Interactivity in Distance Learning:
Network Expedience and Transparence in Virtual Classes
Investigators:
Larry R. Irons, Ph.D.
Donald J. Jung, Ph.D.
Robert O. Keel
Executive Summary
This report is submitted to the Information Technology Research Committee at the
University of Missouri – St. Louis in partial fulfillment of a research grant for the 199899 academic year. The research focused on students’ satisfaction with the learning
experience in 7 distinct virtual classes. Each virtual class included course offerings from
multiple universities, 19 accredited courses at 8 locations, 2 urban (UMKC/UMSL) and 6
non-urban (St. Joseph, Joplin, Delta Center, Jefferson County, Rolla and Poplar Bluff).
We analyze differences between student perceptions of satisfaction for host and remote
sites, but also differences between students at what we here refer to as urban sites
(UMKC/UMSL) and non-urban sites. Our rationale for this approach comes from the
recognition that all remote sites are not equal.
Like any other complex communications infrastructure, the network connecting different
locations in virtual classes in the University of Missouri system has developed over time
with differing combinations of synchronous and asynchronous communication
technologies at the university locations. Thus, we examine differences between student
perceptions of satisfaction for host and remote sites, and also differences between
students at what we here refer to as urban sites (UMKC/UMSL) and non-urban sites.
Overall, students appreciate the interactivity of virtual classes that include a web
component. But, to the degree use of the web component is a mandatory part of the
course requirements, their satisfaction with the class decreases. This is particularly the
case for non-urban students.
Students in virtual classes with a web requirement expressed lower degrees of satisfaction
with the learning experience when compared with those in courses without a web
requirement. When geographic location is controlled, separating the data into urban and
non-urban settings, these findings tell us more. Specifically, students attending classes
with a web requirement in urban settings (St. Louis and Kansas City) were more likely to
express positive degrees of satisfaction than students attending classes with a web
requirement in non-urban settings (St. Joseph, Delta, Rolla, Joplin, Jefferson County,
Poplar Bluff).
Interactivity in Distance Learning
November 1999
1
Introduction
A distinction is traditionally made between education studies and distance education
studies. Such distinctions have been taken for granted largely because educational studies
were based on co-present teaching with face-to-face interaction between participants.
Alternatively, distance education studies generally treated access itself as a preeminent
feature of such classes. In other words, the constraints of time and space have determined
the boundaries of approaches to the study of distance learning, i.e. issues of access.
Whether students could even participate in specific curricula was by default deemed
equally important to developing and implementing models of quality in the learning
process.
Today, with on-going technological advances and adaptation by educational institutions,
traditional courses are increasingly offered as virtual classes rather than traditional
distance education classes. Distance learning students now often have the ability to
communicate with other sites utilizing such media channels as satellite networks, email,
telephone, fax, mail, Internet, world wide web and collaborative network applications, as
well as both broadcast and interactive video in both its desktop and studio forms
(Heldman, 1993; Holmberg, 1977; Shrestha & Sutphin, 1995). Whereas, even in the
recent past, the number of communication channels available tended to favor the host
site, today it is common for remote sites to also have a multitude of channels available
(Barker, Frisbie & Patrick, 1989). These changes have more than technological
implications.
Virtual classes are increasingly a part of the traditional course curriculum, rather than
limited to on-going or adult education. Stanford’s approach to on-line education
(http://stanford-online.stanford.edu/) is just one of many universities offering multimedia
Interactivity in Distance Learning
November 1999
2
courses via the internet. Indeed, the University of Chicago, Columbia University,
Stanford University, the London School of Economics and Political Science, and
Carnegie Mellon University are all members of the Cardean Academic Consortium.
Cardean members work to develop high quality online business education
(http://www.unext.com/whoweare/academicalliances.asp). These developments in the
institutional bases of virtual classes make it important to study distance learning classes
not only from an access perspective, but also from an interactivity perspective, and a
concern for the quality of the learning process. Recognition is slowly developing that the
constraints of time and space are no longer as determinant in distinguishing distance from
co-present learning. Like it or not, the challenge for a virtual class is in measuring up to
the interactive richness, albeit in different ways, of even a lecture hall course
characterized by co-presence.
Students who are not satisfied with the learning experience or the learning outcome will
think twice before signing up for additional distance learning classes.
The importance of students taking more than their first distance learning class becomes
apparent once one stops thinking only in terms of access. When students at one
university have the option of taking a co-present class or taking the same class via the
network from another university, a condition increasingly common within and, relatively
soon, across university systems, the significance of interactivity to such virtual classes
increases.1 The same point becomes even more relevant once universities from different
state systems, or private institutions, begin to compete for online education students. We
are not here referring to “mail order courses” but, rather of curriculum offered by
established and, in some instances “elite,” institutions, like those mentioned in the
previous paragraph. This trend in higher education is obviously not limited to “elite”
institutions. The University of Missouri in general, and UMSL in particular, has already
indicated a serious institutional commitment to developing such curriculum.
Interactivity in Distance Learning
November 1999
3
Comparing traditional distance education classes with virtual classes was not a salient
issue for distance education research as long as educators assumed that learning at a
distance was different from traditional learning in both student populations as well as
goals. But, this assumption of difference is increasingly open to challenge as more
technologies become available to deliver learning at a distance, and provide an increasing
capacity for students to influence the form or content of the distance learning
environment -- a capacity referred to here, following Steuer (1992), as interactivity.
