· Assignment 3 Creating a Compelling VisionLeaders today must be .docx

· Assignment 3: Creating a Compelling Vision
Leaders today must be able to create a compelling vision for the
organization. They also must be able to create an aligned
strategy and then execute it. Visions have two parts, the
envisioned future and the core values that support that vision of
the future. The ability to create a compelling vision is the
primary distinction between leadership and management.
Leaders need to create a vision that will frame the decisions and
behavior of the organization and keep it focused on the future
while also delivering on the short-term goals.
To learn more about organizational vision statements, do an
Internet search and review various vision statements.
In this assignment, you will consider yourself as a leader of an
organization and write a vision statement and supporting values
statement.
Select an organization of choice. This could be an organization
that you are familiar with, or a fictitious organization. Then,
respond to the following:
· Provide the name and description of the organization. In the
description, be sure to include the purpose of the organization,
the products or services it provides, and the description of its
customer base.
· Describe the core values of the organization. Why are these
specific values important to the organization?
· Describe the benefits and purpose for an organizational vision
statement.
· Develop a vision statement for this organization. When
developing a vision statement, be mindful of the module
readings and lecture materials.
· In the vision statement, be sure to communicate the future
goals and aspirations of the organization.
· Once you have developed the vision statement, describe how
you would communicate the statement to the organizational
stakeholders, that is, the owners, employees, vendors, and
customers.

· How would you incorporate the communication of the vision
into the new employee on-boarding and ongoing training?
Write your response in approximately 3–5 pages in Microsoft
Word. Apply APA standards to citation of sources.
Use the following file naming convention:
LastnameFirstInitial_M1_A3.doc. For example, if your name is
John Smith, your document will be named SmithJ_M1_A3.doc.
By the due date assigned, deliver your assignment to the
Submissions Area.
Assignment 3 Grading Criteria
Maximum Points
Chose and described the organization. The description included
the purpose of the organization, the products or services the
organization provides, and the description of its customer base.
16
Developed a vision statement for the organization. Ensured to
accurately communicate the goals and aspirations of the
organization in the vision statement.
24
Ensured that the incorporation and communication strategy for
the vision statement is clear, detailed, well thought out and
realistic.
28
Evaluated and explained which values are most important to the
organization.
24
Wrote in a clear, concise, and organized manner; demonstrated
ethical scholarship in accurate representation and attribution of
sources; displayed accurate spelling, grammar, and punctuation.
8
Total:
100

Title of the Assignment
Subtitle (title of the article)
First paragraph (your introduction):
author, article and journal title, publication year
What is the aim/hypothesis of the paper? (Here you need to
write the thesis/objective that the author is examining. You can
use the author’s exact wording but remember to provide the
citation) 100 words approximately
Main body paragraphs:
Describe the purpose of the study. (in your own words)
What are the gaps or weaknesses in the research? (describe)
What are the major findings of the study? (write the author’s
conclusion and theoretical framework)
How did the author test their hypothesis? (summarize the main
steps the author used in their methodology, does the author
suggests any problems or limitations? What test did he/she
used?)
How reliable are the results? (does the author mentions any
problems that can lead to unreliable results?)
Based on your analysis are the claims in the article accurate?

(do the author’s results make sense to you? Are the conclusions
too narrow or too broad?) 500 words approximately
Last paragraph (your conclusion):
What is the importance of the scientific work? (in your own
words explain if you believe that the particular article is strong
or weak scientifically) 100 words approximately
References

Internet and Higher Education 19 (2013) 10–17
Contents lists available at ScienceDirect
Internet and Higher Education
Unpacking online learning experiences: Online learning self-
efficacy
and learning satisfaction
Demei Shen a,⁎, Moon-Heum Cho b, Chia-Lin Tsai c, Rose
Marra d
a Shanghai Engineering Research Center of Digital Education
Equipment, East China Normal University, China
b Lifespan Development and Educational Sciences, Kent State
University at Stark, United States
c Department of Psychological Sciences, University of Missouri
– Columbia, United States
d School of Information Science and Learning Technologies,
University of Missouri – Columbia, United States
⁎ Corresponding author. Tel.: +86 1 206 524 3022.
E-mail addresses: [email protected], demeishe
1096-7516/$ – see front matter © 2013 Elsevier Inc. All
http://dx.doi.org/10.1016/j.iheduc.2013.04.001
a b s t r a c t
a r t i c l e i n f o
Article history:
Accepted 8 April 2013
Available online 15 April 2013
Keywords:
Online learning

Self-efficacy
Online learning self-efficacy
Learning satisfaction
Self-efficacy is believed to be a key component in successful
online learning; however, most existing studies of on-
line self-efficacy focus on the computer. Although computer
self-efficacy is important in online learning, researchers
have generally agreed that online learning entails self-efficacy
of multifaceted dimensions; therefore, one of the
purposes of the current study was to identify dimensions of
online learning self-efficacy. Through exploratory factor
analysis, we identified five dimensions of online learning self-
efficacy: (a) self-efficacy to complete an online course,
(b) self-efficacy to interact socially with classmates, (c) self-
efficacy to handle tools in a Course Management System
(CMS), (d) self-efficacy to interact with instructors in an online
course, and (e) self-efficacy to interact with class-
mates for academic purposes. In addition, the role of
demographic variables in online learning self-efficacy was in-
vestigated. Demographic variables, such as the number of online
courses taken, gender, and academic status were
found to predict online learning self-efficacy. Furthermore, we
found that online learning self-efficacy predicted stu-
dents' online learning satisfaction. Results are discussed, and
implications for online teaching and learning are
provided.
© 2013 Elsevier Inc. All rights reserved.
1. Introduction
Beliefs about self-efficacy determine level of motivation as
reflected in the amount of effort exerted in an endeavor and the
length of time persisting in a difficult situation (Bandura,
1988).
Self-efficacy is defined as “people's judgments of their
capabilities to

