Perceptions of Compressed Video
Distance Learning (DL) Across Location
and Levels of Instruction in Business
Courses
CONSTANCE R. CAMPBELL
CATHY OWENS SWIFT
GEORGIA SOUTHERN UNIVERSITY
STATESBORO, GEORGIA
ABSTRACT. In this article, the authors
compared student perceptions about distance learning (DL) across location, type of
business course, and level of instruction.
Results indicated that there were no differences in student perceptions based on type
of course or level of instruction. Onsite
students found the DL classroom more distracting than did remote location students,
and the lack of alternative course delivery
formats was more relevant to remote than
to onsite students. All students were more
satisfied than dissatisfied with the DL
experience.
Copyright © 2006 Heldref Publications
170
Journal of Education for Business
I
t is difficult to envision future universities being completely virtual (Dator,
1998; Dunn, 2000), but distance learning
(DL) is a rapidly increasing phenomenon
at the college level. The term DL has
been used to represent a variety of delivery formats, including correspondence
courses, Internet-based courses, interactive videos, television, compressed video,
cable television, and satellite broadcasting (Chadwick, 1995; Potashnik & Capper, 1998; Rungtusanatham, Ellram,
Siferd, & Salik, 2004).
Despite the increased use of online
virtual course delivery systems (Rungtusanatham et al., 2004), compressed
video DL continues to be a popular
form of course delivery. Compressed
video enables an instructor to interact
with geographically separated students,
merging the students into one virtual
classroom (Plagemann & Goebel,
1999). Debate about the effectiveness
of this delivery method continues
(Vamosi, Pierce, & Slotkin, 2004), perhaps because there are still relatively
few evaluations of its effectiveness.
The primary area of concern about DL
is its pedagogical quality (Li, 2005). Of
the published studies concerning the
quality of DL classes, many considered
only one course, thereby limiting the
generalizability of the results. In addition, some examinations of DL have
focused on graduate courses, whereas
others have focused on undergraduate
instruction, but comparisons have not
been made across levels of instruction. A
second major area of concern about DL is
its cost-effectiveness (Fornaciari, Forte,
& Mathews, 1999; Hawkes & Cambre,
2000), but there are currently few evaluations of this issue (Selim, 2005). The purpose of this study was to explore the pedagogical quality and cost effectiveness of
DL, comparing across classes within the
business discipline, across onsite and
remote locations, and across graduate
and undergraduate courses.
Literature Review
A unique feature of DL is the two
groups of students involved in the course,
those onsite and those viewing the classroom through interactive television at a
remote site. Although all of these students experience the same course, it is
unlikely that their experience of the
course is the same, raising the issue of
comparability of the quality of instruction at the onsite and remote locations.
Pedagogical Quality
One means of assessing the quality of
instruction has been to compare onsite
and remote students’ performances. For
example, using pre- and post-test measures, Magiera (1994) found no differences in learning. Likewise, Umble,
Cervero, Yang, and Atkinson (2000)
found no significant differences in learn-
ing between traditional and DL classes in
a course on vaccine-preventable diseases.
In both instances, though, only one class
comprised the study sample.
Others have used grades as a measure
of learning locations, with mixed results.
Researchers have reported grades for students at the remote location that were
either comparable to or higher than
grades of onsite students (Knight & Zhai,
1996). However, these results were often
obtained when studying varied disciplines. Within the business field, Knight
and Zhai found significant differences in
remote and onsite students’ grades in
14% of the courses studied, eight of
which were business courses.
Another approach to comparing quality of instruction at onsite and remote
locations is to examine students’ perceptions of their DL experience. Several factors, including technology, influence students’ perceptions of DL, not only for its
presence, but also for its quality and reliability (Plagemann & Goebel, 1999). In a
report of a DL experience, Crow, Cheek,
and Hartman (2003) noted that technical
difficulties were a key contributor to the
lack of success in their DL courses. Likewise, Magiera (1994) found that the need
to press a microphone button to speak at
remote locations inhibited student participation. Atkinson (1999) similarly reported that the limitations in technology in
the DL environment had a greater impact
on remote students than on onsite students. Based on this information, it
appears that technology is a key factor in
the DL environment and that its impact is
greater for remote students as compared
with onsite students. The technology
issue has not been examined using only
business courses nor has it been examined across levels of instruction. Thus,
we developed the following hypotheses:
H1: DL technology will be more distracting to remote than to onsite students;
H1a: There will be no difference in the
reported level of distraction by technology among types of business classes; and
H1b: There will be no difference in the
reported level of distraction by technology between undergraduate and graduate
students.