One outcome of all these technological advances has been a closer look at how to study
distance learning. Research on distance learning has converged on the point that no
statistically significant differences exist in outcome measures (test scores, attendance,
etc.) between delivering education at a distance and delivering education face to face in a
classroom situation (Verduin and Clark 1991). Studies however are mixed in whether
students, adult or young, prefer classroom co-presence (Johnstone 1991; Phipps and
Merisotis 1999).
Obviously, more research is needed on how distant or virtual classes are measuring up to
traditional co-present classes. A recent report sponsored the American Federation of
Teachers and the National Education Association provides a meta-analysis of recent
research on distance education. Phipps and Merisotis (1999) argue that several gaps exist
in the current research, including:
1. The research has tended to emphasize student outcomes for individual courses
rather than for a total academic program.
2. The research does not take into account differences among students
3. The research does not adequately explain why the drop-out rates of distance
learners are higher.
4. The research does not take into consideration how the different learning styles of
students relate to the use of particular technologies.
Interactivity in Distance Learning
November 1999
4
5. The research focuses mostly on the impact of individual technologies rather than
on the interaction of multiple technologies.
6. The research does not include a theoretical or conceptual framework.
7. The research does not adequately address the effectiveness of “digital libraries”
(Phipps and Merisotis 1999).
The current research study presents findings relevant to points two, five, and six of this
list.
Relative to taking into account differences among students, we not only look for
differences between student perceptions of satisfaction for host and remote sites, but also
differences between students at what we here refer to as urban sites (UMKC/UMSL) and
non-urban sites. Our rationale for this approach comes from the recognition that all
remote sites may not be equal in the public access to computer and network resources.
For example, a remote student at UMKC has readier access to all the research and
computing facilities of an urban university. Whereas, a remote student at Poplar Bluff or
St. Joseph may have access to the course, but not ready access to the whole range of
technological resources available to the urban student. Again, drawing on the lead of
Phipps and Merisotis (1999), our study focuses on the impact of multiple technologies
and uses an explicit conceptual framework, Steuer’s (1992) conceptual model of
telepresence, to study the way synchronic and asynchronic communication technologies
relate to the satisfaction of students with the learning experience.
Focusing on issues of telepresence contrasts sharply with the traditional focus on
synchronic access alone, such as video networks (Steuer 1992), since it provides a
conceptual approach that takes synchronic and asynchronic communication technologies
into account. Advocates of synchronous communication technologies such as interactive,
network video typically maintain that the mere fact students have access to such classes
differentiates them from traditional classes. Thus, the mere fact that a class is offered
Interactivity in Distance Learning
November 1999
5
within driving distance of the student’s home or residence is taken to mean that access
issues are moot. The position, however, overlooks well known disparities between
students at remote sites and those at host sites where the instructor is located. Similarly,
to date, advocates of asynchronous communication technologies such as web-based
courses argue that access (the ability of students to access content from most anywhere at
any time of day) is a key differentiation between those courses and traditional classes.
Here too, advocates sometimes overlook the differences in rates of connection, such as
home dial-up, cable modem, DSL services, for students, as well as the possibility of no
home connectivity. In other words, some web-based learners may depend mostly or
entirely on access to university or business settings for use of the internet. Differences in
individual access to asynchronic communication channels is an important factor in
assessing the relationship between interactivity and satisfaction with the virtual class.
Advocates of all types of distance learning typically focus on the abilities of these
technologies to overcome time and space constraints, rather than focus on the degree to
which implementations of such technologies adequately define a space of communication
for students in the course to work together with the instructor. Thus, we follow Steuer
(1992) in contending that neither of these two positions in isolation takes into account the
importance of vividness and interactivity to the learning situation in virtual classes.2 Nor
do these approaches speak to the practicalities of access to asynchronous technologies
such as the world wide web. We focus on both access and interactivity herein using
Steuer’s (1992) model of telepresence to assess the virtual class in distance learning.
Whether designers of virtual classes need to design for interactivity is a crucial question
that distance learning researchers must face. We do not pretend to pose this question
first. There are many scholars writing on curriculum and course design for computerbased learning whether delivered to the desktop via CD ROM, local area networks, the
6
Interactivity in Distance Learning
November 1999
Internet, or all three. Less study has been done however on the network interface of
virtual classes comprised of interactive video, two-way audio, and chat sessions, or in
other words, synchronic communication technology, and asynchronic communication
technologies such as web sites, discussion lists, e-mail, etc. Assuming that technologies
of distance learning classes need simply to “deliver” existing instructional materials
is too simplistic.3 The technologies used in a virtual class provide a space for
communication made available to learners by the network interface and the design of
courses. Following White (1999) we contend that the measure of quality for distance
learning “is a matter for individual students to decide” (1999). We offer a conceptual
model, a research strategy and a survey instrument to assess students’ perceived
satisfaction with distance learning classes.