organize and execute a course of action required to attain
designated
types of performances” (Bandura, 1986, p. 391). If a person has
a low
level of self-efficacy toward a task, he or she is less likely to
exert ef-
fort; therefore, the person will less likely achieve. Other
research find-
ings have demonstrated that self-efficacy is a better predictor of
academic achievement than any other cognitive or affective
processes
(Schunk, 1991); therefore, self-efficacy is critical in learning
and per-
formance (Hodges, 2008).
Student self-efficacy seems particularly important in
challenging
learning environments, such as an online learning environment
where
students lack the opportunity to interact with others and as a
result
can become socially isolated and easily lost (Cho & Jonassen,
2009;
Cho, Shen, & Laffey, 2010). Recent studies have shown that the
drop-out rate among students in online learning environments is
higher
than in traditional learning environments (Ali & Leeds, 2009).
Some re-
searchers have asserted that the drop-out rate is related in part
to lack
[email protected] (D. Shen).
rights reserved.
of self-efficacy (Lee & Choi, 2011). Researchers have argued
that with
the self-directed nature of online learning, self-efficacy can be a

key
component of academic success in distance education (Hodges,
2008);
therefore, understanding self-efficacy in online learning is
critical to im-
prove online education. The current study was an investigation
of
self-efficacy in online learning settings.
2. Self-efficacy in online learning settings
Self-efficacy is context-specific (Bandura, 1986). In terms of
online
self-efficacy, we need to consider at least three areas:
technology, learn-
ing, and social interaction; however, a majority of researchers
of online
self-efficacy consider only the technological aspect of online
learning.
Consequently, self-efficacy in the other two areas has rarely
been
explored.
With regard to technology, numerous studies have been
conducted
on the role of technological self-efficacy in online student
achievement.
For instance, McGhee (2010) found a significant, moderate, and
positive
relationship between online technological self-efficacy and the
academ-
ic achievement of 45 community college students. Thompson
and Lynch
(2003) studied the psychological processes underlying
resistance to
web-based instruction (WBI) and demonstrated that students

with
weak Internet self-efficacy beliefs tended to resist WBI.
Regarding learning, Ergul (2004) showed that self-efficacy in
dis-
tance education significantly and positively predicted students'
academic
http://crossmark.crossref.org/dialog/?doi=10.1016/j.iheduc.2013
.04.001&domain=pdf
mailto:[email protected]
mailto:[email protected]
http://www.sciencedirect.com/science/journal/10967516
11D. Shen et al. / Internet and Higher Education 19 (2013) 10–
17
achievement. In addition, Artino (2008) found that students
with higher
self-efficacy for computer-based learning are more likely to
experience
learning satisfaction than students with low self-efficacy.
In terms of social interaction, Cho and Jonassen (2009) found
two di-
mensions of online self-efficacy: self-efficacy to interact with
instructors
and self-efficacy to contribute to the online community. In
addition, they
found that students who have high self-efficacy in interacting
with in-
structors and contributing to the online community are more
likely to
use active interaction strategies, such as writing, responding,

and
reflecting. According to Cho and Jonassen researchers of online
learning
self-efficacy should consider diverse situations that can occur in
online
learning contexts, such as interacting with others through
discussion or
collaboration. Hodges (2008) claimed that “research on self-
efficacy in
online environments is in its infancy” (p. 10); in fact, how self-
efficacy
manifests in online learning contexts deserves additional
research and
studies. Although diverse learning settings are assumed, little
empirical
research on self-efficacy has been conducted with a focus on all
three set-
tings in online learning environments.
3. Variables of self-efficacy in online learning settings
Three types of variables relating to student self-efficacy in
online
learning environments are prior online learning experience,
gender,
and academic status. Existing empirical research on
relationships
among the three variables and self-efficacy shows different
findings;
therefore, the current empirical study contributes to filling the
void.
3.1. Prior online experience and self-efficacy
Although little research has been conducted to investigate the
rela-

tionships between prior online learning experience and self-
efficacy, a
reasonable hypothesis is that the more students experience
online,
the more they are likely to have higher levels of online self-
efficacy. An-
other possible hypothesis is that prior online experience is not
related
to online self-efficacy. In their recent study, Cho and Kim
(2013)
found that the number of online courses students took is not
related
to their self-regulation for interaction with others. They viewed
other
factors, such as task structures for interaction and requirements
for in-
teraction, including quality and the number of online interaction
may
be associated with self-regulation for interaction with others.
Although
Cho and Kim's study is not directly related to online self-
efficacy, their
findings imply that prior online experience may not necessarily
predict
online self-efficacy. Because we have two reasonable but
contrasting
hypotheses and because little research has been done to
investigate
the relationship between online experience and self-efficacy,
our re-
search findings will contribute to the expansion of
understanding that
relationship.
3.2. Gender and self-efficacy

Gender difference in self-efficacy has been reported in many
empir-
ical studies. For example, Wesley (2002) studied 400
community col-
lege students and found no significant difference in the self-
efficacy of
male and female students, but students 25 years old and older
exhibited higher levels of self-efficacy than younger students.
Li
(2007), collecting data from 306 Taiwanese students at a
technical col-
lege, found that male students had higher level of general self-
efficacy
and computer self-efficacy than female students, and senior
students
had a higher level of both of the two types of self-efficacy than
under-
class students. Fletcher (2005) found that gender and previous
online
experience influence online learning self-efficacy, with female
students
having greater self-efficacy; however, more recently, Hung,
Chou, Chen,
and Own (2010) found no gender differences in computer or
Internet
self-efficacy or online communication self-efficacy. Because of
mixed
research results, more empirical study is necessary.
3.3. Academic status and self-efficacy
Billings, Skiba, and Connors (2005) compared differences
between
undergraduate and graduate nursing students who took web-
based
courses and found that undergraduates perceived higher levels
of fac-

