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The Amer. Jrnl. of Distance Education, 26:34–49, 2012
Copyright © Taylor & Francis Group, LLC
ISSN 0892-3647 print / 1538-9286 online
DOI: 10.1080/08923647.2012.646089
Student Perceptions and Preferences for Tertiary
Online Courses: Does Prior High School Distance
Learning Make a Difference?
Dale Kirby
Memorial University of Newfoundland
Michael K. Barbour
Wayne State University
Dennis B. Sharpe
Memorial University of Newfoundland
Abstract: University students who had completed at least one distance education
course were surveyed during their first and fourth year of postsecondary studies. When
controlled for those who had previous distance education experience in high school, it
was found that self-regulatory learning behaviors, which are frequently linked to posi-
tive experiences and outcomes in online and distance education courses, were equally
apparent in all of the participating students regardless of whether they had previously
studied online. These findings suggest that high school students do not gain independent
learning skills and attitudes in an online environment regardless of what stakeholders,
administrators, teachers, parents, and even students themselves believe.
The purpose of this study was to examine the impact that experience with
online learning at the K–12 level had on students’ perceptions, attitudes, and
habits in online learning at the postsecondary level. In this article, the authors
examine the existing research on the nature of K–12 online learning with an
emphasis on the skills needed to be successful in that environment. Next,
they describe the methodology used and the results of our student survey, and
then they discuss the implications of the general lack of change in student
perceptions, attitudes, and habits for practitioners and future researchers.
Correspondence should be sent to Dale Kirby, Memorial University of
Newfoundland, G. A. Hickman Building, Office E-3043, St. John’s, NL A1B 3X8.
Canada. E-mail: dkirby@mun.ca
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STUDENT PERCEPTIONS AND PREFERENCES 35
LITERATURE REVIEW
The development of K–12 distance education and K–12 online learning in
Canada are consistent with its development in a number of other countries.
For example, online learning at the K–12 level has also grown exponentially in
the United States over the past two decades. First, district-based online learn-
ing programs and statewide virtual schools emerged in California, Utah, and
Florida in the early and mid-1990s (Barbour 2009). In one of the first national
surveys of K–12 online learning, Clark (2001) examined a total of 44 online
learning programs and estimated that there were approximately 40,000 to
50,000 secondary school students taking one or more online learning courses.
Less than a decade later, in their most recent Keeping Pace with K–12 Online
Learning report, Watson et al. (2010) reported significant K–12 online learn-
ing activity in 48 of the 50 states and that there were over 1,500,000 students
enrolled in online courses in the United States.
Although the practice of K–12 online learning has grown exponentially
over the past two decades, the availability of useful research to guide that
practice has been limited. Barbour and Reeves (2009) wrote that “there [had]
been a deficit of rigorous reviews of the literature related to virtual schools”
(402), whereas Rice (2006) lamented that “a paucity of research exists when
examining high school students enrolled in virtual schools, and the research
base is smaller still when the population of students is further narrowed to the
elementary grades” (430). In their examination of the open access literature,
Cavanaugh, Barbour, and Clark (2009) indicated that most literature related
to K–12 online learning was “based upon the personal experiences of those
involved in the practice of online learning” (5) and in particular based on the
experiences of online teachers, course designers, and administrators.
Another limitation of the existing research is the selective nature of the
students who have historically been represented in studies focused on K–
12 online learning. Haughey and Muirhead (1999) described the preferred
characteristics of students enrolled in K–12 online learning as highly moti-
vated, self-directed, self-disciplined, independent learners who could read and
write well and who also had a strong interest in or ability to use technology.
This description of high-ability students is consistent with descriptions pro-
vided by most of the research in this field (see Clark et al. 2002; Espinoza
et al. 1999; Kozma, Zucker, and Espinoza 1998; Roblyer and Elbaum 2000;
Watkins 2005, as examples and Barbour and Reeves 2009 for an overview of
this issue). Additionally, as Cavanaugh et al. (2004) have noted, “since adults
have progressed through these stages of cognitive development, delivery of
web-based education at the adult level need not concentrate on methods that
help the learner develop these cognitive skills” (7). Simply put, K–12 dis-
tance education—and K–12 online learning—has traditionally been designed
for higher ability students (Barbour 2009).