Conceptual Model
The technological ideal of virtual classes involves building learning environments that
immerse students in the same learning situation across several network locations. A key
to recognizing such futuristic conceptions of the virtual class lies in making networks
transparent to the learning situation. But, what does it mean to describe a network as
“transparent”?4 In its ideal configuration, the goal of transparency leads to a learning
experience with similar features to the holodeck, made famous in the science fiction
series “Star Trek: The Next Generation,” in which people are virtually present one to the
other (Tiftin 1997, 1).5 Indeed, projects such as the CAVE Research Network already
provide working models of network interfaces that approach the telepresence ideal of
transparency in which vividness and interactivity are both highly present, though with the
aid of goggles and other peripheral technologies (see
http://www.evl.uic.edu/cavern/vrserver.html ).6 This ideal network interface has not been
implemented except in highly delimited domains in research and development labs. It
Interactivity in Distance Learning
November 1999
7
does provide a measure of how well current technological configurations support
transparency in network interfaces.
We draw on Steuer (1992) to conceptualize the relationships between the transparent
ideal and the more expedient combination of technologies that already exist to support
virtual classes. Steuer conceptualizes the degree to which a network interface achieves
transparency as telepresence, or “ the extent to which one feels present in the mediated
environment, rather than in the immediate physical environment” (1992, 75). In his
formulation, telepresence and, by implication transparency, requires a high degree of
vividness and interactivity in the technology interface (Steuer 1992). “The first,
vividness, refers to the ability of a technology to produce a sensorially rich mediated
environment. The second, interactivity, refers to the degree to which users of a medium
can influence the form or content of the mediated environment” (Steuer, 1992, p. 80). As
Borgmann recently observed, “Transparency seems to be the perfection of information
about reality,” (1999, 168).
Whether avatars representing people in a virtual class will reach the point of the holodeck
is certainly an open question, with its own set of interesting social, communication, and
technological implications. In some ways it borders on technological determinism since,
even though the technology may or may not develop, it is many times presented as
inevitable (Leyshon and Thrift 1997, 326).7 But, in the near term, to the extent that the
network interface fails to achieve transparency in relation to the learning situation, as in
the virtual classes of today and the near future, the learning situation is constrained by a
network interface that faculty and students themselves orient to and manage as an
obtrusive technology.
Interactivity in Distance Learning
November 1999
8
Instead of a transparent interface rich in vividness and interactivity, learning situations
today consist largely of expedient mixes of synchronic communication technologies
(interactive video networks) and asynchronic communication technologies (web sites
with streaming media, graphic presentations, discussion lists, etc.). Telepresence
provides a conceptual model for explaining the relation of participant immersion in the
learning situation of virtual classes to proximate perceptions of co-presence. We use
Steuer’s model to operationalize the degree of interactivity embedded in the design of
classes using synchronous and asynchronous communication technologies. We do not
operationalize vividness in this study since the interactive video network used in each
course remains virtually constant in design and delivery with only audio controls varying
from studio to studio.
The Study
The research reported herein studied the relative success of virtual classes in producing
positive student perceptions of co-presence in learning situations mediated by
technologies of telepresence. A previous research study (Jung, Keel, and Irons 1998)
tested whether making asynchronous communication channels, such as web sites,
available for students increases the degree of satisfaction with the overall learning
situation. In that study we found the mere availability of a class web site increases
student satisfaction with the learning situation even if the asynchronous communication
technologies of the web are not integrated into the class as interactive class requirements.
In other words, the mere fact that a web site existed for the class increased student
satisfaction even when no requirement existed for students to use the web for specific
communication purposes. Thus, our previous findings speak to the fifth point raised by
Phipps and Merisotis (1999), that the extant research on distance learning has failed to
consider the interaction of multiple technologies and, rather, focused largely on the
impacts of one technology or another.
Interactivity in Distance Learning
November 1999
9
The current research compares student satisfaction within classes with no required web
component to student satisfaction within classes which merely publish class materials on
a web site (e.g. course syllabus, assignments). Furthermore, each of these classes is
compared to classes that are designed to allow such publication of materials, but also
integrate new forms of virtual interactivity (e.g. chat rooms, self-paced or knowledgebased navigational instruction) and require students to engage these resources as a course
requirement. The analysis is done while taking into account design issues as they relate
to student satisfaction with virtual classes. Table 1 outlines five of six possible data
relationships examined in this study.
Table 1
Virtual Class Type A
Interactive video
Synchronic
Asynchronic
+
*
Virtual Class Type B
Interactive video + web
publishing
+
+
Virtual Class Type C
Interactive video + web
publishing/virtual
interaction
+
+
* Asynchronic communication channels are used in any instance of distance education. These channels are
defined by technologies such as faxes, delivery services, etc. The current analysis focuses solely on those
asynchronic technologies that can embed interactivity into the communication.
Our research hypothesis for testing relations between the independent variable level of
design and the dependent variable interactivity predicts that,
The level of interactivity produced by the design of a virtual class increases
student satisfaction with the learning experience.
The variable of interactivity is operationalized according to the level of design included in
the class as distinguished by Table 1. Thus, we predict a higher student satisfaction for
classes as additional channels of interactivity are designed into the class (i.e. classes in
Virtual Class Type A compared to classes in Virtual Class Type B). We further predict
Interactivity in Distance Learning
November 1999
10
higher student satisfaction as asynchronic communication technologies such as the world
wide web are integrated into the course design rather than simply made available (i.e.
classes in Virtual Class Type B compared to classes in Virtual Class Type C).
Methods
We use two methods: 1) a survey on student satisfaction with the learning situation, 2)
field research that includes observations in the virtual classroom. The questionnaire was
developed to gather data to measure the dependent variable of interactivity in relation to
the independent variable of level of design.