ulty–student interactions than graduate students, and
undergraduate
reported higher levels of perceived connection with other
students
and instructor. Using the independent samples t test, Artino and
Stephens (2009) compared undergraduate and graduate students
en-
rolled in several online courses with regard to their academic
motiva-
tion and self-regulation strategies. They found that
undergraduates
had more online learning experience, took a greater number of
online
courses, showed significantly greater levels of task value
beliefs, and
were more likely to continue to take online courses in the future
than graduate students; graduate students showed significantly
higher levels of critical thinking. They found no statistical
differences
between the two groups in self-efficacy beliefs. More empirical
re-
search will contribute to identifying relationships between
academic
status and online self-efficacy.
3.4. Students' satisfaction with online learning
Self-efficacy has been reported as a consistent variable in
predicting
students' learning satisfaction in online learning environments.
Womble
(2008), who investigated the relationship between e-learning
self-
efficacy and e-leaner satisfaction among 440 government
agency em-
ployees in training courses, found significant and positive
correlation be-

tween them. Lim (2001) examined the relationships among
computer
self-efficacy, academic self-concept, satisfaction, and future
participation
of adult distance learners. Findings indicated that computer
self-efficacy
was a significant predictor of both the satisfaction of online
learners and
their intention to take future web-based courses. Lin, Lin, and
Laffey
(2008) investigated students’ task value, self-efficacy, social
ability and
learning satisfaction. Among participants from 11 online
courses in a dis-
tance learning program, the researchers found that self-efficacy,
task
value, and social ability significantly impacted online learning
satisfaction.
4. Research questions
The overarching research question in this study was designed to
investigate the role of self-efficacy in online learning
environments.
More specifically, the following three research questions were
exam-
ined in this study.
1. What are the dimensions of online learning self-efficacy?
2. What variables are related to students’ online learning self-
efficacy?
3. To what extent is self-efficacy related to students’ online
learning
satisfaction?
5. Method

5.1. Participants
The participants in this study were students who were enrolled
in
an online course at the time the study was conducted. Response
rate
was not calculated because students were not required to report
their
course information. A total of 406 online students participated
in the
study. Among them, 301 (74.1%) students were female, and 104
(25.6%) students were male. The majority (N = 351, 86.5%) of
the
participants were Caucasian. More than 50% of the participants
were
in pursuit of a graduate degree (N = 244, 60.1%), but
undergraduates
were also included in the pool of respondents (N = 151, 37.2%).
See
Table 1 for detailed demographic information.
Table 1
Description of participants.
Demographic variables N %
Gender
Male 104 25.6
Female 301 74.1
No response 1 .2
Ethnicity/citizenship
African/African American 13 3.2
Asian, Asian American, or Pacific Islander 17 4.2

Latino/Latino American 14 3.4
Caucasian/Caucasian American 351 86.5
Biracial 9 2.2
No response 2 .5
Degree pursuing
Undergraduate 151 37.2
Graduate 244 60.1
Other 11 2.7
Total 406
12 D. Shen et al. / Internet and Higher Education 19 (2013) 10–
17
5.2. Measures
Two instruments were used for this study: one for identifying
di-
mensions of online learning self-efficacy and the other for
measuring
online learning satisfaction.
5.3. Demographic variables
Participants were asked to self-report demographic information,
including gender, academic status, and number of online courses
taken. Gender was a two-category variable with male coded as 1
and female coded as 0. Academic status was reported as
graduate stu-
dent or undergraduate student. Participants were asked to
provide
the number of online courses they had taken up to the time of
the
survey.
5.4. Online learning self-efficacy

A new scale was developed to measure students' online learning
self-efficacy. Following a literature review, online learning
self-efficacy
was conceptualized into six types of self-efficacy: (a) self-
efficacy to
complete an online course, (b) self-efficacy to interact with
classmates,
(c) self-efficacy to interact with an instructor, (d) self-efficacy
to
self-regulate in online learning, (e) self-efficacy to handle a
course man-
agement system, and (f) self-efficacy to socialize with
classmates. An
initial item pool consisting of 120 items was generated to assess
six
types of online learning self-efficacy. Each item was evaluated
through
an expert review conducted by five doctoral students and two
faculty
members with extensive experience in online teaching and scale
devel-
opment. Each of the experts received six review forms and rated
each
item in terms of relevance to one type of online learning self-
efficacy,
for example, self-efficacy to complete an online course, based
on a
scale of 1 through 3, where 1 was “not relevant at all,” 2
indicated “rel-
evant but needs minor alteration,” and 3 was “very relevant.”
They were
also asked to write comments about the items. The research
group
discussed and compiled the review results and then selected and
re-

vised 35 items as the final scale. An 11-point Likert scale was
used. Par-
ticipants were asked to report how confident they were when
engaging
in various actions in an online course. They responded on a
scale of 0 to
10, where 0 indicated “cannot do at all,” 5 indicated
“moderately confi-
dent can do,” and 10 indicated “highly confident can do.” High
scores in-
dicated higher levels of online learning self-efficacies.
5.5. Learning satisfaction
Learning satisfaction was measured with five items on a scale
of 1
to 5, where 1 denoted “strongly disagree” and 5 denoted
“strongly
agree.” They were adapted from Lin’s (2005) research.
Cronbach's
alpha for learning satisfaction in this study was .88.
5.6. Procedure
The data were collected from two universities in the Midwestern
US.
The authors of the current study contacted online instructors
and asked
for permission to conduct the study in their online courses. With
their
approval the researchers posted the recruiting letter and link to
the on-
line survey on a message board. The instructors also encouraged
stu-
dents to participate in the study. After students filled out the
online

consent form, they were directed to fill out the online survey on
the
website. This study was approved by the IRB and conducted
ethically.
6. Results
6.1. Question 1: what are the dimensions of online learning self-
efficacy?
An exploratory factor analysis was conducted to identify dimen-
sions of online learning self-efficacy. The principle axis
factoring
(PAF) extraction method with oblique rotation was applied (in
this
case Promax). We chose an oblique rotation method because
each
self-efficacy dimension was assumed to be correlated with one
anoth-
er. Four criteria were used to arrive at the solution. First, item
load-
ings should be above .40. Second, any discrepancies between
cross-loadings with an absolute value less than .15 were
deleted;
third, no item was cross-loaded highly to more than one factor,
for
example, greater than .40. And fourth, each factor should have
at
least three items (Pett, Lackey, & Sullivan, 2003). Our results
sug-
gested five factors of online learning self-efficacy. The Kaiser–
Meyer–Olkin measure of sampling adequacy (KMO) value was
.947,
and the chi-square value of Bartlett's Test of Sphericity was x2
(595) = 15121.91, with p b .001. Both of the tests indicated a