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36 KIRBY, BARBOUR, SHARPE
This has led some to question whether K–12 online learning is suitable for
students of all ability levels (Mulcahy 2002). However, one of the difficulties
posed by this concern is that some jurisdictions in the United States have
begun to require students to complete an online course to graduate from high
school (e.g., Michigan, New Mexico, Alabama, Florida, and Idaho). Even in
jurisdictions where online learning is not required, rural students often must
complete academic-level or advanced-level courses that are available only
online (Mulcahy, Dibbon, and Norberg 2008). In one recent study, Kirby and
Sharpe (2010) found that K–12 students who had completed these distance
courses were “over three times more likely to have completed a more academ-
ically rigorous program compared to those [who] did not” (86). This reality
has also led some to wonder if “distance education experience [has] a signifi-
cant effect on subsequent achievement and persistence behavior in university”
(Dodd et al. 2009, 19). This is particularly important given the claims made by
proponents of K–12 online learning that students need to learn in this way to
prepare themselves for future professions and lifelong learning opportunities
that will inevitably require facility with this medium (North American Council
for Online Learning and the Partnership for 21st Century Skills 2006).
To date there has been only a limited amount of research into effec-
tive course design and delivery in K–12 online learning environment
(Barbour 2005, 2007; Keeler and Anderson-Inman 2004a, 2004b; Murphy
and Rodriguez 2009; Murphy and Rodriguez-Manzanares 2009; Murphy,
Rodriguez-Manzanares, and Barbour 2011) and even less on the importance of
self-efficacy (Roblyer 2005, 2006; Roblyer et al. 2008; Roblyer and Marshall
2002–2003). Interestingly, the research into the self-efficacy of students in the
K–12 online learning environment has focused on the development of a pre-
diction instrument. The Educational Success Prediction Instrument (ESPRI)
was designed to identify students who might not have strengths in any of five
areas the researchers felt were important to success in the K–12 online learning
environment—for example, access to and expertise with computers, organi-
zation and self-regulation, beliefs about achievement, responsibility, and risk
taking (Roblyer and Marshall 2002–2003). However, the researchers later con-
cluded that a student’s grade point average was as good a predictor of student
success as the ESPRI (Roblyer et al. 2008). Clearly this is an area where more
research is needed before too many more jurisdictions make decisions about
requiring online learning based on claims of preparing students for their future
learning and work environments.
METHODOLOGY
Context
About 65 percent of public schools in the Canadian province of Newfoundland
and Labrador are located in settlements with five thousand or fewer residents
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STUDENT PERCEPTIONS AND PREFERENCES 37
and are considered “rural schools” (Newfoundland and Labrador 2010). With
a declining rural populace and coinciding smaller numbers of students in the
upper grades of high school, education authorities in the province have turned
to distance education in order to provide for a reasonably comprehensive ros-
ter of senior high school course offerings and address teacher recruitment and
retention issues that often challenge rural school staffing. As a result, a grow-
ing proportion of rural students in Newfoundland and Labrador are completing
some of their high school education through distance courses that utilize a
combination of synchronous and asynchronous online technologies.
Memorial University of Newfoundland also has a history of distance teach-
ing that dates back to the 1960s (Keough 1990). The university offered its first
Web-based distance education courses in the mid-1990s. Since that time, its
suite of online courses has grown to about four hundred (Memorial University
of Newfoundland 2011). For much of the history of K–12 online learning in
the province of Newfoundland and Labrador, both the K–12 program and the
university program have used the same course-management system. This set-
ting provides an ideal environment for studying the attitudes, perspectives, and
experiences of students educated in virtual school environments.
Sample and Participants
A total of 160 fourth-year undergraduate students at Memorial University of
Newfoundland comprised the sample for this research. Each of the students
in the sample signed up for and completed one or more online courses since
entering the university in 2006. All of these students were high school gradu-
ates of the Class of 2006 who participated in a survey of first-year university
students in 2007. The original sample of 369 students included all 162 first-
year students who had completed one or more distance courses at rural high
schools in Newfoundland and Labrador as well as 207 students randomly
selected from the remaining population of 485 first-year university students
who had attended rural schools in the province but had not completed high
school distance courses.
Of the 160 students in the sample, 127 were successfully contacted
and interviewed during the winter 2010 semester, for a response rate of
79.4 percent. Among those interviewed, 56 students (44.1 percent) had com-
pleted high school distance e-learning courses and the remaining 71 students
(55.9 percent) had not.
Instrumentation and Data Collection
The online survey instrument utilized for this research was designed to col-
lect information from students regarding their expectations and perceptions
of online distance education courses. The survey contained a number of
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38 KIRBY, BARBOUR, SHARPE
multi-item scales representing latent constructs. A list of the survey items
corresponding to each of these composite constructs is provided in the
Appendix. All the survey items utilized a four-point Likert-type multiple choice
response format with values of strongly agree, agree, disagree, and strongly
disagree.