Questionnaires
Questionnaires were distributed to the professors to pass out in each class location. A
cover sheet asked the students to volunteer an anonymous assessment of the virtual
class. Each student’s questionnaire, whether they chose to complete it or not, was
handed back during class in a sealed envelope. Each professor then forwarded the
questionnaires to the researchers.
The questionnaire (see Appendix A) for the current study consisted of 23 items, with
18 on a seven point Likert scale, four “yes/no” items, and one item to determine
gender. The Likert items asked students to indicate their agreement on a seven point
scale ranging from strongly agree (1) to strongly disagree (7). A general Comments
section was provided at the end of the questionnaire with a specific Comments section
provided for Question 18 which read: “It was difficult to get the professor’s attention
during class when it was needed.”
Interactivity in Distance Learning
November 1999
11
Observations
Each researcher observed two classes in the ITC in St. Louis. Observations included
a pre-class informal interview with the professor along with sitting through the class
to take note of the class and network dynamics.
Virtual Classes and Course Locations
The research focused on student’s perception of satisfaction with the learning experience
in 7 distinct virtual classes. Each virtual class included course offerings from multiple
universities, 19 accredited in courses at 8 locations, 2 urban (UMKC/UMSL) and 6 nonurban (St. Joseph, Joplin, Delta Center, Jefferson County, Rolla and Poplar Bluff). A
majority of the students (144) were located near an urban campus (UMSL and UMKC)
and the remaining students (51) accessed the other, non-urban facilities.
Response Rate
197 out of 273 surveys distributed for this study were returned. The response rate of this
anonymous questionnaire therefore was approximated 72.16%, which both Moser (1972)
and Alreck and Settle (1995) report as being a more than adequate response rate for mail
questionnaires.
Data Analysis
The survey instrument was designed to measure student perceptions of satisfaction
with the learning situation in virtual classes. A previous study (Jung, Keel, and Irons
1998) reported the following finding.
students do perceive a benefit from courses using web technologies to
augment the interactive video medium in virtual classes. Web technologies
affect the students’ perception of telepresence. This conclusion is
strengthened by the fact that, of the classes studied, none embedded the use of
web sites, discussion lists, or e-mail into the curriculum design itself. Yet,
even with this minimal use, students still perceive a benefit in their access to
Interactivity in Distance Learning
November 1999
12
the teacher. This is especially the case with students who previously used the
technologies (1998, p.28).
These previous findings did indicate support for the predictive relationships outlined
between Virtual Class Type A and Virtual Class Type B when communication
technologies (synchronic and asynchronic) are controlled. Our current analysis of the
data collected to examine the same predictions for relationships outlined between
Virtual Class Type B and Virtual Class Type C found statistical support for only one
item measuring interactivity. Thus, we did not uniformly find higher student
satisfaction as asynchronic communication technologies such as the world wide web
were integrated into the course design rather than simply made available.
Specifically, student responses to Question 18 (“It was difficult to get the professor’s
attention during class when it was needed.”) occurred in the direction predicted
(Table 2).
Responses to question 18 revealed an interesting pattern. Students in classes with a web
requirement are significantly more likely to disagree with the statement when compared
to students in classes without the web requirement. Thus, students in classes with a web
requirement perceived it to be easier to get the professor’s attention.
Table 2
Tests of Between-Subjects Effects
Question 18: “It was difficult to get the professor’s attention during class when it was
needed.”
Source
Type III Sum
df
Mean
F
Sig.
of Squares
Square
Corrected Model
132.776(a)
3
44.259
10.318
.000
Intercept
3777.647
1
Web Requirement
79.181
1
Host
29.124
1
Web Requirement * Host
3.897E-02
1
Error
802.156
187
Total
4916.000
191
Corrected Total
934.932
190
a R Squared = .142 (Adjusted R Squared = .128)
Interactivity in Distance Learning
November 1999
3777.647
79.181
29.124
3.897E-02
4.290
880.651
18.459
6.789
.009
.000
.000
.010
.924
13
Table 3: Cell Means for Table 2
Descriptive Statistics
Question 18: “It was difficult to get the professor’s attention during class when it was
needed.”
Web Requirement
Host
Mean
Std. Deviation
N
yes
yes
6.12
1.92
25
no
5.28
1.56
36
Total
5.62
1.75
61
no
yes
4.71
2.08
38
no
3.80
2.27
92
Total
4.07
2.25
130
Total
yes
5.27
2.12
63
no
4.22
2.19
128
Total
4.57
2.22
191
Additionally, students at remote sites are more likely to agree with the statement in
Question 18 regardless of whether a web requirement is part of the course (Table 3). No
interactions between the variables (web requirement or location) are statistically
significant. Consider the following representative comments to question 18 (“It was
difficult to get the professor’s attention during class when it was needed.”):
Table 4: Comments to question 18
Site
Host
Comment
“Raised hand, pick up microphone.”
“Speak out, wave hand”
We had to wave down the person running the audio
because we were always muted, this made it difficult to
Remote
interact.
By the time the professor knows you want to talk the
discussion usually changed subjects.
The statistical findings shown in Table 2 are bolstered by the comments of students to
Question 18. Students at remote sites indicate a lower degree of satisfaction with their
ability to get the professor’s attention, regardless of whether a web requirement is used in
Interactivity in Distance Learning
November 1999
14
the course. This finding points to a contradiction in one of our starting premises, that
issues of access are not salient to research on interactivity.
