08832323.2015.1019818
Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Student Reactions to Classroom Management
Technology: Learning Styles and Attitudes Toward
Moodle
Christina Chung & David Ackerman
To cite this article: Christina Chung & David Ackerman (2015) Student Reactions to Classroom
Management Technology: Learning Styles and Attitudes Toward Moodle, Journal of Education
for Business, 90:4, 217-223, DOI: 10.1080/08832323.2015.1019818
To link to this article: http://dx.doi.org/10.1080/08832323.2015.1019818
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Date: 11 January 2016, At: 19:18
JOURNAL OF EDUCATION FOR BUSINESS, 90: 217–223, 2015
Copyright Ó Taylor & Francis Group, LLC
ISSN: 0883-2323 print / 1940-3356 online
DOI: 10.1080/08832323.2015.1019818
Student Reactions to Classroom Management
Technology: Learning Styles and Attitudes
Toward Moodle
Christina Chung
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Ramapo College of New Jersey, Mahwah, New Jersey, USA
David Ackerman
California State University, Northridge, Northridge, California, USA
The authors look at student perceptions regarding the adoption and usage of Moodle. Selfefficacy theory and the Technology Acceptance Model were applied to understand student
reactions to instructor implementation of classroom management software Moodle. They
also looked at how the learning styles of students impacted their reactions to Moodle. Results
show that students most valued the control Moodle gave them over their educational
progress. Communication was also found to be an important benefit students sought in
Moodle. Individual student reaction to Moodle was influenced by visual learning and degree
of laziness.
Keywords: classroom management software, learning styles, Moodle, self-efficacy,
technology acceptance model
In higher education, using a course management system
(CMS) has become an essential tool for many instructors.
As a result researchers have started to focus on the benefits
of CMS in teaching and learning. A few studies such as
Chung and Ackerman (2010) and Payette and Gupta (2009)
have examined managing a CMS in terms of instructors’
perceptions, but there is less investigation regarding student
reaction to CMS.
In contrast to instructors, students do not have as much
choice about the use of a CMS. If the course is a required
course, they can choose a course section. If it is an elective,
they can choose not to take the course, but for the most part
selection is more likely based on time and content than on
instructor use of CMS. For the most part students will experience the degree of CMS that their instructors implement.
Despite this lack of choice for students, CMS can influence
the entire structure and flow of their coursework. More
Correspondence should be addressed to David Ackerman, California
State University, Northridge, College of Business and Economics, Department of Marketing, 18111 Nordhoff Street, Northridge, CA 91330-8377,
USA. E-mail: david.s.ackerman@csun.edu
Color versions of one or more figures in this article can be found online
at www.tandfonline.com/vjeb.
importantly, their reaction to an instructor’s implementation of CMS can greatly impact their learning experience.
The major CMS are Blackboard (Blackboard Inc.,
Washington, DC) WebCT (Washington, DC), and Moodle,
though there are many other choices available. Despite
familiarity with Blackboard or WebCT, as of August 2014,
Moodle had a user-base of 53,958 registered and verified
sites, serving 68,958,596 users in 7.6C million courses
(Moodle, 2015). Moodle is an open-source learning management system. This means Moodle is available free of
charge to anybody under the terms of the General Public
License—there is no licensing fee.
Moodle provides several functions. Moodle can facilitate
student–instructor and student–student interactions. Message boards and customizable chat rooms allow both asynchronous and synchronous communication. Students
themselves can communicate within groups and use discussion boards themselves. Study guides provided by instructors and perhaps shared commonly among students are an
important benefit (Lewis et al., 2005). This common ground
for communication in cyberspace makes it an important
tool for online classrooms. Moodle also allows for more
rapid distribution of grades for exams and assignments. A
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218
C. CHUNG AND D. ACKERMAN
Moodle classroom home page is a very efficient tool that is
a much less time consuming and error prone process than
completion of the same tasks using paper or even email.
Business instructors have adopted use of the system for
both online courses and face-to-face classrooms. Some
have suggested that student motivation is a key factor in the
success of Moodle in the classroom and that students found
it easier to use (Beatty & Ulasewicz, 2006). Students do
like Moodle better than faculty (Payette & Gupta, 2009),
but this may be a function of greater faculty familiarity
with other classroom management software.
The purpose of this study was to investigate student perceptions in adopting and using Moodle and how their perceptions impact the effective use of the CMS. First, this
research looks at the influence of several constructs including academic self-efficacy, internet self-efficacy, usefulness,
difficulty, communication effectiveness, and enjoyment on
student perceptions of CMS. Second, the impact of learning
styles and implicit theory on the functional benefits students
derive from CMS is examined. The findings help explain
student perspectives on Moodle and provide the basis for
suggestions as to how faculty can effectively implement
Moodle for their teaching.
THEORETICAL FOUNDATION AND HYPOTHESES
Self-Efficacy and Technology Acceptance Model
From a student’s perspective, Moodle provides the means
whereby they receive class materials and submit assignments to instructors. Studies have suggested that students
do find online learning and components provided by most
classroom software packages to be effective in overall
learning (Clarke, Flaherty, & Mottner, 1999) and a CMS
can be used in a variety of online active/passive learning
experiences, including even a social dilemma game (Oertig,
2010). Overall, they are in fact very positive about most
aspects of a CMS (Carvalho, Nelson, & Silva, 2011). This
positive impact does not seem to vary by the learning style
of the student (Young, Klemz, & Murphy, 2003).
Despite these potential benefits, the use of a CMS is not
always met with optimism. Could a lack of clarity about
how to use CMS, the inability to complete tasks and perhaps
the stresses or other negative aspects of using it lead some
students to view it with disfavor? This could also influence
student evaluations of a course and their instructors.
The two theories, self-efficacy theory and Technology
Acceptance Model (TAM), were utilized for a theoretical
foundation in analyzing the relationships amongst these
variables. Within social cognitive theory, self-efficacy theory was developed by Bandura (1977). Self-efficacy refers
to beliefs about an individual’s capabilities to learn or perform behaviors at designated levels (Bandura, 1986, 1997).