Four items on the survey were designed to assess the self-regulatory
skills of students enrolled in distance education courses whereas another
twelve items measured students’ distance education self-efficacy. Both of these
multi-item survey components were adapted from an instrument designed by
Holcomb, King, and Brown (2004). Lower composite scores for these con-
structs reflect greater perceptions of self-regulation and distance education
self-efficacy.
Four constructs included in the survey, self-evaluation (four items), goal
setting (five items), environment structuring (four items), and time manage-
ment (three items), were adapted from Barnard, Paton, and Lan’s (2008) Online
Self-regulated Learning Questionnaire (OSLQ). Lower composite scores on
each of these dimensions are indicative of greater self-regulation in online
learning by students.
Seven further survey items, originally devised by House, Weldon, and
Wysocki (2007), assessed student expectations of their online distance edu-
cation by asking them to identify if they expected their online courses to be
more or less difficult compared with traditional courses. Lower scores for this
variable suggest that students expect that they will learn the same amount and
receive the same grade if they complete a course in an online format.
Another eleven-item scale included on the survey was created by Barnard,
Paton, and Rose (2007) to assess student perceptions of online course com-
munications and collaboration. Lower overall scores on this scale reflect more
positive perceptions toward online course communication and collaboration.
The final survey construct, satisfaction with distance education, was adapted
from a scale designed by Walker (2005). As with the previous variable, a lower
composite score is indicative of a higher level of satisfaction with distance edu-
cation courses whereas a higher score suggests a lower level of satisfaction with
this course delivery format.
Data Analysis
The data were analyzed using version 18 of the Statistical Package for Social
Sciences (SPSS). First, the reliability of each of the multi-item constructs
included on the survey was estimated using the Cronbach’s alpha coefficient of
reliability. Further analysis using logistic regression was carried out to compare
the scores on the composite variables for the group of students who completed
distance education courses in high school with the scores of the students who
did not.
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STUDENT PERCEPTIONS AND PREFERENCES 39
Results
Table 1 lists the mean scores and Cronbach’s alpha values for each of the
composite variables assessed in the survey. In each case, the Cronbach’s alpha
values for the latent constructs were .70 or better, indicating a high degree of
interitem reliability and an acceptable standard of agreement for this type of
survey research (Nunnally 1978).
The mean scores for each of the survey constructs were similar for stu-
dents who had high school distance course experience and those who did not
have high school distance course experience. Overall, the survey respondents
tended to perceive themselves as self-regulated learners. Their responses indi-
cated that they had a sense of self-efficaciousness (or competence) with regard
to their participation in distance education courses. Of the self-regulatory
behaviors assessed in the survey, the students most strongly agreed that they
tended to regulate their learning environments. However, they also agreed
that they proactively set goals for their learning in distance courses. They
Table 1. Mean Scores and Cronbach’s Alpha Values for Composite Variables
High school
distance course
experience
No high school
distance course
experience
MSDMSD
Self-regulation 1.97 0.40 1.94 0.35
α=.706
Distance education self-efficacy 2.16 0.45 2.19 0.40
α=.880
Self-evaluation 2.40 0.42 2.54 0.53
α=.724
Goal setting 2.03 0.53 2.02 0.52
α=.820
Environment structuring 1.76 0.53 1.81 0.52
α=.869
Time management 2.54 0.58 2.45 0.57
α=.710
Distance education expectations 2.68 0.47 2.63 0.47
α=.843
Perception of distance course
communication and collaboration
2.42 0.40 2.59 0.49
α=.858
Satisfaction with distance education 2.50 0.56 2.50 0.44
α=.910
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40 KIRBY, BARBOUR, SHARPE
were somewhat less likely to agree that they employed self-regulated learning
strategies such as self-evaluation and time management.
The overall mean score for the “distance education expectations” vari-
able was 2.65, which suggested that the students tended not to agree that
they would learn more or receive a higher grade in distance education courses
compared with courses delivered in the traditional face-to-face format. With
regard to students’ perception of distance course communication and col-
laboration, the overall score of 2.51 for this variable indicated that students
held a slightly negative view of communications and collaboration in distance
education courses. Further, a similar score of 2.50 for satisfaction with dis-
tance education suggested that the students who participated in the study were
somewhat dissatisfied with their distance education course experiences.
The results of the logistic regression are detailed in Table 2. These results
indicated that when the high school distance learners were compared with
the other university students who participated in the survey, there were no
significant differences between them on any of the measures.