We assumed that the interactive video space produced by the synchronic communication
technology (i.e. the interactive video network) was equally accessible to host and remote
students regardless of their use of the world wide web. Yet, increasing the level of
interactivity in a course by requiring web use as part of the course design (i.e. increasing
interactivity through design) introduces another dimension to the access issue.
Our current data point to access as a multidimensional variable in that students not only
require access to the media space opened by the interactive video network , but also
require access to the web, or the internet, when a virtual class integrates use of the web
with the course design. Thus, student perceptions of interactivity are affected by this
latter dimension of access. For example, when we examine student responses to question
11 (“Access to this class was more convenient than access to the same class would
usually be for me.”) an interesting pattern is seen (Table 5). Students enrolled in classes
that integrate the web into the course as a required component view the class as less
accessible than do students enrolled in classes where they are not required to use web
resources, even though the web may be employed by the teacher to present syllabus and
other related information (Table 6).
Interactivity in Distance Learning
November 1999
15
Table 5
Tests of Between-Subjects Effects
Question 11: “Access to this class was more convenient than access to the same class would usually be for
me.”
Source
Type III Sum of
df Mean Square
F
Sig.
Squares
53.798(a)
3
17.933
4.537
.004
Corrected Model
2400.769
1
2400.769 607.386
.000
Intercept
30.825
1
30.825
7.799
.006
Web Requirement
1.186
1
1.186
.300
.585
Host
5.635
1
5.635
1.426
.234
Web Requirement * Host
754.951
191
3.953
Error
3482.000 195
Total
808.749 194
Corrected Total
a R Squared = .067 (Adjusted R Squared = .052)
Table 6: Cell Means for Table 5
Descriptive Statistics
Question 11: “Access to this class was more convenient than access to the same class would usually be for
me.”
Web Requirement
Host
Mean
Std. Deviation
N
4.28
2.11
25
yes
yes
4.49
1.82
37
no
4.40
1.93
62
Total
3.77
2.07
39
no
yes
3.21
1.98
94
no
3.38
2.02
133
Total
3.97
2.09
64
Total
yes
3.57
2.02
131
no
3.70
2.04
195
Total
When we examine the likelihood that a student will choose to take a virtual class again,
the data show that the web requirement and location are the most significant predictors of
choosing to take another course. Student responses on Question 15 (“I would not choose
to take another class that uses interactive video.”) are most likely to agree when they are
in classes at remote sites with a web requirement designed into the course (Table 7). This
finding is anomalous to the patterns predicted by the model in Table 1. Increased levels
of interactivity in a course that result from increased levels of design do not predict the
likelihood of a student agreeing with Question 15. Rather, a web requirement combined
16
Interactivity in Distance Learning
November 1999
with a remote location is most predictive (Table 8). This finding led us to reconsider the
way we conceptualize access.
Table 7
Tests of Between-Subjects Effects
Question 15: “I would not choose to take another class that uses interactive video.”
Source
Type III Sum of Squares df Mean Square
F
77.561(a)
3
25.854
5.880
Corrected Model
3315.836
1
3315.836 754.184
Intercept
22.195
1
22.195
5.048
Web Requirement
2.132
1
2.132
.485
Host
24.198
1
24.198
5.504
Web Requirement * Host
826.558 188
4.397
Error
5575.000 192
Total
904.120 191
Corrected Total
a R Squared = .086 (Adjusted R Squared = .071)
Sig.
.001
.000
.026
.487
.020
Table 8: Cell Means for Table 7
Descriptive Statistics
Question 15: “I would not choose to take another class that uses interactive video.”
Web Requirement
Host
Mean
Std. Deviation
4.56
2.35
yes
yes
4.00
2.29
no
4.23
2.31
Total
4.53
2.41
no
yes
5.56
1.79
no
5.26
2.04
Total
4.54
2.37
Total
yes
5.12
2.06
no
4.93
2.18
Total
N
25
36
61
38
93
131
63
129
192
The multidimensional attributes of access made it important to reconsider the way
location is operationalized. We originally looked at access in terms of host/remote issues
which are no doubt crucial. Yet, when we consider access to the world wide web issues
of geographical location become salient to the study. To explore these issues we decided
to break location down into those University of Missouri sites in St. Louis and Kansas
City and those sites outside these two campus locations. This breaks down in general
terms into urban sites and non-urban sites. Our assumption is that access to the internet is
Interactivity in Distance Learning
November 1999
17
more readily available in these urban campuses and residences than in the non-urban
settings.
Table 9
Tests of Between-Subjects Effects
Question 11: “Access to this class was more convenient than access to the same class would
usually be for me.”
Source
Type III
Sum of
Squares
Corrected Model
154.659(a)
3
51.553
15.054
.000
1076.681
1
1076.681
314.401
.000
42.836
1
42.836
12.509
.001
9.447
1
9.447
2.759
.098
26.141
1
26.141
7.633
.006
Error
654.089
19
1
3.425
Total
3482.000
19
5
808.749
19
4
Intercept
Web Requirement
Urban
Web Requirement * Urban
Corrected Total
df
Mean
Square
F
Sig.
a R Squared = .191 (Adjusted R Squared = .179)
Table 10: Cell Means for Table 9
Descriptive Statistics
Question 11: “Access to this class was more convenient than access to the same class would
usually be for me.”