high
level of appropriateness for a factor analysis to proceed.
The five factors explained 74.20% of the total variance, and
each fac-
tor explained 50.62%, 10.23%, 5.95 %, 4.22%, and 3.18% of the
variance,
respectively. In accordance with the items included in the
factors, we
named the five factors as follows: (a) self-efficacy to complete
an online
course, (b) self-efficacy to interact socially with classmates, (c)
self-
efficacy to handle tools in a Course Management System
(CMS),
(d) self-efficacy to interact with instructors in an online course,
and (e) self-efficacy to interact with classmates for academic
pur-
poses. Cronbach's alpha for each dimension of online learning
self-efficacy was .93, .92, .93, .94, and .93, respectively. See
Table 2
for more detailed information about factor loadings, items, and
Cronbach's alpha.
6.2. Question 2: what variables are related to students' online
self-efficacy?
In order to answer Research Question 2, descriptive statistics
and
multiple regressions were conducted using IBM SPSS Statistics
20.
6.2.1. Descriptive statistics of variables
Descriptive statistics, including mean and standard deviations,
were acquired and have been presented in Table 3. Information

about how many online courses students took prior to
participating
in the study was also collected. Students reported that on
average
they took 5.43 online courses (SD = 3.89). Students tended to
have
high levels of self-efficacy beliefs, and the mean value of all
the five
self-efficacy factors were above 7 out of 10. Their learning
satisfaction
score was high as well, with a mean value of 4.32. The
correlation of
factors indicated all the dimensions of online learning self-
efficacy
significantly (ranged from r = .295 to r = .749) correlated to one
an-
other, and they all significantly correlated to learning
satisfaction
(ranged from r = .320 to r = .562). To conduct the following
analy-
ses, gender was treated as a dichotomous variable, with 0
indicated
Table 2
Results of exploratory factor analysis.
Factor loadings
1 2 3 4 5
Factor 1: Self-efficacy to complete an online course
(Eigenvalue = 17.72; 50.62% of variance explained, alpha =
.93)

How confident are you that you could do the following tasks in
the Online Course?
Complete an online course with a good grade .849 −.034 .036
.065 −.126
Understand complex concepts .867 .101 −.123 .156 −.233
Willing to face challenges .684 .104 −.041 .197 −.047
Successfully complete all of the required online activities .874
−.034 −.038 .072 −.043
Keep up with course schedule .808 −.008 −.096 −.110 .211
Create a plan to complete the given assignments .516 .039 .185
−.013 .130
Willingly adapt my learning styles to meet course expectations
.629 .097 .025 −.007 .199
Evaluate assignments according to the criteria provided by the
instructor .551 .103 .235 .051 .026
Factor 2: Self-efficacy to interact socially with classmates
(Eigenvalue = 3.58, 10.23% of variance explained, alpha = .92)
How confident are you that you could do the following social
interaction tasks
with your CLASSMATES in the ONLINE course?
Initiate social interaction with classmates −.022 .812 .045 −.010
.067
Socially interact with other students with respect −.120 .567
.095 .164 .187
Develop friendship with my classmates .099 .860 −.045 −.094
−.058
Apply different social interaction skills depending on situations
−.017 .899 .057 −.020 .024
Pay attention to other students’ social actions .081 .945 .033
−.093 −.084
Factor 3: Self-efficacy to handle tools in a CMS (Eigenvalue =
2.08; 5.95% of

variance explained, alpha = .93)
How confident are you that you could use the following tasks
while using online
course TOOLS in the course management system?
Download instructional materials .061 −.075 .717 .032 .087
Post a new message in a discussion board −.128 −.043 .997 .011
.009
Reply to others' message in a discussion board −.110 −.063 .912
.048 .018
Submit assignments .094 .058 .767 .041 −.102
Open files within the course management system .068 .055 .822
.040 −.017
Send email to others with or without attached files .022 .089
.784 −.055 −.105
Factor 4: Self-efficacy to interact with instructors in an online
course
(Eigenvalue = 1.48; 4.22% of variance explained, alpha = .94)
How confident are you that you could do the following tasks
while interacting
with your INSTRUCTOR in the ONLINE Course?
Clearly ask my instructor questions .029 −.070 .033 .958 −.041
Timely inform the instructor when unexpected situations arise
−.028 −.026 .180 .658 .101
Initiate discussions with the instructor .014 .032 .002 .768 .123
Express my opinions to instructor respectfully .198 −.056 −.071
.721 .101
Seek help from instructor when needed .058 .036 −.008 .902
−.074
Factor 5: Self-efficacy to interact with classmates for academic
purposes

(Eigenvalue = 1.11; 3.18% of variance explained, alpha = .93)
How confident are you that you could do the following tasks
while interacting
with your CLASSMATES in the ONLINE course?
Actively participate in online discussions .131 −.073 .020 .060
.737
Effectively communicate with my classmates −.029 .218 −.033
.072 .722
Express my opinions to other students respectfully .028 .005
.022 .341 .521
Respond to other students in a timely manner .033 .097 −.036
.063 .751
Provide help to other students when assistance is needed .015
.307 −.085 .000 .684
Request help from others when needed −.146 .301 −.030 .170
.582
Note: the bold emphasis indicates the loading value of an item
and that the item has loaded on the identified factor.
Table 3
Descriptive statistics of variables.
Variables 1 2 3 4 5 6 7 8 9
Academic status –
Gender −.13 –
Number of Online Courses .339⁎⁎ −.090 –
Factor 1: Self-efficacy to complete an online course .116⁎
−.167⁎⁎ .205⁎⁎ –
Factor 2: Self-efficacy to interact socially with classmates .037
−.060 .074 .452⁎⁎ –
Factor 3: Self-efficacy to handle tools in a CMS .150⁎⁎ −.146⁎⁎
.118⁎ .596⁎⁎ .295⁎⁎ –

