increase student satisfaction. The article
contains good discussion from the literature regarding the impact of faculty on student
satisfaction in online classes and then confirms this result in the findings. The findings clarify
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that instructor actions directly impact student satisfaction, and which actions are most effective
in doing so.
Gap Analysis
The largest factor of dissatisfaction in adult online learning is the lack of face-to-face
interaction by the learner with the facilitator or other learners (Alshare, Freeze, Lane, & Wen,
2011; Boling, Hough, Krinsky, Saleem, & Stevens, 2012; Donavant, 2009; Pigliapoco &
Bogliolo, 2008). Dissatisfaction culminates in markedly higher dropout rates (Al-Fahad. 2010;
Pigliapoco & Bogliolo, 2008), decreased motivation to learn (Omar, Kalulu, & Belmasrour,
2011; Park & Choi, 2009), less participation, and consequently, less learning (Jackson et al.,
2010; Martinez-Caro, 2009; Shea, Fredericksen, & Pickett, 2006; Zemke & Zemke, 1995). A
relationship has been demonstrated between online participation and learning performance
(Huang et al., 2012; Martinez-Caro, 2009; Pelz, 2010; Ruey, 2010), as well as between learning
performance and student satisfaction in online courses (Ali & Ahmad, 2011; Chen & Lien, 2011;
Ferguson & DeFelice, 2010; Kozub, 2010; Martinez-Caro, 2009). However, there is little
empirical research regarding adult online?? professional development or appropriate techniques
for teaching and engaging non-traditional learners (Chen & Lien, 2011; Donavant, 2009), or on
appropriate modes of interaction in learning management systems (So & Bonk, 2010). The
specific problem to investigate involves identifying factors in an online adult professional
development learning environment that can eliminate or moderate the lack of face-to-face
interaction, fostering increased learner participation, satisfaction, and perceived learning, which
contribute to online learning success. Knowledge gained will enlarge the currently small
knowledge base regarding online professional development training (Chen & Lien, 2011;
Donavant, 2009), will contribute a better understanding of facilitating engaging online
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instruction (Bradley, 2009; Huang et al., 2012), and assist in identifying the proper level and
types of media for use in the online classroom (Fletcher, Tobias, & Wisher, 2007; MartinezCaro, 2009).
Proposed Study
I propose a quasi-experimental nonequivalent groups study to investigate whether the
addition of a visual element (webcam) can foster increased online success as mediated by
increased learner participation, increased learner satisfaction, and increased perceived learning in
an online adult professional development learning environment. At least ten instructors will
teach two instances of two separate live virtual courses (LVC) for a US-based technology
company. One instance of each course will be a control and one will utilize the webcam to
promote additional interaction for the student-instructor relationships, and attempt to mitigate the
lack of face-to-face interaction noted as the primary source of dissatisfaction for online students.
The students of these LVC, who can sign in from any location worldwide, will be surveyed after
each class to ascertain their satisfaction, engagement, and perceived learning with the class as
measured by sections of the Learner Satisfaction and Transfer-of-learning Questionnaire (LSTQ)
developed by Gunawardena et al. (2010). A one-way analysis of variance (ANOVA) and t tests
will be conducted to determine whether the use of the visual element increases the mediating
variables of learner participation, satisfaction, or perceived learning in the experimental classes
versus the control classes thereby promoting online success.
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