Web Requirement
Urban
Mean
Std. Deviation
N
4.36
1.90
56
yes
yes
4.83
2.32
6
no
4.40
1.93
62
Total
4.02
1.91
88
no
yes
2.11
1.60
45
no
3.38
2.02
133
Total
4.15
1.90
144
Total
yes
2.43
1.89
51
no
3.70
2.04
195
Total
Interactivity in Distance Learning
November 1999
18
Responses to Question 11 indicate that although the web requirement or level of design is
the most predictive variable relating to the question of access, the combination of the
urban (STL or KC) variable with the web requirement is predictive at the .006 level
(Table 9).
The relationships between level of design and geographical location are further
highlighted in the responses to Question 22. Students in classes with the web
requirement are significantly more likely to agree with the statement when compared to
students without a web requirement as part of the course. Students attending at locations
other than STL/KC whose course requires them to use the web are statistically more
likely to agree with the statement in Question 22 (“I would not recommend any
interactive video class to other students.”). So, students with these attributes are less
likely to recommend such courses (Table 11).
Table 11
Tests of Between-Subjects Effects
Question 22: “I would not recommend any interactive video class to other students.”
Source
Type III
Sum of
Squares
Corrected Model
79.793(a)
3
26.598
7.358
.000
Intercept
1312.101
1
1312.101
362.998
.000
42.027
1
42.027
11.627
.001
1.387E-03
1
1.387E-03
.000
.984
17.770
1
17.770
4.916
.028
Error
675.935
187
3.615
Total
5284.000
191
755.728
190
Web Requirement
Urban
Web Requirement * Urban
Corrected Total
df
Mean Square
F
Sig.
a R Squared = .106 (Adjusted R Squared = .091)
Interactivity in Distance Learning
November 1999
19
Table 12: Cell means for Table 11
Descriptive Statistics
Question 22: “I would not recommend any interactive video class to other students.”
Web Requirement
Urban
Mean
Std. Deviation
N
4.27
2.25
56
yes
yes
3.20
2.68
5
no
4.18
2.28
61
Total
4.84
1.83
86
no
yes
5.89
1.38
44
no
5.19
1.76
130
Total
4.61
2.02
142
Total
yes
5.61
1.73
49
no
4.87
1.99
191
Total
We tentatively conclude that students at locations other than STL/KC appreciate access to
the class per se. Their positive assessment of the learning experience is diminished when
a requirement to use the web is added to the course. We speculate that this pattern holds
because access to the web in those locations (other than STL/KC) is not as readily
available. On the other hand, students in locations with ready access to the web (STL/KC)
in courses with a web requirement are more likely to disagree with Question 22 regardless
of whether they are host or remote students.
Student responses to Question 7 (“The web site and electronic discussion group
contributed significantly to my learning the course content.”) indicate that students
enrolled in courses with a web requirement are statistically more likely (p = .057) to agree
than students enrolled in courses without a web requirement (Table 13). The relationship
holds regardless of location.
Interactivity in Distance Learning
November 1999
20
Table 13
Tests of Between-Subjects Effects
Question 7: “The web site and electronic discussion group contributed significantly to my learning
the course content.”
Source
Type III Sum of Squares
df
Mean
F
Sig.
Square
27.964(a)
5
5.593
.965
.440
Corrected Model
646.824
1
646.824
111.635
.000
Intercept
21.301
1
21.301
3.676
.057
Web Requirement
4.089
1
4.089
.706
.402
Host
2.989
1
2.989
.516
.473
Urban
1.686
1
1.686
.291
.590
Web Requirement*Host
12.524
1
12.524
2.162
.143
Web
Requirement*Urban
1095.082 189
5.794
Error
2737.000 195
Total
1123.046 194
Corrected Total
R Squared = .025 (Adjusted R Squared = -.001)
Table 14: Cell Means for Table 13
Descriptive Statistics
web site and electronic discussion group
contributed significantly to my learning the course content.”
Question 7: “The
Web Requirement
Host
yes
Yes
no
Total
no
yes
no
Total
Total
yes
no
Total
Interactivity in Distance Learning
November 1999
Urban
yes
Total
yes
no
Total
yes
no
Total
yes
Total
yes
no
Total
yes
no
Total
yes
Total
yes
no
Total
yes
no
Total
Mean
Std. Deviation
2.75
2.75
2.63
1.33
2.42
2.68
1.33
2.55
3.28
3.28
2.71
3.15
2.93
2.97
3.15
3.03
3.08
3.08
2.67
2.94
2.78
2.85
2.94
2.88
1.92
1.92
2.08
.52
1.97
1.99
.52
1.94
3.09
3.09
2.46
2.26
2.36
2.76
2.26
2.59
2.70
2.70
2.30
2.21
2.26
2.48
2.21
2.41
N
24
24
32
6
38
56
6
62
39
39
48
46
94
87
46
133
63
63
80
52
132
143
52
195
21
Thus, students who are required to use the web, regardless of location are statistically
more likely to agree with Question 7. Students who are not required to use the web, but
have course content available from the web on a voluntary basis, are statistically less
likely to agree with Question 7 (Table 14). These relationships hold regardless of
host/remote or location.
Students who will not recommend the class to others (see Question 22 discussion)
nevertheless recognize the importance to learning that the web requirement holds (see
Question 7 discussion). We speculate that their appreciation for the contribution of a
web requirement to learning class content points to the salience of design for positive
perceptions of the learning experience rather than the learning situation per se. Even
students in STL/KC, where access to the web is less problematic, express less willingness
to take another interactive video course but agree that using the web contributes to
learning course content.