Factor 4: Self-efficacy to interact with instructors in an online
course .037 −.099⁎ .115⁎ .675⁎⁎ .550⁎⁎ .538⁎⁎ –
Factor 5: Self-efficacy to interact with classmates for academic
.066 −.145⁎⁎ .144⁎⁎ .705⁎⁎ .671⁎⁎ .529⁎⁎ .749⁎⁎ –
Learning Satisfaction −.079 −.146⁎⁎ .038 .562⁎⁎ .377⁎⁎ .320⁎⁎
.506⁎⁎ .428⁎⁎ –
M 5.43 9.08 7.53 9.68 9.17 8.85 4.32
SD 3.89 1.21 2.36 0.80 1.35 1.51 0.80
⁎ p b .05.
⁎⁎ p b .01.
17
17
“female,” and 1 represented “male.” Similarly, we used 0 to
represent
“undergraduate”, and 1 to indicate “graduate”. Gender and
number of
online courses both weakly correlated with four self-efficacy
factors
except self-efficacy to interact socially with classmates. Table 3
shows the result of descriptive statistics.
6.2.2. Multiple regressions
To investigate how demographic variables are associated with
stu-
dents' online learning self-efficacy, five separate multiple
regressions
were performed. The demographic variables included the
number of

online courses students took prior to participating in the study
as
well as gender and academic status.
6.2.3. Self-efficacy to complete an online course
The number of online courses, gender, and academic status
together
accounted for approximately 6.5% of the variance in self-
efficacy to com-
plete an online course (Radj
2 = .065), F(3, 391) = 10.07, p b .001. The
number of online courses was a significant predictor of self-
efficacy to
complete an online course, t (391) = 3.48, p b .01, which
accounted
for 3% of the variance in self-efficacy to complete an online
course not
accounted for by other self-efficacy factors (pr = .173) and
uniquely
accounted for 3% of the variance in self-efficacy to complete an
online
course (sr = .170). Holding other variables constant, we found
that as
one more online course was taken by students, their self-
efficacy to com-
plete an online course was estimated to increase by about .06
point (95%
CI: .03, .09, Beta = .18).
Gender was also a significant predictor of self-efficacy to
complete
an online course, t(391) = −3.13, p b .01, which accounted for
2% of
the variance in self-efficacy to complete an online course not

accounted
for by other self-efficacy factors (pr = −.156) and uniquely
accounted
for 2% of the variance in self-efficacy to complete an online
course
(sr = −.152). Holding other variables constant, we found that
males
had .43 point less than their female counterparts (95% CI: −.69,
−.16;
Beta = −.15).
Academic status was not a significant predictor of self-efficacy
to
complete an online course, t (391) = 1.07, p > .05.
6.2.4. Self-efficacy to interact socially with classmates
The number of online courses, gender, and academic status did
not
significantly predict self-efficacy to interact socially with
classmates, F
(3, 391) = 1.01, p > .05.
6.2.5. Self-efficacy to handle tools
together
significantly predicted self-efficacy to handle tools in a CMS,
and
accounted for approximately 4.2% of the variance (Radj
2 = .042), F(3,
391) = 6.75, p b .001.
The number of online courses was not a significant predictor of
self-efficacy to handle tools in a CMS, t(391) = 1.25, p > .05.

Gender was a significant predictor of self-efficacy to handle
tools
in a CMS, t(391) = −2.85, p b .01, which accounted for 2% of
the
variance in self-efficacy to handle tools in a CMS not accounted
for
by other self-efficacy factors (pr = −.143) and uniquely
accounted
for 2% of the variance in self-efficacy to handle tools in a CMS
(sr = − .141). Holding other variables constant, we found that
males had .26 point less than their female counterparts (95% CI:
−
.44, − .08; Beta = − .14).
Academic status was a significant predictor of self-efficacy to
handle
tools in a CMS, t(391) = 2.48, p b .05, which accounted for 2%
of the
variance in self-efficacy to handle tools in a CMS not accounted
for by
other self-efficacy factors (pr = .125) and uniquely accounted
for 1%
of the variance in self-efficacy to handle tools in a CMS (sr =
.122).
Holding other variables constant, we found that graduate
students
had .22 point more than undergraduate students in self-efficacy
to han-
dle tools (95% CI: .05, 39; Beta = .13).
6.2.6. Self-efficacy to interact with instructors in an online
course
The number of online courses, gender, and academic status to-
gether significantly predicted self-efficacy to interact with
instructors

in an online course and accounted for approximately 1.6% of
the var-
iance (Radj
2 = .016), F(3, 391) = 3.16, p b .05. Number of online
courses was not a significant predictor of self-efficacy to
interact
with instructors, t (391) = 1.94, p > .05.
Gender was a significant predictor of self-efficacy to interact
with
instructors in an online course in a CMS, t(391) = −2.07, p b
.05,
which accounted for 1% of the variance in self-efficacy to
interact
with instructors in an online course not accounted for by other
self-efficacy factors (pr = −.104) and uniquely accounted for
1% of
the variance in self-efficacy to interact with instructors in an
online
course(sr = −.104). Holding other variables constant, we found
that males had .32 point less than their female counterparts
(95%
CI: −.62, −.02; Beta = −.10) in their self-efficacy to interact
with
instructors in an online course.
to
interact with instructors in an online course, t(391) = .005, p >
.05.
6.2.7. Self-efficacy to interact with classmates for academic
purposes
together

accounted for approximately 3.8% of the variance in self-
efficacy to in-
teract with classmates for academic purposes (Radj
2 = .038), F(3,
391) = 5.21, p b .01.
The number of online courses was a significant predictor of
self-
efficacy to interact with instructors, t(391) = 2.23, p b .05,
which
accounted for 1% of the variance in self-efficacy to interact
with class-
mates for academic purposes not accounted for by gender (pr =
.112)
and uniquely accounted for 1% of the variance in self-efficacy
to interact
with classmates for academic purposes (sr = .111). Holding
other vari-
ables constant, we found that as one more online course was
taken by stu-
dents, their self-efficacy to interact with classmates for
academic
purposes was estimated to increase by about .05 point (95% CI:
.01, .09,
Beta = .12).
Gender was also a significant predictor of self-efficacy to
interact
with classmates for academic purposes in a CMS, t(391) =
−2.81,
p b .01, which accounted for 2% of the variance in self-efficacy
to inter-
act with classmates for academic purpose not accounted for by
gender