DISCUSSION
With increasing numbers of students participating in online courses at all levels,
it becomes more important to understand the characteristics and perspectives
Table 2. Logistic Regression Results for Composite Variables Predicting Student
Participation in High School Distance Courses
Predictor variable βSE βpOdds ratio
Self-regulation −0.04 0.66 .95 0.96
Distance education
self-efficacy
0.92 0.88 .29 2.52
Self-evaluation −0.71 0.72 .33 0.49
Goal setting −0.30 0.61 .62 0.74
Environment structuring 0.28 0.51 .59 1.32
Time management 1.35 0.56 .20 3.84
Distance education
expectations
0.84 0.80 .30 2.31
Perception of distance course
communication and
collaboration
−0.83 0.70 .24 0.44
Satisfaction with distance
course communication and
collaboration
−1.43 0.87 .10 0.24
Constant −0.10 7.75 .96 0.91
Note: Nagelkerke R2=0.13. Model χ2(9) =36.8, p<.05.
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STUDENT PERCEPTIONS AND PREFERENCES 41
of the population of online learners. The information yielded may enable
educators to better engage online learners, provide them with more effec-
tive supports, and further grow online course enrollments to include a wider
audience (Barbour 2010b). Taken together, the findings of the current study
suggest that it is important not to draw conclusions about the perspectives and
preferences of students based on their prior participation in online learning.
Overall, the results indicate that the self-regulatory learning behaviors
that are frequently linked to positive experiences and outcomes in online and
distance education courses were equally apparent in all of the participating
university students regardless of whether they had previously studied online.
It is possible that, as was indicated in a previous study by Kirby et al. (2010),
secondary school students may report that they develop positive learner charac-
teristics through online education experience. However, we found no evidence
that high school online learners were advantaged or superior to other univer-
sity students in terms of their sense of self-efficacy in distance education or
their self-regulatory learning behaviors. This was consistent with the belief of
Roblyer et al. (2008) that a student’s prior academic performance is likely a
better indicator of the potential for success in the postsecondary environment
than prior distance education experience or measuring any of the individual
variables that contribute to why that student had been successful.
Further, the findings of the current study suggest that, despite their ear-
lier exposure to online learning, the attitudes and expectations of students who
participated in online learning in secondary school do not differ significantly
from those of students whose first encounter with online learning occurred in
the university setting. This is contrary to the claims made by proponents of
online learning at the secondary level (North American Council for Online
Learning and the Partnership for 21st Century Skills 2006). It is notable that
both groups held quite similar and somewhat negative views of distance educa-
tion in terms of their expectations and satisfaction. Similarly, both groups did
not view the quality of communication and collaboration in distance courses
as favorable. Evidently, willingness to repeat the online learning experience
at the postsecondary level should not necessarily be interpreted as a pref-
erence for this form of learning. This is consistent with Barbour’s (2010a)
claim that K–12 distance education in Canada is often seen as a substitute for
when face-to-face learning is not feasible. This perception of distance educa-
tion as a secondary or less preferred option may contribute to these negative
views.
CONCLUSIONS AND IMPLICATIONS
The absence of significant differences between the groups on any of the vari-
ables measured may be due to student experiences with distance education at
university level having a mediating effect on any impact that secondary school
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42 KIRBY, BARBOUR, SHARPE
experience with online learning might have had. It is also possible that students
who are attracted to and enroll in university-level studies hold similar views of
online and computer-mediated education already. Finally, it may have been
related to the fact that the postsecondary distance education was delivered in
a primarily asynchronous fashion, whereas the secondary distance education
program in Newfoundland and Labrador relies very strongly on a synchronous
component—almost to the point where students rarely use the asynchronous
course materials housed in the learning management system (Barbour and Hill
2011). Regardless of the rationale, these findings run counter to the belief that
students need or should be required to enroll in distance education experiences
while still in high school in order to prepare them for future distance education
studies.
The lack of differences between students who have had distance education
experience in high school and those who have not had experience with distance
education may be explained by the fact that the high school distance education
programs fail to develop these skills and behaviors—as has been suggested
by some of the participants from Johnson’s (2010) study. If this is indeed the
case, the creation of a Center for Distance Learning and Innovation (CDLI)
readiness course to help develop these skills in high school students may be
required to better prepare these students for distance education studies—as
suggested by Philpott, Sharpe, and Neville (2008). At the postsecondary level,
practitioners should be aware that prior high school distance education experi-
ence does not necessarily indicate that students are more prepared for distance
learning, that they have a greater affinity for it, or that they have more devel-
oped or superior skills in areas that tend to advantage distance learners (e.g.,
self-efficacy, self-regulatory behaviors). Additionally, as students in this study
were generally dissatisfied with the level of communication and collaboration
in their distance education courses, designers and teachers should consider
building in specific activities that encourage these behaviors. These activities
would ideally occur early in the course to create a positive experience and
potentially begin the development of a community of learners earlier in the
course.