Conclusions
Our most interesting specific finding relates to the degree of satisfaction expressed by
students in courses that include a web requirement compared to those students in courses
without a web requirement. Overall, students in courses with a web requirement
expressed lower degrees of satisfaction with the learning experience when compared to
those in courses without a web requirement. However, when we control for geographic
location, separating the data into urban and non-urban settings, these findings tell us
more. Specifically, students attending classes with a web requirement in urban settings
(St. Louis and Kansas City) were more likely to express positive degrees of satisfaction
than students attending classes with a web requirement in non-urban settings (St. Joseph,
Delta, Rolla, Joplin, Jefferson County, Poplar Bluff).
Interactivity in Distance Learning
November 1999
22
Our findings are also relevant to a more general discussion. Because this study:
(1) takes into account differences among students, in particular differences among urban
and non-urban, (2) focuses on the interaction of multiple technologies, and (3) is guided
by the conceptual framework of telepresence, we have begun to fill in what Phipps and
Merisotis (1999) identify as significant gaps in the research and important flaws in the
methodology of technology-based distance education research. The following question is
increasingly important: “Is distance learning in higher education on par with traditional
classroom-based instruction?”
The term “distance learning” is an evolving one but lacks specificity. It can involve a
wide variety of media from interactive video to Internet and e-mail-based technology.
While the term may lack specificity, one thing is clear. Increasing numbers of colleges
and universities are using distance learning as a significant component of their
educational programs. As previously noted, students who are not satisfied with the
learning experience as well as the learning outcome will think twice before signing up for
additional distance learning classes. Universities therefore need to seriously focus on
more than providing the network, the technological infrastructure, and course content.
System planners and curriculum designers need to begin a serious research program to
examine the way networks, the technological infrastructure, and course content interact in
demarcating a learning environment for virtual classes.
Universities in general, and the University of Missouri system members particularly, must
begin questioning the range of skills required to use the technology and participate in the
flexible learning environment made possible by uses of synchronic and asynchronic
network connections. Indeed, distance learning networks that integrate the synchronic
and asynchronic channels of communication into virtual classes will prevail in the
emerging marketplace where universities compete for students within states, across the
23
Interactivity in Distance Learning
November 1999
nation, and internationally. Universities that make the design choice to minimize the
obtrusiveness of their learning networks’ will lead. Curriculum design must explicitly
consider the interactivity supported by the design of communication channels in a virtual
class as well as the differential access of students to those channels.
Students appreciate the interactivity of virtual classes that include a web component. But,
to the degree that use of the web component is a part of the course requirements, their
satisfaction with the class decreases. This is particularly the case for non-urban students.
A number of possible explanations for this pattern come to mind, none of which is
sufficient without more detailed data on individual access to network resources. Students
at urban universities are advantaged in virtual classes in their individual access to
network resources, specifically dial-up access as well as residential broadband access to
the internet is more widely distributed in urban areas. Furthermore, for dial-up internet
users, urban students are less likely to face as many telephony costs such as long distance
charges when compared to students in non-urban areas. Thus, it makes sense that urban
students would not find access to web resources needed in a course as burdensome as
non-urban students. We conclude that our data point to at least one basic research need in
the design and delivery of virtual classes offered by the University of Missouri–St. Louis.
The degree of variation of access to asynchronic communication resources such as the
web, e-mail, etc. between urban and non-urban students needs to be assessed by a focused
research effort.
Interactivity in Distance Learning
November 1999
24
References
Alreck, P.L., & Settle, R.B. (1995). The survey research handbook. NY: Irwin
Professional Publishing.
Barker, B. O., Frisbie, A. G., and Patrick, K. R. (1989). Broadening the definition of
distance education in light of the new telecommunications technologies. The American
Journal of Distance Education, 3, 20-29.
Borgmann, A. (1999) Holding On to Reality: The Nature of Information at the Turn of
the Millennium Chicago: The University of Chicago Press.
Fulkerth, B. (1998) “A Bridge for Distance Education: Planning for the Information- age
Student,” Syllabus vol. 12, no. 4, pp. 28-30, 71.
Heldman, R. K. (1993). Future telecommunications. Washington, DC: McGraw-Hill, Inc.
Holmberg, B. (1977). Distance education. NY: Nichols Publishing Co.
Holmberg, B. (1981). Status and trends of distance education. NY: Nichols Publishing
Co.
Johnstone, S. M. (1991) "Research on Telecommunicated Learning: Past, Present, and
Future," ANNALS of the American Academy of Political and Social Science vol. 51, no.
4, pp. 49-57.
Jung, D. J. & Irons, L. R. (1995) Analysis of Interactivity in Distance Education: The
Missouri IVPTF Experiment Report submitted to the Interactive Video Programming
Task Force of the Missouri Public Service Commission and State of Missouri Department
of Elementary and Secondary Education.
Jung, D. J., Keel, R. O. & Irons, L. R. (1998) Interactivity in Distance Education: A study
of Telepresence in University Virtual Classes,” International Conference on the Social
Impact of Information Technologies. St. Louis, Missouri. October 1998.
Leyshon, A. & Thrift, N. (1997) MoneySpace: Geographies of Monetary Transformation
London: Routledge.
