Abstract
The factors that
influence the efficacy beliefs toward success in online learning
environments were examined for counselors-in-training. A multivariate
analysis of variance was run to determine the effects of student age and
previous enrollment in online courses on efficacy beliefs. Results
indicate that efficacy beliefs are significantly influenced by both age
and previous experiences. Implications for research and training
instruction are discussed.
Although
the Internet and World Wide Web have been around for
nearly
40 years, the use of technology in the delivery of university education
is a fairly new innovation, only becoming a common practice in the early
1990s (Williams,
2002 ). Since that time online learning has fast become a major
component of many university academic programs. As noted by Bonk (2001)
“no technology has so swiftly assumed prominence in both educational and
commercial settings as the web” (p. 13). With its ability to assist
educators in overcoming many traditional instructional boundaries (Holcomb,
King, & Brown, 2004), online technology has revolutionized the
traditional view of teaching (Frey,
Yankelov, & Faul, 2003 ;
Willis, 1993 ).
In a review of the
instructional technology literature, researchers have noted several
advantages to online learning including increased access (Olsen,
2002;
Phipps & Merisotis, 1999
). These findings suggest that the
convenience and flexibility of online courses allows many students to
participate in courses they otherwise might not have been able to
previously because of either geographic or personal reasons. The
research also suggests that the structure and content of these courses
make them conducive to self-paced learning (Appleton
& Orr, 2000 ;
Vrasidas & McIsaac, 2000 ), allowing students to work at a pace that
provides them with the opportunity to develop a deeper understanding of
course content (Biggs,
1999 ). An element of practicality is added to the learning process
allowing students the chance to apply learned concepts to problem
solving situations and relate these concepts to everyday experiences (Janda,
1992 ;
Teh, 1999
). These benefits make online education an attractive
option for many students. It is this popularity that has led some (Keeton,
2004 ) to project that online instruction will soon become the
largest source of higher education in America. As a result, many
institutions have begun to adopt online instruction as the next logical
step in educational delivery systems (O’Malley
& McCraw, 1999) and have begun applying it to several academic
content areas (Bates,
2000 ;
Edelson & Pittman, 2001 ).
In the past few
years many counselor educators have begun experimenting with online
instruction, finding new and innovative ways to integrate online
technology into existing courses to supplement, and in some cases
replace traditional methods of instruction (Granello, 2000 ;
Jones & Karper, 2000). These efforts continue to increase as
counselor educators become more familiar with new and existing online
technologies (Baltimore, 2000 ,
Jencius, 2003;
Tyler & Sabella, 2004 ). Despite the increased
acceptance of online technology empirical research remains limited
concerning the use of technology in counselor education (Myers & Gibson,
1999). Studies that have been conducted have primarily examined student
attitudes toward technology use (Berry,
Srebalus, Cromer, & Takacs, 2003;
Chandras, 2000 ;
Hayes & Robinson,
2000 ;
Lundberg, 2000
). These researchers found that students
generally held positive attitudes toward the use of technology and
perceived online instruction to be a valuable experience. In their
study, Berry et al. (2003)
noted that students did not indicate a preference for online instruction
despite previous experiences in online courses. They suggest that this
finding may be the result of experiences in past online courses that
were poorly designed and inappropriately implemented. Absent in these
studies was any consideration of the potential role existing cognitive
constructs have on student success in these courses. An examination of
these constructs might provide counselor educators with a better
understanding of students in online courses and the factors that
influenced their success in these courses. An important construct that
has been used measure individual ability to successfully complete a task
is self-efficacy (Doll & Torkzadeh, 1989 ).
Self-Efficacy
Self-efficacy is a
major component of Bandura’s (1986 ) social cognitive learning theory.
Also called perceived ability, self-efficacy refers to the confidence
people have in their abilities to successfully perform a particular task
(Bandura, 1997 ). It is an individual’s impression of what they are
capable of doing. Thus, a person may regard him or herself as quite
capable in one area but much less capable in another. In discussing his
theory of perceived self-efficacy, Bandura (1977 ,
1997 ) described the
way in which judgments of own capabilities influence performance and the
determinants of those judgments. Self-efficacy influences
the choices we make, the effort we put forth, how long we persist when
confronted with obstacles (and in the face of failure), and the way we
feel about a situation.