Barbour (2010b) argued that research into K–12 distance education, like
many aspects of educational technology, has often focused on single, unique
settings or relied upon single data collection methods. One of the limitations
of this study is that it did focus on a single K–12 online learning program,
which is unique due to its heavy reliance upon synchronous delivery meth-
ods. This study also utilized surveys as the sole method of data collection,
which Marshall and Rossman (1999) posited “are of little value for examining
complex social relationships or intricate patterns of interaction” (131). Both of
these realities give rise to the need for this study to be replicated in other setting
along with additional data to be collected using methods designed to provide
a more complete understanding of the lack of statistical differences that were
found.
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STUDENT PERCEPTIONS AND PREFERENCES 43
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STUDENT PERCEPTIONS AND PREFERENCES 47
Appendix. Summary of Survey Items by Construct Variable
Variable Items
Self-regulation I have good study habits.
I am able to monitor my time effectively.
I am able to get things done on time.
I use my time effectively.
Distance education
self-efficacy
I would rather that we did not have to learn through
distance education.
Using distance education makes learning much more fun.
Distance education makes learning easier.
Distance education makes learning faster.
I can usually deal with most difficulties I encounter when
using the Internet.
The Internet can make me much more productive.
Distance education makes learning more difficult.
Distance education makes learning slower.
Distance education enables me to take courses most
effectively.
Distance education meets my personal needs.
Distance education meets my professional needs.
Distance education is a valuable experience for me.
Self-evaluation I summarize my learning in distance courses to examine
my understanding of what I have learned.
I ask myself a lot of questions about the course material
when studying for a distance course.
I communicate with my classmates to find out how I am
doing in my distance classes.
I communicate with my classmates to find out what I am
learning that is different from what they are learning.
Goal setting I set standards for my assignments in distance courses.
I set short-term (daily or weekly) goals as well as
long-term goals (monthly or for the semester).
I keep a high standard for my learning in my distance
courses.
I set goals to help me manage studying time for my
distance courses.
I don’t compromise the quality of my work because it is
distance.
Environment
structuring
I choose the location where I study to avoid too much
distraction.
I find a comfortable place to study.
I know where I can study most efficiently for distance
courses.
I choose a time with few distractions for studying for my
distance courses.
(Continued)
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48 KIRBY, BARBOUR, SHARPE
Appendix. (Continued)
Variable Items
Time management I allocate extra studying time for my distance courses
because I know it is time-demanding.
I try to schedule the same time every day or every week to
study for my distance courses, and I keep that schedule.
Although we don’t have to attend classes, I still try to
distribute my studying time evenly across the week.
Distance education
expectations
Distance teaching is more effective than in-class teaching.
I learn better through distance courses compared with
on-campus courses.
I believe I will earn a worse grade in a distance course
compared with an on-campus course.
I believe I can learn the same amount in either distance or
on-campus courses.
I believe I can earn the same grade in distance and
on-campus courses.
I believe I can earn a better grade in a distance course than
in an on-campus course.
I believe I can learn more in distance courses than from
on-campus lectures.
Perception of
distance course
communication
and
collaboration
Online communications with my instructor helped with
the learning process in distance courses.
Online communications with my classmates helped with
the learning process in distance courses.
I felt like I was part of a community with my classmates
in my distance courses.
Using online communications tools helped me feel a
sense of community with my classmates.
Group activities helped me feel a sense of community
with my classmates.
Distance classes that do not use communications between
students make me feel isolated from my classmates
and/or alone.
Distance classes without collaborative group activities
make me feel isolated from my classmates and/or
alone.
The connections or relationships I make in one distance
class carry over to other distance classes.
I communicate online with my classmates even when
assignments do not require it.
I will keep in contact with some of my distance course
classmates when my course/degree is finished.
A sense of community among distance students is
important to their satisfaction and success.
(Continued)
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STUDENT PERCEPTIONS AND PREFERENCES 49
Appendix. (Continued)
Variable Items
Satisfaction with
distance
education
Distance education is stimulating.
I prefer distance education.
Distance education is exciting.
Distance education is worth my time.
I enjoy studying by distance.
I look forward to studying by distance.
I would enjoy my education more if all my classes were
by distance.
I would prefer distance education for courses I take in the
future.
Overall, I am satisfied with my distance education classes.
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