Moser, C.A. (1972). Survey methods in social investigation. NY: Basic Books.
Roussos, M., Johnson, A., Moher, T., Leigh, J., Vasilakis, C., & Barnes, C. (1998)
“Learning and Building Together in an Immersive Virtual World,” Presence
25
Steuer, J. (1992) “Defining Virtual Reality: Dimensions Determining Telepresence,”
Journal of Communication. (Autumn) vol. 42, no. 4, pp. 73-93.
Tiffin, J. & Rajasingham, L. (1995) In Search of the Virtual Class: Education in an
Information Society London and New York: Routledge.
Verduin, J. R. & Clark, T.A. (1991) Distance Education. San Francisco: Jossey-Bass
Publishers.
URLs
Beller, Michal and Ehud Or (1998) “The Crossroads between Lifelong Learning and
Information Technology: A Challenge Facing Leading Universities,” Journal of
Computer Mediated Communication, vol. 4, no. 2.
See http://www.ascusc.org/jcmc/vol4/issue2/beller.html
Graziadei, William D., Sharon Gallagher, Ronald N. Brown, and Joseph Sasiadek
“Building Asynchronous and Synchronous Teaching-Learning Environments” located at
http://horizon.unc.edu/projects/monographs/CD/Technological_Tools/Graziadei.asp).
Phipps, Ronald and Jamie Merisotis (1999) “What’s the Difference? A Review of
Contemporary Research on the Effectiveness of Distance Learning in Higher Education,”
The Institute for Higher Education Policy. Available from
http://www.ihep.com/PR15.htm.
Tiffin, John (1997) “The Virtual Class: Enhancing Learning in an Information Society,”
Keynote Address – The OTFE/OTS Conference, located at
http://www.tafe.lib/rmit/edu.au/ots/nlt/proceed/thevir.html
White, Frank (1999) “Digital Diploma Mills: A Dissenting Voice,” First Monday issue 4,
no. 7 http://firstmonday.org/issue/issue4_7/white/index.html
26
Endnotes
1
Indeed, Stanford offers an online MSEE degree program focusing on
telecommunications with two different credit options. It offers an Honor’s Cooperative
Program (HCP) that assigns status to online students comparable to on-campus students.
It also offers a Non-Degree Option (NDO) that admits online students on a course by
course basis rather than to the graduate program itself. “The NDO category is exclusive
to SCPD [Stanford Center for Professional Development] and is designed for students
who wish to upgrade their competency in a particular area without pursuing an advanced
degree,” see http://scpd.stanford.edu/ce/telecom/onlinedegree.html . Such offerings are
the first steps towards competition between universities for students registering in virtual
classes.
As Beller and Or note, “Technological advances have made synchronous (same time)
distance learning both viable and effective, primarily through video-conferencing and
satellite systems. Combining this with asynchronous Internet-based delivery makes it
possible to provide first-class teaching by excellent instructors to distant students while
maintaining interaction between instructor, students and peers. The technology allows the
same experts who prepared the learning materials also to take command of and guide the
learning process (unlike traditional distance teaching, where they were usually not
involved in the actual teaching),” (1998, pp. 3-4).
2
3
Needless to say, we vigorously disagree with scholars of distance learning like
Graziadei, Gallagher, Brown, and Sasiadek who contend that “media do not influence
learning under any conditions. The best current evidence is that media are mere vehicles
that deliver instruction but do not influence student achievement any more than the truck
that delivers our groceries causes changes in our nutrition,”
(http://horizon.unc.edu/projects/monographs/CD/Technological_Tools/Graziadei.asp).
Fulkerth summarizes this point noting that, “Our ongoing Distance Education
development challenge will be to continue to work toward creating student-centered,
technology-mediated learning communities in which the technology tools are so
seamlessly integrated as to be transparent,” (1998, p. 71).
4
Tiffin describes the evolution of such a class experience with the term HyperReality,
noting that it occurs “when, you telephone me in to this Conference as a virtual
person…that you see in three-dimensions and can even touch. Of course, it will be
obvious to begin with that virtual people are virtual people. They will look like animated
tailor’s dummies. But, as time goes by, as the superhighways come into place and
personal computing acquires real grunt it will become increasingly difficult to tell the
difference between people who are really present and people who are virtually present”
(1997, 1).
5
6
The NICE (Narrative Immersive Constructionist/Collaborative Environments) project is
done within the CAVE. As the CAVE website notes:
27
“CAVERN, the CAVE Research Network, is an alliance of industrial and research
institutions equipped with CAVEs, ImmersaDesks, and high-performance
computing resources all interconnected by high-speed networks to support
collaboration in design, training, scientific visualization, and computational
steering, in virtual reality,” see http://www.evl.uic.edu/cavern/vrserver.html
The NICE project has developed an exploratory learning environment for 6-10 year old
children. Wearing lightweight seteroglasses the children use a light-weight hand-held
device called a wand to manage the growth of a virtual garden (Roussos, Johnson, Moher,
Leigh, Vasilakis, and Barnes 1998)
http://www.ice.eecs.uic.edu/~nice/NICE/PAPERS/PRESENCE/presence.html
Leyshon and Thrift note that “Ironically, the real message of each of these
accounts…seems to be ‘inevitability’- not what the future might hold, but the inevitable
hold of the present over the future- what the future could not fail to see” (1997, 326).
7
28