If an individual
possesses the ability to successfully perform, then a specific task will
be attempted. The task will be avoided if it is perceived to be too
difficult (Bandura, 1986 ). These efficacy beliefs are developed over
time and are strengthened by a number of sources. According to Bandura
(1982 ), efficacy beliefs are developed and reinforced by four sources:
“performance attainments, vicarious experiences of observing the
performance of others, verbal persuasion, and physiological states from
which people partly judge their capability, strength, and vulnerability”
(p. 126). A major portion of the self-efficacy research has focused on
exploring the impact of these sources on the development of efficacy
beliefs.
Self-efficacy
research has broadened in scope over the last decade to include
investigations of ability perceptions across several domains. Recent
explorations have investigated self-efficacy beliefs regarding the use
of technology. The emergence of new educational delivery systems
emphasizing online instruction and distance learning principles has
created an interest in understanding efficacy beliefs regarding online
instruction. A result of this focused research has been the development
of a new sub-domain of efficacy beliefs known as online self-efficacy.
Online self-efficacy
is defined as the belief an individual has in his/her capabilities to
organize and execute courses of Internet actions required to produce
given attainments (Eastin & LaRose, 2000 ). These Internet actions are
characterized by highly interactive, multi-way synchronous (real time)
and asynchronous (posted) communication and include the various
components traditionally used in online instruction such as electronic
mail, bulletin and discussion boards, newsgroups, chat rooms, and
computer conferencing (Romiszowski & Mason, 1996
). In today’s academic
climate, educators are challenged with finding ways to utilize these
Internet technologies to offer interactive practice of a subject that
facilitates student learning and promotes academic success. Given the
abundance of research supporting the relationship between student
perceptions of their abilities and academic performance it is important
to further examine student perceptions of their ability to successfully
complete online courses as an important part of the overall assessment
of online course effectiveness in counselor education.
Investigations of
online self-efficacy have typically sought to identify factors that
might predict strong, positive self-efficacy beliefs. One factor that
has been shown to influence online self-efficacy is experience with the
Internet and online applications. The more an individual knows about a
specific task the stronger their self-efficacy beliefs (Torkzadeh,
Pflughoeft, & Hall, 1999 ). Although online courses and distance
education are becoming more common place in higher education it is
important to remember that online learning is still a relatively new
concept to many students (Scagnoli, 2001 ). Researchers have generally
found a positive relationship between online experience and
self-efficacy (Eachus, 1996
;
Joo, Bong, & Choi, 2000 ;
Potosky, 2002 ;
Schrum & Hong, 2002), noting that self-efficacy is an important
factor mediating success in online courses (Gibson, 1998 ). For many
novice users, extended online activity may produce feelings of
disorientation (Dias, Gomes, & Correja, 1999 ). These students who have
not had experience with the various forms of technology used in online
instruction may become confused and anxious when asked to utilize an
online component (Chang, 2005 ). This confusion leaves many finding
themselves spending a disproportionate amount of time worrying how to
use the technology rather than focusing on the content of the
assignment. As a result, they may doubt their abilities to successfully
complete an online course.
As colleges and
universities continue to integrate new forms of technology and online
delivery systems faculty must be aware of the impact these new
approaches may have on students who may not have an extensive background
in online instruction. This particularly holds true for counselor
educators. Baltimore (2000
) notes that there is a growing need for the
counseling profession, including its counselors-in-training, to become
proficient in various computer applications and the Internet. Web-based
applications are already being implemented in several courses within the
counseling curriculum including career (Stevens & Lundberg, 1998 ),
group (Krieger & Stockton, 2004 ), counseling techniques (Jones
& Karper, 2000), and clinical supervision (Watson,
2003). Therefore, the purpose of this study is to examine the
online self-efficacy beliefs of counselor education students. An
understanding of these beliefs might provide useful in structuring
future online courses that facilitate student success. In the current
study the influence of previous online course experience and student age
on the online self-efficacy beliefs of counselor education students was
explored.
Methodology
Participants
A convenience sample
of 64 graduate counselor education students was used in this study. The
sample consisted of 47 females and 16 males (one student did not respond
to this question). Participants were organized into four age
categories: 18-25 years old (n = 12), 26-35 years old (n = 31), 36-45
years old (n = 12), and 46-55 years old (n = 9). The majority of
participants reported previous experience in online courses. Twenty
participants (31.3%) reported no prior experience in online courses, 28
(43.7%) reported experience in one or two courses, and 16 (25.0%)
reported previous experience in three or more online courses.