This theory explains that an individual has a certain level of
confidence in his or her ability to perform tasks. Academic
self-efficacy and Internet self-efficacy were examined as
exogenous variables. Academic self-efficacy is expressing
confidence in academic ability, awareness of effort toward
study, and expectation for success in college attainment.
Much research shows that self-efficacy influences academic
motivation, learning, and achievement (Pajares, 1996;
Schunk, 1995). Internet self-efficacy focuses on how well
one believes s/he can accomplish needed tasks and goals on
the Internet (M. L. Lai, 2008). This type of self-efficacy is a
potentially important factor to examine student perceptions
on Moodle.
TAM was developed by Davis (1989) based on the theory
of reasoned action to explain computer usage behavior. There
are two constructs in the model, perceived usefulness (PU)
and perceived ease of use (PEOU), that measure the degree
of an individual’s system usage and perceptions in examining
behavioral intention and actual use. PU is the extent to which
applications contribute to improving user performance.
PEOU refers to the degree of required effort to take advantage of the application (Davis, 1989). Davis, Bagozzi, and
Warshwa (1989) found that perceived usefulness is a major
determinant of people’s intentions to use computers. Usefulness beliefs were more salient for inexperienced users than
experienced users (Taylor, 2004). Based on these theories
and previous research, a research model was created (Figure 1) and the following hypotheses developed to examine
the relationships between the latent constructs:
Hypothesis 1 (H1): Academic self-efficacy is positively
related to internet self-efficacy.
H2: Internet self-efficacy is negatively related to perceived
difficulty and positively related to perceived
usefulness.
H3: Perceived usefulness is negatively related to perceived
difficulty and positively related to communication
effectiveness and enjoyment in using Moodle.
H4: Perceived difficulty is negatively related to communication effectiveness and enjoyment in using Moodle.
H5: Communication effectiveness is positively related to
enjoyment in using Moodle.
Learning Styles and CMS
Can learning styles impact on student reaction to classroom
management systems? If so, what dimension of learning
style is most closely linked to adoption of CMS such as
Moodle? Students perceive that there is a relationship
between general technology use and their learning style
(C. Lai, Wang, & Lei, 2011). This certainly makes sense
from what instructors see in the course of a semester
regarding the way students communicate. Some students
like to communicate online by email and some by class discussion boards. Yet others prefer face-to-face communication. These differences are also seen in the way work is
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STUDENT REACTIONS TO CLASSROOM MANAGEMENT TECHNOLOGY
219
FIGURE 1 Research model: Student perceptions of Moodle.
turned into the instructor. If requirements about the way
work are turned in is not specified, some students will prefer to email in assignments from a home computer, some
like to post it on a classroom management site, yet others
will send it in by a variety of methods from their tablet PC
or cell phone as soon as they are finished. Can specific
learning styles have an impact on the use of classroom management technology?
Just as in face-to-face learning, students differ in how
they prefer information to be presented online as well. For
example, Saeed, Yang, and Sinnappan (2009) found that
sensors, who are careful and more detail oriented, preferred
email over other types of communication in learning where
as others like intuitors and visual learners preferred blogs
and videos respectively. Similarly, learning style can
impact on how students utilize learning technology as well
(Vigentini, 2009). Use of online material instructors supply
to students is an increasingly frequently-used component of
courses so it is important to determine the impact of learning styles on student perceptions of the different components of a classroom management system.
In sum, not all students will react in the same way to
instructor implementation of CMS. Some adapt quickly,
some more slowly, and yet others really have specific needs
that are fulfilled by the type of features their instructors provide for them in CMS. Students who have different learning
styles will take a different approach and perhaps require
some flexibility on the part of the instructor. Thus, in this
study, three specific questions regarding learning styles
were developed.
Research Question 1 (RQ1): Do learning styles have an
impact on student perceptions of classroom management technology?
RQ2: Which of the dimensions of learning styles have the
greatest impact on student perceptions of classroom
management technology?
RQ3: Which aspects of classroom management technology
are most impacted by student learning styles?
METHOD
We administered a web survey designed to measure marketing student perceptions toward CMS. Data were
collected using a convenience sampling method using a
self-administered questionnaire among marketing major
students. One hundred twenty-five respondents from six
marketing classes at two universities, in the northeast and
in the southwest, participated in the survey. The samples
consisted of 58% women and 42% men. All respondents
were between 18 and 28 years old. Eight-three percent of
students were juniors and seniors. Respondents revealed
that, besides Moodle, they had used Blackboard (30%),
WebCT (29%), and other (16%) CMS. In addition, students
indicate they have good Moodle literacy (average 5.7 of 7).
For all questions, the response options consisted of a 7point Likert-type scale ranging from 1 (strongly disagree)
to 7 (strongly agree).
Questionnaire items measuring Moodle usefulness
(Cronbach’s a D .94), Moodle difficulty (Cronbach’s a D
.86), and Internet self-efficacy (Cronbach’s a D .93) scales
were adapted from Chen and Tseng’s (2012) study. Academic self-efficacy scale (Cronbach’s a D .85) was modified
from the College Learning Effectiveness Inventory scale.
Moodle communication effectiveness (Cronbach’s a D .90)
and enjoyment scales (Cronbach’s a D .93) were adapted
from Martınez-Torres et al.’s (2008) research. In addition,
220
C. CHUNG AND D. ACKERMAN
there was a scale for implicit theory (Cronbach’s a D .83)
modified from Beruchashvili, Moiso, and Heisley (2014).
Learning style scales was adapted from Fleming (n.d.).
A factor analysis performed on the inventory of learning
styles found four factors. These were related to being
“social” (with factor loadings of .66–.81), “doesn’t like
listening” (with factor loadings of .62–.83) “visual,” (with
factor loadings of .72–.76), and “lazy” (with factor loadings
of .57–.74).