(pr = −.141) and uniquely accounted for 2% of the variance in
self-efficacy to interact with classmates for academic purposes
(sr = −.140). Holding the number of online courses constant,
males
had an average of.48 point less than their female counterparts
(95%
CI: −.81, −.14; Beta = −.14) in their self-efficacy to interact
with
classmates for academic purposes.
to
interact with instructors in an online course, t (391) = .30, p >
.05.
Please see Table 4 for more information about the regression
results.
6.3. Question 3: to what extent is self-efficacy related to
students' online
learning satisfaction?
Multiple regression analysis was performed using the five self-
efficacy factors as independent variables and learning
satisfaction as
dependent variable to detect whether the five self-efficacy
belief fac-
tors predict learning satisfaction (Table 5).
The five self-efficacy factors together accounted for
approximately
35% of the variance in learning satisfaction (Radj
2 = .352), F (2,
59) = 28.43, p b .001. Self-efficacy to complete an online
course was
a significant predictor of lea rning satisfaction, t (392) = 7.28,

p b .001, which accounted for 12% of the variance in learning
satisfac-
tion not accounted for by other self-efficacy factors (pr = .345)
and
uniquely accounted for 9% of the variance in learning
satisfaction
(sr = .294). Holding other self-efficacy factors constant, as self-
efficacy to complete an online course increased by 1 point,
learning
Table 4
Multiple regression analysis results for self-efficacy factors.
Variable B SE. β pr Sr 95% C.I. T Sig.
Lower Upper
Self-efficacy to complete an online course
(Constant) 8.78 .12
Number of Online Courses .06 .02 .18 .173 .170 .03 .09 3.48⁎⁎
.001
Gender −.43 .14 −.15 −.156 −.152 −.69 −.16 −3.13⁎⁎ .002
Academic status .14 .13 .06 .054 .052 −.12 .40 1.07 .285
Self-efficacy to interact socially with classmates
(Constant) 7.54 .24
Number of Online Courses .03 .03 .05 .051 .051 −.03 .09 1.00
.316
Gender −.34 .26 −.07 −.065 −.065 −.85 .18 −1.29 .197
Academic status .03 .25 −.01 −.006 −.006 −.52 .47 −.11 .910
Self-efficacy to handle tools in a CMS
(Constant) 9.54 .08
Number of Online Courses .01 .01 .07 .063 .061 −.01 .04 1.25

.214
Gender −.26 .09 −.14 −.143 −.141 −.44 −.08 −2.85⁎⁎ .005
Academic status .22 .09 .13 .125 .122 .05 .39 2.48⁎ .013
Self-efficacy to interact with instructors in an online course
(Constant) 9.06 .14
Number of Online Courses .04 .02 .10 .098 .097 .00 .07 1.94
.053
Gender −.32 .15 −.10 −.104 −.104 −.62 −.02 −2.07⁎ .039
Academic status .00 .15 .00 .00 .00 −.29 .29 .01 .996
Self−efficacy to interact with classmates for academic purpose
(Constant) 8.72 .15
Number of Online Courses .50 .02 .12 .112 .111 .01 .09 2.23⁎⁎
.026
Gender −.48 .17 −.14 −.141 −.140 −.81 −.14 -2.81⁎⁎ .008
Academic status .05 .16 .02 015 015 .27 .37 .30 .764
⁎ p b .05.
⁎⁎ p b .01.
17
satisfaction was estimated to increase by about .31 point (95%
CI: .22, .40, Beta = .46).
Self-efficacy to interact socially with classmates was a
significant
predictor of learning satisfaction, t (392) = 2.68, p b .01, which
accounted for 2% of the variance in learning satisfaction not
accounted
for by other self-efficacy factors (pr = .134) and uniquely
accounted
for 1% of the variance in learning satisfaction (sr = .108).
Holding
other self-efficacy factors constant, as self-efficacy to interact

socially
with classmates increased by 1 point, learning satisfaction was
estimat-
ed to increase by about .05 point (95% CI: .01, .09, Beta = .15).
Self-efficacy to interact with instructors in an online course was
a
significant predictor of learning satisfaction, t (392) = 3.96, p b
.001,
which accounted for 4% of the variance in learning satisfaction
not
accounted for by other self-efficacy factors (pr = .196) and
uniquely
accounted for 3% of the variance in learning satisfaction (sr =
.160).
Holding other self-efficacy factors constant, as self-efficacy to
interact
with instructors in an online course increased by 1 point,
learning satis-
faction was estimated to increase by about .16 point (95% CI:
.08, .23,
Beta = .26).
Table 5
Multiple Regression Analysis Results for Learning Satisfaction.
Variable B SE.
(Constant) 1.04 .39
Self-efficacy to complete an online course .31⁎⁎⁎ .04
Self-efficacy to interact socially with classmates .05⁎⁎ .02
Self-efficacy to handle tools in a CMS −.06 .05
Self-efficacy to interact with instructors in an online course
.16⁎⁎⁎ .04
Self-efficacy to interact with classmates for academic purpose
−.09⁎ .04