The physical presence of the instructor is also a factor in DL. Freddolino
(1996) found that onsite and remote students had similar perceptions of DL,
except in the area of relationships. On
the basis of this information, we expected the absence of the professor to be a
greater issue at remote locations than at
onsite locations. Once again, there was
no information on which to base predictions of differences across types of
classes or levels of instruction. Our
hypotheses were as follows:
H2: Remote DL students will be more
likely to agree that the physical absence
of the instructor affected their learning in
the course;
H2a: There will be no difference in the
impact of the physical absence of the
instructor among types of business classes;
and
H2b: There will be no difference in the
impact of the physical absence of the
instructor between undergraduate and
graduate students.
Student satisfaction with DL has been
a concern, but results of satisfaction studies have been mixed. Vamosi et al. (2004)
discovered that all students perceived that
DL hindered their learning of course
material and made the course less interesting to them, decreasing their motivation in the course; however, they did not
compare onsite and remote locations and
only used one class as a measure. Likewise, Ponzurick, France, and Logar
(2000) found students to be least satisfied
with the DL delivery method, compared
with other course delivery formats. In
contrast, comparing DL with traditional
classroom instruction, Knight and Zhai
(1996) found that students were satisfied
with their DL experience. Freddolino
(1996) found no difference between
onsite and remote students’ overall perceptions of the DL course. On the basis
of these mixed results, we proposed the
following hypotheses:
H3: There will be no difference
between onsite and remote students in
their satisfaction with the DL experience;
H3a: There will be no difference among
students in various business classes in their
satisfaction with the DL experience; and
H3b: There will be no difference
between graduate and undergraduate students in their satisfaction with the DL
experience.
Cost-Effectiveness
There are few publications regarding
the cost-effectiveness of DL. Hawkes
and Cambre (2000) list 12 nontraditional measures of cost-effectiveness for
DL, among which are the extent to
which DL (a) provides opportunities for
students to participate in courses, (b)
results in an increase in the number of
students participating, and (c) helps
“sell the school” to prospective students.
These measures reflect changes in the
demographic characteristics of potential
college students. Currently, there is a
group of potential students who wish to
continue their education, but who are
unable to focus exclusively on a fulltime educational program that is location-specific (Freddolino, 1996). For
these students, the accessibility of the
course is a primary determinant of their
participation (Vamosi et al., 2004).
These students are likely to elect DL
classes because of the convenience they
offer, not because they are the preferred
method of delivery (Ponzurick et al.,
2000; Vamosi et al.). These findings
suggest a difference between remote
and onsite students in terms of the alternatives available to them. Therefore, we
formed the following hypothesis:
H4: The lack of alternatives to DL will be
more important to remote students.
METHOD
Setting
We collected data from DL courses
offered through interactive television
and satellite broadcast, originating from
a comprehensive public university.
Instructors presented course material
primarily from the onsite location with
the capability for all participants to
interact. The professor was generally
present onsite, with occasional visits to
remote locations. Therefore, all students
had experience with the professor being
present and absent from their locations.
Business DL courses originate from
a DL classroom with four large screen
televisions—two in the front of the
room and two in the back. On the front
screens, DL students view themselves
on one screen and the remote locaJanuary/February 2006
171
tion(s) on the other. In the back of the
room, instructors view themselves on
one screen and the remote location(s)
on the other. Information is transmitted
by compressed digital video system.
Available for the instructor’s use are an
Elmo (which projects an image of a
sheet of paper in a manner similar to
that of an overhead projector), whiteboard, computer, and video player. A
facilitator in the room assists in moving between technologies and ensures
that the camera follows the instructor’s
movements. Remote locations also
have up to four large-screen televisions
as well as computer equipment, dry
erase board, and a technical facilitator.
At all locations, students must press a
button on a microphone and speak into
the microphone when making comments or asking questions.
not identify survey respondents, the university chose not to elicit demographic
information, such as gender or race, on
the Distance Learning Survey.
Analysis
The location at which the student
completed the course (i.e., onsite or
remote), the particular type of business
course, and the level of the course
(undergraduate or graduate) were independent variables. Question 5 and
Question 2 (see Appendix) were used as
the dependent variables in a multivariate
analysis of variance (MANOVA) to analyze the first two hypotheses. To test the
remaining hypotheses, we factor analyzed the survey, and we used the resulting factors in a second MANOVA.