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RESULTS
An exploratory factor analysis (EFA) was run to assess the
measurement properties of the scales. Some items with factor loadings lower than .5 were deleted and a six-factor
solution of 23 items was identified. The EFA solution
accounted for 80% of the cumulative variance. Cronbach’s
alpha was used to measure internal consistency. All measures demonstrate good reliability with alpha values of .85
and greater (see Appendix).
Subsequent testing using confirmatory factor analysis
(CFA) was examined for the overall validity of the measurement model. The CFA results indicate an acceptable fit
with x2 D 358.69, df D 215, p D .000, comparative fit index
(CFI) D .94, root mean square error of approximation
(RMSEA) D .07, Tucker-Lewis index (TLI) D .92. The
CFI and TLI exceed the recommended cut-off value of .9
and the RMSEA is lower than the cutoff value of .08. Further, construct validity is evaluated based on the factor
loading estimates, construct reliabilities, variance extracted
percentages and inter-construct correlations. All loading
estimates are significant (p < .000) with the lowest being
.69 and the highest being .94. The variance-extracted estimates are .60, .82, .73, .62, 77, and .83 for academic selfefficacy, Internet self-efficacy, perceived usefulness, perceived difficulty, communication effectiveness, and enjoyment, respectively. In addition, the construct reliability
estimates are all adequate, ranging from .85 to .98.
Discriminant validity is measured by comparing the variance-extracted percentage for any two constructs with the
square of the correlation estimate between these two constructs. The results indicate that the convergent validity of
the model is supported and good reliability is also
established.
The next step was to examine the overall theoretical
model specification and the hypotheses by using the structural equation modeling (SEM). The SEM results indicate a
satisfactory fit of data with x2 D 361.15, df D 221, p D
.000, CFI D .94, RMSEA D .07, TLI D .93. The SEM
structural path results reveal that all hypotheses are supported except H4 (Figure 2).
To examine RQ1 through RQ3, a regression analysis of
the factors impacting on overall satisfaction with Moodle
were also significant, F(7, 125) D 31.31, p D .00, R2 D .63.
Significant dependent variables included visual (Std. b D
.12), t D 2.01, df D 124, p < .05; being social (Std. b D
–.14), t D –2.34, df D 124, p < .05; difficulty (Std. b D
.15), t D 2.38, df D 124, p < .05; usefulness (Std. b D .25),
t D 3.08, df D 124, p < .00; and control (Std. b D .48), t D
6.32, df D 124, p < .00.
In addition, a regression analysis was used to analyze
student perception of the functional benefits of Moodle
because classroom management software is by its nature
and use functional. The results of a linear regression were
significant, F(6, 125) D16.98, p D .00, R2 D .44. Significant
dependent variables included verbal (Std. b D .14), t D
1.97, p D .05; lazy (Std. b D –.14), t D –2.01, p < .05; difficulty (Std. b D .26), t D 3.82, p < .00; and communication
(Std. b D .47), t D 6.55, p < .00. Lastly, a correlation with
the implicit theory measure found that entity theory personality in students was inversely related to satisfaction with
Moodle (r2 D –.19, p D .04).
DISCUSSION AND IMPLICATIONS FOR
INSTRUCTORS
These results suggest first that the single most important
factor in overall satisfaction with classroom management
system is the control it gives students over their educational
progress. Depending on how it is implemented by the
instructor, CMS offers students flexibility in the timing and
amount of work they upload at any particular time. They
can also see their progress online. Such flexibility can
empower students who otherwise may feel they are at the
mercy of the instructor’s or department’s schedule. The
implication for instructors is that they should set up CMS
so that students are best able to monitor their own progress.
The schedule, including assignments and readings, should
be embedded as much as possible in the CMS so students
know beforehand the pace of the work and how much they
need to complete to move on in the course.
The result of a positive relationship between difficulty
and satisfaction or functional benefits of classroom management software was surprising. Perhaps, to an extent students felt that the more difficult software management was,
the more effective it was. Difficulty up to a certain degree
can be a challenge that is perceived as facilitating a goal. In
this case, a certain degree of complexity may also have
given students a sense of accomplishment that they were
learning a software system. The implication of this for
instructors is that it is ok to push students a little, to challenge them with a CMS. Maybe instructors could set up a
more elaborate and enriching curriculum on Moodle, with
videos and exercises, to motivate. Learning an instructor’s
system, with helpful features and functions, can be rewarding in and of itself.
Visual learning is also an important factor in overall student satisfaction with classroom management software.
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STUDENT REACTIONS TO CLASSROOM MANAGEMENT TECHNOLOGY
221
FIGURE 2 Tests of the hypotheses.
Given the graphics and visuals in CMS such as Moodle,
visual learners would be more satisfied with the system. As
this trend continues with software moving over to Appletype graphics systems, visual learners will be at an even
greater advantage in coming years. The implication of this
finding is that instructors need to expect to spend a little
more time with students who are not visual learners when
setting up a CMS. Perhaps setting up written protocols for
functions in the CMS the instructor has implemented may
help. Visual models for students who are not oriented
toward visual learning to copy may aid in walking these
students through the steps they need to complete.
On the one hand, it seems obvious that usefulness would
be a factor in satisfaction with classroom management software. On the other hand, enjoyment or other positive factors had no impact. This suggests that classroom
management software such as Moodle are viewed strictly
as tools for school work, not for fun or personal enrichment.
It also means that instructors are not likely to find students
available on the CMS on the weekends and breaks if they
need to communicate with them and may need to use other
means.
The findings for incremental versus entity theories of
intelligence are in line with what would be expected given
extant literature (Burnette, O’Boyle, VanEpps, Pollack, &
Finkel, 2013; Shih, 2011). Those who had a more rigid
entity view about their ability to deal with technology, it is
fixed and cannot change, were less likely to be satisfied
with Moodle. Those who had a more flexible view of ability
to work with technology were more likely to be satisfied
with Moodle.