Note. R Square = .360. Adjusted R Square = .352.
⁎ p b .05.
⁎⁎ p b .01.
⁎⁎⁎ p b .001.
Self-efficacy to interact with classmates for academic purpose
was a
significant predictor of learning satisfaction, t (392) = −2.16, p
b .05,
which accounted for 1% of the variance in learning satisfaction
not
accounted for by other self-efficacy factors (pr = −.109) and
uniquely
accounted for 1% of the variance in learning satisfaction (sr = -
.087).
Holding other self-efficacy factors constant, as self-efficacy to
inter-
act with classmates for academic purpose increased by 1 point,
learning satisfaction was estimated to decrease by about .09
point
(95% CI: −.17, − .01, Beta = − .16).
Self-efficacy to handle tools in a CMS was not a significant
predic-
tor of learning satisfaction, t (392) = −1.08, p > .05.
7. Discussion
7.1. Multiple dimensions of online self-efficacy
One of the purposes of this study was to investigate dimensions
of
self-efficacy in online learning. Through the exploratory factor
analy-
sis, we found five dimensions of online learning self-efficacy.
This

β pr sr 95% C.I. T Sig.
Lower Upper
.46 .345 .294 .22 .39 7.28⁎⁎⁎ .000
.15 .134 .108 .01 .09 2.68⁎⁎ .008
−.06 −.054 −.044 −.16 .05 −1.08 .281
.26 .196 .160 .08 .23 3.96⁎⁎⁎ .000
−.16 −.109 −.087 −.17 −.01 −2.16⁎ .031
17
result indicates that online learning self-efficacy is
multidimensional
and reflects the complex, multifaceted situation of online
learning. Dif-
ferent from much online self-efficacy research that focused
solely on
one aspect of learning setting such as technology, the current
online
self-efficacy study involved three aspects of online contexts,
including
technology, learning, and social interaction. The five
dimensions of the
self-efficacy scale may contribute to understanding multifaceted
self-
efficacy in online learning environments.
Interestingly enough, different from our assumption that “self-
efficacy in self-regulation” is a separate online self-efficacy,
“self-
efficacy in self-regulation” did not emerge as a separate factor,

at least
not with our data set. The three items, which were created to
assess
self-efficacy for self-regulated learning, loaded to self-efficacy
to com-
plete an online course. These three items included the
following: Create
a plan to complete the given assignments, willingly adapt my
learning
styles to meet course expectations, and evaluate assignments
according
to the criteria provided by the instructor. One possible
explanation is
that students might have interpreted self-regulation skills, such
as plan-
ning, monitoring, and evaluation, as tactics leading to complete
an on-
line course. Future researchers should restate each item to
measure
self-regulation aspect of self-efficacy.
7.2. Variables related to self-efficacy in online settings
Three variables including gender, online experience, and
academic
status were related to online learning self-efficacy to some
extent.
First, gender was a significant predictor of all the self-efficacy
beliefs ex-
cept self-efficacy to interact socially with classmates. In
general, the re-
sults demonstrate that female students were likely to have
higher
online learning self-efficacy than male students, implying that
female
students may be more active, seek more help, or function better

than
male students. Our results are consistent with Gebara's study
(2010),
demonstrating that female students reported higher level of
online
self-efficacy than male students.
Second, online experience measured with the number of online
courses was a significant predictor for two self-efficacy beliefs:
self-
efficacy to complete an online course and self-efficacy to
interact with
classmates for academic purposes. This finding indicates that
the stu-
dents who took more online courses were more likely to have
higher
online learning self-efficacy to complete an online course; in
addition,
they were more likely to communicate and collaborate with
other stu-
dents on academic tasks. However, online experience was not
signifi-
cantly related to self-efficacy to interact socially with
classmates,
self-efficacy to handle tools in a CMS, and self-efficacy to
interact with
instructors in an online course.
Last, academic status was not related with most of the
dimensions of
online learning self-efficacy, which was consistent with other
studies;
for example, Artino and Stephens (2009) found no significant
difference
in self-efficacy between undergraduates and graduates. In the
current

study, academic status predicted self-efficacy to handle tools in
a CMS
only; in other words, graduate students tended to have higher
levels
of technological self-efficacy than undergraduate students
perhaps be-
cause graduate students had more experience with online
learning
technology and perhaps because more graduate level courses
were de-
livered online than undergraduate courses. This was verified by
the
number of online courses taken by undergraduate and graduate
stu-
dents. An independent sample t-test on number of online
courses by ac-
ademic status revealed that graduate students had taken
significantly
more online courses (M = 6.48, SD = 3.80) than undergraduates
(M = 3.76, SD = 3.42), t (394) = 2.72, p b .001.
Overall, gender, the number of online courses, and academic
status
together did not explain much of the variance in the dimensions
of on-
line learning self-efficacy (R squared less than 7%), showing
that other
reasons may play vital roles in development of self-efficacy
beliefs in
online contexts. Perhaps, what really influences to students'
online
self-efficacy is quality of learning experience instead of
demographic
information, including gender and academic status or the
number of
online courses students took. Recently, Cho and Kim (2013)

found
that instructors' scaffolding efforts to facilitate social
interaction
among students or between students and teacher are most
significantly
related to students' self-regulation for interaction with others
than any
other variables, such as demographic variables and the number
of on-
line courses in online learning settings. This shows that if
students per-
ceived that they received quality support from online
instructors, the
students might engage in more social interaction with others,
perhaps
leading them to develop high self-efficacy for social
interactions regard-
less the number of course she or he takes.
7.3. Self-efficacy and learning satisfaction
The five dimensions of online learning self-efficacy except self-
efficacy to handle tools in a CMS significantly predicted
students' online
learning satisfaction. Among the four significant dimensions of
self-
efficacy, self-efficacy to complete an online course was most
significantly
associated with learning satisfaction; and it explained
approximately
12% of variance in satisfaction. However, the power of
remaining
self-efficacies that explain variance in satisfaction is marginal.
Self-
efficacy to interact socially with classmates, self-efficacy to
interact