RESULTS
Survey
Table 1 shows means, standard deviations, and correlations. The test of the
first hypothesis, which suggested that
remote site students would be more distracted by the DL technology than
onsite students would, was significant,
but not in the predicted direction, F(1,
490) = 3.09, p < .05. Onsite students
were more likely to agree that the technology inhibited their learning than
were remote location students. The
impact of technology in the DL classroom was not perceived differently
depending on which business class was
surveyed, F(5, 490) = 1.43, nor upon
whether students were undergraduates
or graduates, F(1, 490) = .59.
At the end of each semester, students
completed a Distance Learning Survey
(see Appendix) that was developed by the
participating university for use as their
student rating of instruction. Each question was answered on a scale from 1
(strongly disagree) to 5 (strongly agree).
Participants
We used a total of 521 surveys in the
study: 248 onsite and 273 remote. Most
respondents were undergraduate students
(61%), with the largest numbers in management courses. To ensure confidentiality of responses so that professors could
The second hypothesis was not supported. With respect to the impact of the
instructor’s presence in the classroom,
there was no difference in student ratings by location, F(1, 490) = .33. There
was also no difference by type of business class, F(5, 490) = 2.03, or by level
of class, F(1, 490) = .34.
Because there was more than one
question pertaining to satisfaction with
the course and alternatives to the course,
we conducted a principal components
factor analysis on the survey, resulting
in three factors, which explained 71% of
the variance in the data. We also conducted an oblique rotation of the data
using Direct Oblimin (SPSS, Chicago,
IL) to interpret the factors, producing
the factor matrices in Table 2. The first
factor comprised statements that were
worded in favor of DL; therefore, we
called this factor Satisfaction. Cronbach’s alpha reliability of this factor
was .89. The second factor consisted of
statements about DL that were worded
unfavorably; therefore, we called this
factor Dissatisfaction (α = .80). The
third factor consisted of statements
about alternatives to DL. Therefore, we
called this factor Alternatives (α = .88).
The MANOVA of the third set of
hypotheses indicated that there was no
difference in satisfaction or dissatisfaction between the onsite and remote location students, F(1, 478) = .22 and F(1,
478) = 1.15, respectively. Furthermore,
there were no differences in students’
reported satisfaction by type of class,
F(5, 478) = 1.57 or by level of class F(1,
478) = .54.
TABLE 1. Means, Standard Deviations, and Correlations Among Variables
Question
1
2
3
4
5
6
7
8
9
10
11
M
SD
1
2
3
4
5
6
7
8
9
10
11
2.62
2.55
2.76
2.69
2.61
2.75
2.37
2.82
2.85
2.57
2.50
1.20
1.15
1.40
1.29
1.23
1.36
1.04
1.37
1.53
1.42
1.40
.65**
.19**
.43**
.42**
.25**
.34**
.26**
.26**
.14**
.13**
.06
.53**
.49**
.17**
.38**
.13**
.15**
.14**
.16**
.20**
.08
.67**
.13**
.68**
.68**
.42**
.37**
.51**
.26**
.34**
.28**
.27**
.21**
.21**
.09*
.45**
.08
.08
.07
.09*
.02
.63**
.62**
.40**
.34**
.12**
.13**
.22**
.24**
.81**
.46**
.39**
.59**
.49**
.79**
—
*p < .05. **p < .01.
172
Journal of Education for Business
TABLE 2. Pattern/Structure Matrix for Factor Analysis of Student Survey
Instrument
Question
3
6
8
9
10
11
1
2
4
5
7
Satisfaction
Pattern Structure
.828
.849
.842
.786
.261
.144
.223
.018
.178
–.112
–.250
Eigenvalue
% variance
explained
.849
.847
.875
.865
.499
.400
.296
.136
.298
.024
–.034
Factor
Dissatisfaction
Pattern Structure
–.006
.072
.049
.028
–.048
–.032
.759
.849
.697
.779
.574
.144
.200
.203
.208
.171
.179
.759
.838
.731
.768
.622
Alternatives
Pattern Structure
.073
–.048
.083
.247
.821
.874
–.165
–.064
.023
.033
.413
4.365
2.279
1.146
39.682
20.717
10.418
.319
.221
.345
.488
.888
.910
.064
.124
.226
.167
.461
Note. Bold-faced numbers indicate variables included in interpretation of a factor. Satisfaction =
statements in favor of distance learning; Dissatisfaction = expressing disfavor with distancelearning; Alternatives = statements related to distance learning alternatives.
The fourth hypothesis was supported,
indicating that the lack of alternatives to
DL was more important to students at
the remote site than they were to students onsite, F(1, 478) = 8.59, p < .01.