Laziness impacted negatively on the functional benefits
of Moodle but not overall satisfaction. This finding suggests
that harder working students are more concerned
specifically with the functional benefits that can be derived
from a classroom management system. They are not necessarily happier overall than lazier students with CMS such
as Moodle. Instructors who wish to reward harder working
students may emphasize the functional benefits of their
implementation of the CMS. They could explain, for example, how downloading of a study guide or a group feedback
discussion board can impact on a specific part of the course
or the grade.
CONCLUSIONS
These results suggest that communication benefits, both
communication and verbal learning style are significant,
are an important perceived benefit of classroom management systems to students. Moodle does help facilitate communication both between student and instructor as well as
between students themselves. Students may be reluctant to
connect with classmates who are not friends on social
media sites to do class work or group work. On the other
hand, given our previous finding, classroom management
software is strictly workspace. To the degree to which
classroom management software can facilitate communication regarding class work and events between students and
instructors, it will be perceived as beneficial. Instructors
can aid in this process by perhaps setting up times where
out-of-class discussion can take place. Other instructors
encourage and give points for student comments in chat
rooms, which is an extrinsic reward that could encourage
use of the CMS as a means of communication.
SEM results indicate that students who are confident in
their overall academic abilities will tend to be more confident in other areas such as Internet or technology usage.
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C. CHUNG AND D. ACKERMAN
Overall academic self-efficacy led to Internet self-efficacy
and the Internet self-efficacy is significantly related to perceived usefulness and perceived difficulty. As shown in
Figure 2, even though there is significant relationship
between perceived usefulness and perceived difficulty, the
only important factor that is positively related to communication effectiveness and enjoyment in using Moodle is perceived usefulness. These results suggest that the perceived
usefulness of classroom management system is the key to
students using it. If they feel it is useful in an overall way,
they will use it to communicate with their instructors and
their classmates. They will also enjoy using it, which will
likely increase the time and scope of activities for the classroom management system is used. Results also suggest that
the effectiveness of a CMS as a communication tool can
impact on enjoyment with using, perhaps at least within the
scope of the class, taking on the role of social media of
choice for students.
LIMITATIONS AND FURTHER STUDY
This study used convenience samples consisting of all the
students in the classes and the overall sample size was relatively small. Also, this study is limited in that it does not
have direct measures of student use of classroom management systems. Students can say what they enjoy or what
they find useful, but the relationship with behavior may be
different. Future researchers should directly track classroom management system usage by students, tying behaviors to measures of various perceptual and personality
antecedents.
In addition, this study only samples traditional students
who have in-class contact with the instructor and face-toface interaction with classmates. Online students who use
Moodle as their primary link to the learning experience
might have different perceptions and reactions. Future
researchers need to investigate student perceptions of classroom management software among online students and
compare them to those of traditional students. Last, the
questions regarding measuring the learning styles in the
Fleming questionnaire were from a commercial website,
but the items are similar to existing validated learning style
inventories (Felder & Spurlin, 2005; Martinez, 2001).
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APPENDIX MEASURES
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Implicit Theory
1. A person’s ability to work well with the internet and software is something very basic to them and can’t be changed
much.
2. Whether a person can work well with the internet and software is deeply ingrained in their personality. It cannot be
changed much.
3. There is not much that can be done to change whether or
not a person can work well with the internet and software.
Internet Self-Efficacy
1. I am confident that I can connect to the web pages I want to
browse.
2. I am confident that I can use the Internet to download the
information I need.
3. I am confident that I can use the search for information.
Academic Self-Efficacy
1. I have high academic expectations of myself.
2. I believe it is possible for me to make good grades.
3. I am determined to do what it will take in order to succeed
with my goals.
4. Gaining knowledge is important to me.
Difficulty
1. I often become confused when I use Moodle.
2. I make errors frequently when using Moodle.
3. Interacting with Moodle is often frustrating.
Usefulness
1. Using Moodle reduces time spent on unproductive activities
in my learning.
2. Using Moodle enhances my effectiveness on my study.
3. Using Moodle improves the quality of the study I do.
4. Using Moodle makes it easier to do my study.
5. Using Moodle is an effective way for me to learn.
6. Moodle is an appropriate tool for me to use as a learning
medium.
Moodle—Communication Effectiveness
1. Moodle makes discussion with classmates easier.
2. Moodle makes it easier to share new knowledge with
classmates.
223
Vigentini, L. (2009). Using learning technology in university courses:
Do styles matter? Multicultural Education & Technology Journal,
3, 17–32.
Young, M. R., Klemz, B. R., & Murphy, J. W. (2003). Enhancing learning
outcomes: The effects of instructional technology, learning styles,
instructional methods and student behavior. Journal of Marketing Education, 25, 130–142.
3. Moodle makes it easier to get access to classmates’
opinions.
Moodle—Functional Effectiveness
1. Moodle helps me organize my time so that I have plenty of
time to study.
2. Moodle helps me make study goals and keep up with them.
3. Moodle helps me break big assignments into manageable
pieces.
4. Moodle helps me the ways to organize course materials.
5. Moodle helps me in better understanding of the project/
assignment.
6. Moodle helps me to accomplish my task quickly.
7. Moodle helps me to improve my performance.
8. Moodle helps me to enhance effectiveness of my assignment/project.
Satisfaction
1. I am satisfied with Moodle.
2. I am pleased with Moodle.
3. I am satisfied by the contents of the information found on
Moodle.
4. I am satisfied by the format in which information is found
on Moodle.
5. I am satisfied by the timeliness in which information is
found on Moodle.
Enjoyment
1. Using Moodle is a fun activity.
2. Using Moodle stimulates my imagination.
3. Using Moodle is interesting.
Learning Style
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
I like to read out loud.
I like oral reports.
I am good at explaining.
I enjoy acting / being on stage.
I am good in study groups.
I like science lab.
I study with loud music on.
I like adventure books and movies.
I usually take breaks when studying.
I am nervous during lectures.
I need quiet study time.
I have to think awhile before understanding lecture.
I am good at spelling
I understands/likes charts.