with instructors in an online course, and self-efficacy to interact
with
classmates for academic purpose explain variance in satisfaction
only
2%, 4%, and 1%, respectively. The results show that students'
self-
assessment about their capabilities to complete an online course
is
more important in explaining satisfaction with online learning
than
any other self-efficacies.
7.4. Implications for online teaching
The five dimensions of online self-efficacies were identified:
self-efficacy to complete an online course, self-efficacy to
interact so-
cially with classmates, self-efficacy to handle tools in a CMS,
self-
efficacy to interact with instructors in an online course, and
self-
efficacy to interact with classmates for academic purposes.
Several
implications for online teaching follow.
7.4.1. Scaffold students to participate in learning activities
Self-efficacy to complete an online course explains most of the
vari-
ance both in online self-efficacy and in learning satisfaction.
Online in-
structors can support students' course completion by providing
co-
regulation opportunities, for example, online instructors' regular
moni-
toring on students' course participation and providing support

and
encouragement to complete an online course (Shea, Li, &
Pickett,
2006). Through regular monitoring of students' activities, online
in-
structors can find students' slow participation or failure to
submit as-
signments, especially for less experienced online students.
Then,
online instructors can provide immediate support and guidance
for stu-
dents to participate in the activities or complete the tasks.
7.4.2. Promote social interaction with others
The current study shows that three dimensions of online self-
efficacy
are related to social interactions among students and between
students
and instructors. The nature of online learning requires students
to inter-
act actively with both instructors and classmates. Especially
those stu-
dents with less experience may experience anxiety about
interacting
with others and may feel social isolation if they perceive lack of
support
from others. Online literature suggests that instructors should
create so-
cial presence and teaching presence to foster a sense of learning
commu-
nity (Yang, Tsai, Kim, Cho, & Laffey, 2006). Possible examples
to promote
social interactions with others include instructors' direct
interactions ef-
forts, such as participating in discussion boards (Artino &

Stephens,
2009), providing guidelines for social interaction, recognizing
students'
contribution to online learning community (Shea et al., 2006),
and mon-
itoring students' social interaction processes (Cho & Kim,
2013).
17
7.4.3. Provide an orientation to enhance students' self-efficacy
to handle
tools in a CMS
Although we found that self-efficacy to handle tools in a CMS
was
not a significant predictor for learning satisfaction, we found
that
self-efficacy to handle tools in a CMS is still a dimension of
online
self-efficacy. In addition, a significant number of studies
consistently
reported that technology-related self-efficacy promotes student
mo-
tivation and learning. In particular, self-efficacy to handle tools
in a
CMS is important for new online learners or at the beginning of
the
class (Cho, 2012). An orientation program will help students
develop
self-efficacy to handle tools in a CMS. Possible examples of
orientation
include scavenger activities that engage students with tools in a
CMS

and a video tutorial that demonstrates the use of tools in a CMS.
7.4.4. Consider gender differences in online self-efficacy
Our study findings demonstrate gender differences in all
dimensions
of online self-efficacy except for self-efficacy to interact
socially with
classmates. Female students have significantly higher self-
efficacy
than male students. Online instructors may need to provide
additional
support for male students to help them develop online self-
efficacy.
Possible instructional strategies include paying extra attention
to male
students' learning processes, providing immediate feedback and
assis-
tance, supporting them in the completion of tasks, and
encouraging
them to interact with others by sending an individual note or
recogniz-
ing their contributions to the development of an online learning
community.
8. Conclusion
Considering three aspects of dynamic online learning environ-
ments – technology, learning, and social interaction – we
explored
the dimensions of online learning self-efficacy and found that
online
self-efficacy involves five dimensions. Although more research
is nec-
essary to test its validity with larger samples from multiple
online

courses, our study provides a reliable instrument that can be
used
to measure diverse aspects of online self-efficacy. In addition,
the
study demonstrates that researchers studying online learning
self-efficacy should consider multiple aspects of self-efficacy in
online
contexts. Different from the existing self-efficacy researchers
who
have explored only one or two aspects of self-efficacy in online
set-
tings, we explored five aspects of self-efficacy that may
represent
more concrete online learning contexts. Furthermore, we found
gen-
der differences in online self-efficacy. This finding will
contribute to
existing online study involving gender difference in self-
efficacy.
Last, our study demonstrates that self-efficacy to complete an
online
course most significantly explains variances in satisfaction. It
shows
students' self-judgment about their capabilities to complete an
online
course is critical for their satisfaction with an online course.
Further-
more, instructors' proactive approaches for social interaction,
such as
monitoring and encouragement for social interactions, are
suggested
to help students develop the self-efficacy needed to complete an
on-
line course.
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http://tojde.anadolu.edu.tr/tojde14/articles/ergul.htmUnpacking
online learning experiences: Online learning self-efficacy and
learning satisfaction1. Introduction2. Self-efficacy in online
learning settings3. Variables of self-efficacy in online learning
settings3.1. Prior online experience and self-efficacy3.2.
Gender and self-efficacy3.3. Academic status and self-
efficacy3.4. Students' satisfaction with online learning4.
Research questions5. Method5.1. Participants5.2. Measures5.3.
Demographic variables5.4. Online learning self-efficacy5.5.
Learning satisfaction5.6. Procedure6. Results6.1. Question 1:
what are the dimensions of online learning self-efficacy?6.2.
Question 2: what variables are related to students' online self-
efficacy?6.2.1. Descriptive statistics of variables6.2.2. Multiple
regressions6.2.3. Self-efficacy to complete an online
course6.2.4. Self-efficacy to interact socially with
classmates6.2.5. Self-efficacy to handle tools6.2.6. Self-
efficacy to interact with instructors in an online course6.2.7.

Self-efficacy to interact with classmates for academic
purposes6.3. Question 3: to what extent is self-efficacy related
to students' online learning satisfaction?7. Discussion7.1.
Multiple dimensions of online self-efficacy7.2. Variables
related to self-efficacy in online settings7.3. Self-efficacy and
learning satisfaction7.4. Implications for online teaching7.4.1.
Scaffold students to participate in learning activities7.4.2.
Promote social interaction with others7.4.3. Provide an
orientation to enhance students' self-efficacy to handle tools in
a CMS7.4.4. Consider gender differences in online self-
efficacy8. ConclusionReferences

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