However, there were no differences by
type of class, F(5, 478) = 1.26 or by
level of class, F(1, 478) = .75.
Because the factor analysis resulted
in a factor comprising positive statements and a factor comprising negative
statements, we conducted a paired t test
to compare the positive and negative
statements. The significant result, t(508)
= 4.19, p < .01, indicated that students
were more likely to agree with the positively worded statements than with the
negatively worded ones.
DISCUSSION
Results indicate that compressed
video DL continues to be a viable technology. In terms of pedagogical effectiveness, students are generally more
satisfied than dissatisfied with the DL
experience despite the fact that the DL
technology is more distracting to onsite
than to remote students. The distraction
may be explained by the results of the
fourth hypothesis test. That is, students
who register for DL courses because
they have no other alternatives may be
more psychologically prepared for the
presence of added technology in the DL
classroom.
The lack of significant difference
across groups in the impact of the
physical absence of the instructor may
indicate that this is not an issue for students. An alternative explanation is
that it may indicate that whatever
impact the instructor’s absence has on
students is uniform across locations,
across type of class, and across levels
of instruction.
The results also indicate that DL meets
several of Hawkes and Cambre’s (2000)
cost-effectiveness criteria. DL is effective
in providing otherwise unavailable alternatives for students, thereby providing a
means for recruiting new students. DL is
providing opportunities for that cohort of
students who are unable to physically
relocate (Freddolino, 1996). The level of
student satisfaction represented in this
study also indicates that DL is meeting
the cost-effectiveness measure of providing an educational experience with which
students are satisfied.
Because of the larger number and
variety of student responses included in
this study, as compared with prior studies (Crow et al., 2003; Magiera, 1994),
it was possible to explore the issues of
types of class and level of instruction, as
well as student location. The lack of significant differences in student perceptions based on the type of business
course and the level of instruction suggests that the most important criterion
of differentiation in the DL experience
is the location of the students.
The results of this study extend our
understanding of DL both by confirming
findings from previous research as well
as by providing new insights specific to
this study. In terms of adding to the body
of evidence from previous research (e.g.,
Allen et al., 2004), the current results
continue to confirm that instructors need
not fear a lack of pedagogical quality in
the DL classroom. The results also confirm that students are generally satisfied
with the DL experience.
Several new findings emerged from
this study as well. Prior research on DL
has generally sampled only one course
(Ponzurick et al., 2000; Vamosi et al.,
2004). Our sample included multiple
courses, but all were within the Business discipline; thus, we were able to
demonstrate that perceptions about DL
do not differ across courses within one
broad discipline. Prior research also has
not compared perceptions regarding DL
across levels of instruction. With our
sample of undergraduate and graduate
classes, we were able to demonstrate
that perceptions about DL classes do not
vary across level of instruction. Our
finding that perceptions of DL did differ
by location (i.e., onsite versus remote)
is a contribution of this study and indicates that onsite students, who are more
distracted by the DL technology, may
need extra assistance in becoming
familiar with the DL setting. A final
contribution of the study is the provision of data regarding the fact that
remote students are attracted to DL
because it provides an opportunity to
take courses where no other alternatives
are available.
Future studies may build on the current research by comparing various
types of course delivery (i.e., traditional onsite, DL, and online). Studies
should include undergraduate and
graduate classes and several types of
business classes in all three environments. In the current survey, we did
January/February 2006
173
not include demographic information;
therefore, in future research efforts,
investigators should study differences
in age levels, gender, full-time versus
part-time status, and other variables
that may impact student attitudes.
NOTE
Correspondence concerning this article should
be addressed to Constance R. Campbell, Associate
Professor of Management, Georgia Southern University, PO Box 8154, COBA, Statesboro, GA
30460. E-mail: [email protected]
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APPENDIX
Survey Instrument
Scale: 1 = strongly disagree to 5 = strongly agree
1. The distance learning classroom impacted the way that I learn.
2. The physical absence of the instructor impacted the way that I learn.
3. I learned as much in the distance learning class environment as I would have in an
actual live classroom.
4. The distance learning classroom had more distractions than an actual live
classroom would have had.
5. The technology (cameras, microphones, and television monitors) inhibited the
way I participated in class.
6. My performance in this class was the same as it would have been in an actual live
classroom.
7. My grade in this course was affected by the distance learning format.
8. I enjoyed this distance learning class.
9. I would take another distance learning class.
10. I enrolled in a degree program because it was made accessible by distance
learning.
11. I would not be enrolled if this class were not available by distance learning.