I am good with sign language.
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Student Reactions to Classroom Management
Technology: Learning Styles and Attitudes Toward
Moodle
Christina Chung & David Ackerman
To cite this article: Christina Chung & David Ackerman (2015) Student Reactions to Classroom
Management Technology: Learning Styles and Attitudes Toward Moodle, Journal of Education
for Business, 90:4, 217-223, DOI: 10.1080/08832323.2015.1019818
To link to this article: http://dx.doi.org/10.1080/08832323.2015.1019818
Published online: 25 Mar 2015.
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Date: 11 January 2016, At: 19:18
JOURNAL OF EDUCATION FOR BUSINESS, 90: 217–223, 2015
Copyright Ó Taylor & Francis Group, LLC
ISSN: 0883-2323 print / 1940-3356 online
DOI: 10.1080/08832323.2015.1019818
Student Reactions to Classroom Management
Technology: Learning Styles and Attitudes
Toward Moodle
Christina Chung
Downloaded by [Universitas Maritim Raja Ali Haji] at 19:18 11 January 2016
Ramapo College of New Jersey, Mahwah, New Jersey, USA
David Ackerman
California State University, Northridge, Northridge, California, USA
The authors look at student perceptions regarding the adoption and usage of Moodle. Selfefficacy theory and the Technology Acceptance Model were applied to understand student
reactions to instructor implementation of classroom management software Moodle. They
also looked at how the learning styles of students impacted their reactions to Moodle. Results
show that students most valued the control Moodle gave them over their educational
progress. Communication was also found to be an important benefit students sought in
Moodle. Individual student reaction to Moodle was influenced by visual learning and degree
of laziness.
Keywords: classroom management software, learning styles, Moodle, self-efficacy,
technology acceptance model
In higher education, using a course management system
(CMS) has become an essential tool for many instructors.
As a result researchers have started to focus on the benefits
of CMS in teaching and learning. A few studies such as
Chung and Ackerman (2010) and Payette and Gupta (2009)
have examined managing a CMS in terms of instructors’
perceptions, but there is less investigation regarding student
reaction to CMS.
In contrast to instructors, students do not have as much
choice about the use of a CMS. If the course is a required
course, they can choose a course section. If it is an elective,
they can choose not to take the course, but for the most part
selection is more likely based on time and content than on
instructor use of CMS. For the most part students will experience the degree of CMS that their instructors implement.
Despite this lack of choice for students, CMS can influence
the entire structure and flow of their coursework. More
Correspondence should be addressed to David Ackerman, California
State University, Northridge, College of Business and Economics, Department of Marketing, 18111 Nordhoff Street, Northridge, CA 91330-8377,
USA. E-mail: david.s.ackerman@csun.edu
Color versions of one or more figures in this article can be found online
at www.tandfonline.com/vjeb.
importantly, their reaction to an instructor’s implementation of CMS can greatly impact their learning experience.
The major CMS are Blackboard (Blackboard Inc.,
Washington, DC) WebCT (Washington, DC), and Moodle,
though there are many other choices available. Despite
familiarity with Blackboard or WebCT, as of August 2014,
Moodle had a user-base of 53,958 registered and verified
sites, serving 68,958,596 users in 7.6C million courses
(Moodle, 2015). Moodle is an open-source learning management system. This means Moodle is available free of
charge to anybody under the terms of the General Public
License—there is no licensing fee.
Moodle provides several functions. Moodle can facilitate
student–instructor and student–student interactions. Message boards and customizable chat rooms allow both asynchronous and synchronous communication. Students
themselves can communicate within groups and use discussion boards themselves. Study guides provided by instructors and perhaps shared commonly among students are an
important benefit (Lewis et al., 2005). This common ground
for communication in cyberspace makes it an important
tool for online classrooms. Moodle also allows for more
rapid distribution of grades for exams and assignments. A
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218
C. CHUNG AND D. ACKERMAN
Moodle classroom home page is a very efficient tool that is
a much less time consuming and error prone process than
completion of the same tasks using paper or even email.
Business instructors have adopted use of the system for
both online courses and face-to-face classrooms. Some
have suggested that student motivation is a key factor in the
success of Moodle in the classroom and that students found
it easier to use (Beatty & Ulasewicz, 2006). Students do
like Moodle better than faculty (Payette & Gupta, 2009),
but this may be a function of greater faculty familiarity
with other classroom management software.
The purpose of this study was to investigate student perceptions in adopting and using Moodle and how their perceptions impact the effective use of the CMS. First, this
research looks at the influence of several constructs including academic self-efficacy, internet self-efficacy, usefulness,
difficulty, communication effectiveness, and enjoyment on
student perceptions of CMS. Second, the impact of learning
styles and implicit theory on the functional benefits students
derive from CMS is examined. The findings help explain
student perspectives on Moodle and provide the basis for
suggestions as to how faculty can effectively implement
Moodle for their teaching.
THEORETICAL FOUNDATION AND HYPOTHESES
Self-Efficacy and Technology Acceptance Model
From a student’s perspective, Moodle provides the means
whereby they receive class materials and submit assignments to instructors. Studies have suggested that students
do find online learning and components provided by most
classroom software packages to be effective in overall
learning (Clarke, Flaherty, & Mottner, 1999) and a CMS
can be used in a variety of online active/passive learning
experiences, including even a social dilemma game (Oertig,
2010). Overall, they are in fact very positive about most
aspects of a CMS (Carvalho, Nelson, & Silva, 2011). This
positive impact does not seem to vary by the learning style
of the student (Young, Klemz, & Murphy, 2003).
Despite these potential benefits, the use of a CMS is not
always met with optimism. Could a lack of clarity about
how to use CMS, the inability to complete tasks and perhaps
the stresses or other negative aspects of using it lead some
students to view it with disfavor? This could also influence
student evaluations of a course and their instructors.
The two theories, self-efficacy theory and Technology
Acceptance Model (TAM), were utilized for a theoretical
foundation in analyzing the relationships amongst these
variables. Within social cognitive theory, self-efficacy theory was developed by Bandura (1977). Self-efficacy refers
to beliefs about an individual’s capabilities to learn or perform behaviors at designated levels (Bandura, 1986, 1997).
This theory explains that an individual has a certain level of
confidence in his or her ability to perform tasks. Academic
self-efficacy and Internet self-efficacy were examined as
exogenous variables. Academic self-efficacy is expressing
confidence in academic ability, awareness of effort toward
study, and expectation for success in college attainment.
Much research shows that self-efficacy influences academic
motivation, learning, and achievement (Pajares, 1996;
Schunk, 1995). Internet self-efficacy focuses on how well
one believes s/he can accomplish needed tasks and goals on
the Internet (M. L. Lai, 2008). This type of self-efficacy is a
potentially important factor to examine student perceptions
on Moodle.
TAM was developed by Davis (1989) based on the theory
of reasoned action to explain computer usage behavior. There
are two constructs in the model, perceived usefulness (PU)
and perceived ease of use (PEOU), that measure the degree
of an individual’s system usage and perceptions in examining
behavioral intention and actual use. PU is the extent to which
applications contribute to improving user performance.
PEOU refers to the degree of required effort to take advantage of the application (Davis, 1989). Davis, Bagozzi, and
Warshwa (1989) found that perceived usefulness is a major
determinant of people’s intentions to use computers. Usefulness beliefs were more salient for inexperienced users than
experienced users (Taylor, 2004). Based on these theories
and previous research, a research model was created (Figure 1) and the following hypotheses developed to examine
the relationships between the latent constructs:
Hypothesis 1 (H1): Academic self-efficacy is positively
related to internet self-efficacy.
H2: Internet self-efficacy is negatively related to perceived
difficulty and positively related to perceived
usefulness.
H3: Perceived usefulness is negatively related to perceived
difficulty and positively related to communication
effectiveness and enjoyment in using Moodle.
H4: Perceived difficulty is negatively related to communication effectiveness and enjoyment in using Moodle.
H5: Communication effectiveness is positively related to
enjoyment in using Moodle.
Learning Styles and CMS
Can learning styles impact on student reaction to classroom
management systems? If so, what dimension of learning
style is most closely linked to adoption of CMS such as
Moodle? Students perceive that there is a relationship
between general technology use and their learning style
(C. Lai, Wang, & Lei, 2011). This certainly makes sense
from what instructors see in the course of a semester
regarding the way students communicate. Some students
like to communicate online by email and some by class discussion boards. Yet others prefer face-to-face communication. These differences are also seen in the way work is
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STUDENT REACTIONS TO CLASSROOM MANAGEMENT TECHNOLOGY
219
FIGURE 1 Research model: Student perceptions of Moodle.
turned into the instructor. If requirements about the way
work are turned in is not specified, some students will prefer to email in assignments from a home computer, some
like to post it on a classroom management site, yet others
will send it in by a variety of methods from their tablet PC
or cell phone as soon as they are finished. Can specific
learning styles have an impact on the use of classroom management technology?
Just as in face-to-face learning, students differ in how
they prefer information to be presented online as well. For
example, Saeed, Yang, and Sinnappan (2009) found that
sensors, who are careful and more detail oriented, preferred
email over other types of communication in learning where
as others like intuitors and visual learners preferred blogs
and videos respectively. Similarly, learning style can
impact on how students utilize learning technology as well
(Vigentini, 2009). Use of online material instructors supply
to students is an increasingly frequently-used component of
courses so it is important to determine the impact of learning styles on student perceptions of the different components of a classroom management system.
In sum, not all students will react in the same way to
instructor implementation of CMS. Some adapt quickly,
some more slowly, and yet others really have specific needs
that are fulfilled by the type of features their instructors provide for them in CMS. Students who have different learning
styles will take a different approach and perhaps require
some flexibility on the part of the instructor. Thus, in this
study, three specific questions regarding learning styles
were developed.
Research Question 1 (RQ1): Do learning styles have an
impact on student perceptions of classroom management technology?
RQ2: Which of the dimensions of learning styles have the
greatest impact on student perceptions of classroom
management technology?
RQ3: Which aspects of classroom management technology
are most impacted by student learning styles?
METHOD
We administered a web survey designed to measure marketing student perceptions toward CMS. Data were
collected using a convenience sampling method using a
self-administered questionnaire among marketing major
students. One hundred twenty-five respondents from six
marketing classes at two universities, in the northeast and
in the southwest, participated in the survey. The samples
consisted of 58% women and 42% men. All respondents
were between 18 and 28 years old. Eight-three percent of
students were juniors and seniors. Respondents revealed
that, besides Moodle, they had used Blackboard (30%),
WebCT (29%), and other (16%) CMS. In addition, students
indicate they have good Moodle literacy (average 5.7 of 7).
For all questions, the response options consisted of a 7point Likert-type scale ranging from 1 (strongly disagree)
to 7 (strongly agree).
Questionnaire items measuring Moodle usefulness
(Cronbach’s a D .94), Moodle difficulty (Cronbach’s a D
.86), and Internet self-efficacy (Cronbach’s a D .93) scales
were adapted from Chen and Tseng’s (2012) study. Academic self-efficacy scale (Cronbach’s a D .85) was modified
from the College Learning Effectiveness Inventory scale.
Moodle communication effectiveness (Cronbach’s a D .90)
and enjoyment scales (Cronbach’s a D .93) were adapted
from Martınez-Torres et al.’s (2008) research. In addition,
220
C. CHUNG AND D. ACKERMAN
there was a scale for implicit theory (Cronbach’s a D .83)
modified from Beruchashvili, Moiso, and Heisley (2014).
Learning style scales was adapted from Fleming (n.d.).
A factor analysis performed on the inventory of learning
styles found four factors. These were related to being
“social” (with factor loadings of .66–.81), “doesn’t like
listening” (with factor loadings of .62–.83) “visual,” (with
factor loadings of .72–.76), and “lazy” (with factor loadings
of .57–.74).
Downloaded by [Universitas Maritim Raja Ali Haji] at 19:18 11 January 2016
RESULTS
An exploratory factor analysis (EFA) was run to assess the
measurement properties of the scales. Some items with factor loadings lower than .5 were deleted and a six-factor
solution of 23 items was identified. The EFA solution
accounted for 80% of the cumulative variance. Cronbach’s
alpha was used to measure internal consistency. All measures demonstrate good reliability with alpha values of .85
and greater (see Appendix).
Subsequent testing using confirmatory factor analysis
(CFA) was examined for the overall validity of the measurement model. The CFA results indicate an acceptable fit
with x2 D 358.69, df D 215, p D .000, comparative fit index
(CFI) D .94, root mean square error of approximation
(RMSEA) D .07, Tucker-Lewis index (TLI) D .92. The
CFI and TLI exceed the recommended cut-off value of .9
and the RMSEA is lower than the cutoff value of .08. Further, construct validity is evaluated based on the factor
loading estimates, construct reliabilities, variance extracted
percentages and inter-construct correlations. All loading
estimates are significant (p < .000) with the lowest being
.69 and the highest being .94. The variance-extracted estimates are .60, .82, .73, .62, 77, and .83 for academic selfefficacy, Internet self-efficacy, perceived usefulness, perceived difficulty, communication effectiveness, and enjoyment, respectively. In addition, the construct reliability
estimates are all adequate, ranging from .85 to .98.
Discriminant validity is measured by comparing the variance-extracted percentage for any two constructs with the
square of the correlation estimate between these two constructs. The results indicate that the convergent validity of
the model is supported and good reliability is also
established.
The next step was to examine the overall theoretical
model specification and the hypotheses by using the structural equation modeling (SEM). The SEM results indicate a
satisfactory fit of data with x2 D 361.15, df D 221, p D
.000, CFI D .94, RMSEA D .07, TLI D .93. The SEM
structural path results reveal that all hypotheses are supported except H4 (Figure 2).
To examine RQ1 through RQ3, a regression analysis of
the factors impacting on overall satisfaction with Moodle
were also significant, F(7, 125) D 31.31, p D .00, R2 D .63.
Significant dependent variables included visual (Std. b D
.12), t D 2.01, df D 124, p < .05; being social (Std. b D
–.14), t D –2.34, df D 124, p < .05; difficulty (Std. b D
.15), t D 2.38, df D 124, p < .05; usefulness (Std. b D .25),
t D 3.08, df D 124, p < .00; and control (Std. b D .48), t D
6.32, df D 124, p < .00.
In addition, a regression analysis was used to analyze
student perception of the functional benefits of Moodle
because classroom management software is by its nature
and use functional. The results of a linear regression were
significant, F(6, 125) D16.98, p D .00, R2 D .44. Significant
dependent variables included verbal (Std. b D .14), t D
1.97, p D .05; lazy (Std. b D –.14), t D –2.01, p < .05; difficulty (Std. b D .26), t D 3.82, p < .00; and communication
(Std. b D .47), t D 6.55, p < .00. Lastly, a correlation with
the implicit theory measure found that entity theory personality in students was inversely related to satisfaction with
Moodle (r2 D –.19, p D .04).
DISCUSSION AND IMPLICATIONS FOR
INSTRUCTORS
These results suggest first that the single most important
factor in overall satisfaction with classroom management
system is the control it gives students over their educational
progress. Depending on how it is implemented by the
instructor, CMS offers students flexibility in the timing and
amount of work they upload at any particular time. They
can also see their progress online. Such flexibility can
empower students who otherwise may feel they are at the
mercy of the instructor’s or department’s schedule. The
implication for instructors is that they should set up CMS
so that students are best able to monitor their own progress.
The schedule, including assignments and readings, should
be embedded as much as possible in the CMS so students
know beforehand the pace of the work and how much they
need to complete to move on in the course.
The result of a positive relationship between difficulty
and satisfaction or functional benefits of classroom management software was surprising. Perhaps, to an extent students felt that the more difficult software management was,
the more effective it was. Difficulty up to a certain degree
can be a challenge that is perceived as facilitating a goal. In
this case, a certain degree of complexity may also have
given students a sense of accomplishment that they were
learning a software system. The implication of this for
instructors is that it is ok to push students a little, to challenge them with a CMS. Maybe instructors could set up a
more elaborate and enriching curriculum on Moodle, with
videos and exercises, to motivate. Learning an instructor’s
system, with helpful features and functions, can be rewarding in and of itself.
Visual learning is also an important factor in overall student satisfaction with classroom management software.
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STUDENT REACTIONS TO CLASSROOM MANAGEMENT TECHNOLOGY
221
FIGURE 2 Tests of the hypotheses.
Given the graphics and visuals in CMS such as Moodle,
visual learners would be more satisfied with the system. As
this trend continues with software moving over to Appletype graphics systems, visual learners will be at an even
greater advantage in coming years. The implication of this
finding is that instructors need to expect to spend a little
more time with students who are not visual learners when
setting up a CMS. Perhaps setting up written protocols for
functions in the CMS the instructor has implemented may
help. Visual models for students who are not oriented
toward visual learning to copy may aid in walking these
students through the steps they need to complete.
On the one hand, it seems obvious that usefulness would
be a factor in satisfaction with classroom management software. On the other hand, enjoyment or other positive factors had no impact. This suggests that classroom
management software such as Moodle are viewed strictly
as tools for school work, not for fun or personal enrichment.
It also means that instructors are not likely to find students
available on the CMS on the weekends and breaks if they
need to communicate with them and may need to use other
means.
The findings for incremental versus entity theories of
intelligence are in line with what would be expected given
extant literature (Burnette, O’Boyle, VanEpps, Pollack, &
Finkel, 2013; Shih, 2011). Those who had a more rigid
entity view about their ability to deal with technology, it is
fixed and cannot change, were less likely to be satisfied
with Moodle. Those who had a more flexible view of ability
to work with technology were more likely to be satisfied
with Moodle.
Laziness impacted negatively on the functional benefits
of Moodle but not overall satisfaction. This finding suggests
that harder working students are more concerned
specifically with the functional benefits that can be derived
from a classroom management system. They are not necessarily happier overall than lazier students with CMS such
as Moodle. Instructors who wish to reward harder working
students may emphasize the functional benefits of their
implementation of the CMS. They could explain, for example, how downloading of a study guide or a group feedback
discussion board can impact on a specific part of the course
or the grade.
CONCLUSIONS
These results suggest that communication benefits, both
communication and verbal learning style are significant,
are an important perceived benefit of classroom management systems to students. Moodle does help facilitate communication both between student and instructor as well as
between students themselves. Students may be reluctant to
connect with classmates who are not friends on social
media sites to do class work or group work. On the other
hand, given our previous finding, classroom management
software is strictly workspace. To the degree to which
classroom management software can facilitate communication regarding class work and events between students and
instructors, it will be perceived as beneficial. Instructors
can aid in this process by perhaps setting up times where
out-of-class discussion can take place. Other instructors
encourage and give points for student comments in chat
rooms, which is an extrinsic reward that could encourage
use of the CMS as a means of communication.
SEM results indicate that students who are confident in
their overall academic abilities will tend to be more confident in other areas such as Internet or technology usage.
Downloaded by [Universitas Maritim Raja Ali Haji] at 19:18 11 January 2016
222
C. CHUNG AND D. ACKERMAN
Overall academic self-efficacy led to Internet self-efficacy
and the Internet self-efficacy is significantly related to perceived usefulness and perceived difficulty. As shown in
Figure 2, even though there is significant relationship
between perceived usefulness and perceived difficulty, the
only important factor that is positively related to communication effectiveness and enjoyment in using Moodle is perceived usefulness. These results suggest that the perceived
usefulness of classroom management system is the key to
students using it. If they feel it is useful in an overall way,
they will use it to communicate with their instructors and
their classmates. They will also enjoy using it, which will
likely increase the time and scope of activities for the classroom management system is used. Results also suggest that
the effectiveness of a CMS as a communication tool can
impact on enjoyment with using, perhaps at least within the
scope of the class, taking on the role of social media of
choice for students.
LIMITATIONS AND FURTHER STUDY
This study used convenience samples consisting of all the
students in the classes and the overall sample size was relatively small. Also, this study is limited in that it does not
have direct measures of student use of classroom management systems. Students can say what they enjoy or what
they find useful, but the relationship with behavior may be
different. Future researchers should directly track classroom management system usage by students, tying behaviors to measures of various perceptual and personality
antecedents.
In addition, this study only samples traditional students
who have in-class contact with the instructor and face-toface interaction with classmates. Online students who use
Moodle as their primary link to the learning experience
might have different perceptions and reactions. Future
researchers need to investigate student perceptions of classroom management software among online students and
compare them to those of traditional students. Last, the
questions regarding measuring the learning styles in the
Fleming questionnaire were from a commercial website,
but the items are similar to existing validated learning style
inventories (Felder & Spurlin, 2005; Martinez, 2001).
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APPENDIX MEASURES
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Implicit Theory
1. A person’s ability to work well with the internet and software is something very basic to them and can’t be changed
much.
2. Whether a person can work well with the internet and software is deeply ingrained in their personality. It cannot be
changed much.
3. There is not much that can be done to change whether or
not a person can work well with the internet and software.
Internet Self-Efficacy
1. I am confident that I can connect to the web pages I want to
browse.
2. I am confident that I can use the Internet to download the
information I need.
3. I am confident that I can use the search for information.
Academic Self-Efficacy
1. I have high academic expectations of myself.
2. I believe it is possible for me to make good grades.
3. I am determined to do what it will take in order to succeed
with my goals.
4. Gaining knowledge is important to me.
Difficulty
1. I often become confused when I use Moodle.
2. I make errors frequently when using Moodle.
3. Interacting with Moodle is often frustrating.
Usefulness
1. Using Moodle reduces time spent on unproductive activities
in my learning.
2. Using Moodle enhances my effectiveness on my study.
3. Using Moodle improves the quality of the study I do.
4. Using Moodle makes it easier to do my study.
5. Using Moodle is an effective way for me to learn.
6. Moodle is an appropriate tool for me to use as a learning
medium.
Moodle—Communication Effectiveness
1. Moodle makes discussion with classmates easier.
2. Moodle makes it easier to share new knowledge with
classmates.
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3. Moodle makes it easier to get access to classmates’
opinions.
Moodle—Functional Effectiveness
1. Moodle helps me organize my time so that I have plenty of
time to study.
2. Moodle helps me make study goals and keep up with them.
3. Moodle helps me break big assignments into manageable
pieces.
4. Moodle helps me the ways to organize course materials.
5. Moodle helps me in better understanding of the project/
assignment.
6. Moodle helps me to accomplish my task quickly.
7. Moodle helps me to improve my performance.
8. Moodle helps me to enhance effectiveness of my assignment/project.
Satisfaction
1. I am satisfied with Moodle.
2. I am pleased with Moodle.
3. I am satisfied by the contents of the information found on
Moodle.
4. I am satisfied by the format in which information is found
on Moodle.
5. I am satisfied by the timeliness in which information is
found on Moodle.
Enjoyment
1. Using Moodle is a fun activity.
2. Using Moodle stimulates my imagination.
3. Using Moodle is interesting.
Learning Style
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
I like to read out loud.
I like oral reports.
I am good at explaining.
I enjoy acting / being on stage.
I am good in study groups.
I like science lab.
I study with loud music on.
I like adventure books and movies.
I usually take breaks when studying.
I am nervous during lectures.
I need quiet study time.
I have to think awhile before understanding lecture.
I am good at spelling
I understands/likes charts.
I am good with sign language.