Participants were recruited prior to the beginning of a regularly
scheduled class session. Those participants volunteering to participate
completed a survey questionnaire and a personal data sheet. No
incentives were provided for participating in this study.
Instrumentation
Online Technology
Self-Efficacy Scale.
The Online Technology Self-Efficacy Scale (OTSES;
Miltiadou & Yu, 2000 )
is a 29-item instrument designed to measure self-efficacy specific to
the online learning environment. Items are scored on a four-point Likert scale from not confident at all (1) to very confident
(4). The OTSES includes items which relate to four components of online
instruction: (a) Internet Competencies (opening a website, conducting
Internet searches), (b) Synchronous Interaction (reading and replying in
a chat room or instant messenger system), (c) Asynchronous Interaction I
(accessing, reading, and sending email messages), and (d) Asynchronous
Interaction II (accessing and posting messages to a group discussion
board). The OTSES yields a global scale score of online self-efficacy
with an internal consistency reliability estimate of .95. Following
Miltiadou and Yu’s (2000
) suggestion, the single global score will be
used as the dependent variable in this study. A reliability analysis
conducted to examine the internal consistency of the OTSES instrument
for the current sample yielded an alpha coefficient of .96, suggesting
that the OTSES was a reliable instrument for the given sample.
Personal Data Sheet.
The personal data sheet created for this study asked participants to
indicate their age, gender, ethnicity, marital status, employment
status, previous online course experience, weekly computer usage, and
home Internet access.
Results
Descriptive
statistics were computed for the participants’ OTSES scores. Means,
standard deviations and score ranges for each groups’ OTSES scores are
presented in Table 1. The results indicate a trend toward increasing
efficacy beliefs for those with greater online experience and a trend
toward decreasing efficacy beliefs for more non-traditional students.
Table 1.
Means and Standard
Deviations of OTSES scores by Age and Previous Online Experience
|
Sample Group
|
Mean
|
SD |
Minimum |
Maximum |
|
No previous
online courses |
92.40 |
20.08 |
62 |
116 |
|
1-2 previous
online courses |
98.61 |
17.23 |
44 |
116 |
|
3-5 previous
online courses |
106.44 |
8.18 |
90 |
116 |
|
|
|
|
|
|
|
18-25 years old
|
101.00 |
14.51 |
69 |
116 |
|
26-35 years old
|
103.35 |
12.85 |
69 |
116 |
|
36-45 years old
|
87.83 |
21.90 |
44 |
116 |
|
46-55 years old
|
93.56 |
20.88 |
66 |
116 |
To determine the
significance of these reported differences, a 3 x 4 between subjects
factorial analysis of variance (ANOVA) was calculated to evaluate the
impact of previous class experience (none, 1-2, 3 or more) and age
(18-25, 26-35, 36-45, 46-55) on online self-efficacy perceptions. Given
the unequal sample sizes a Levene’s test was used to assess the
homogeneity of variance between the groups. The results of the Levene
test, F(11, 52) 1.79, p < .08, were nonsignificant
indicating that sample variances were equivalent and that the results of
the analyses would be valid. Results from the factorial ANOVA yielded
significant main effects for both previous online course experience F(2,
52) = 3.38, p < .042, η2 = .12, and age, F(3,
52) = 3.10, p < .034, η2 = .15. The interaction
effect between previous online course experience and student age was
nonsignificant for the given sample.
Post hoc analyses
were computed to indicate specific differences between the subgroups of
each variable. The Scheffé follow-up procedure (p = .05) was
performed to assess pairwise differences among the three levels of
previous online course experience. The results indicated that online
self-efficacy beliefs for the no previous online courses (M = 92.40, SD
= 20.08) and 3-5 previous online courses (M = 106.44, SD = 8.18) groups
differed significantly. Applying the Scheffé procedure to the four
levels of age yielded a significant difference between the 26-35 year
old group (M = 103.35, SD = 12.85) and 36-45 year old group (M = 87.83,
SD = 21.90).
Discussion
The identification
of previous experience with online learning is in line with other
findings that have shown performance accomplishment to be the most
important source of self efficacy (Bandura, 1997 ;
Wise & Trunnell, 2001
). Participants who had previously completed multiple online courses
felt more confident in their abilities to succeed in an online course
than those who had minimal or no previous experience with online
courses. This finding appears to support previous studies (Edwards,
Portman, Bethea, 2002 ;
McFadden & Jencius, 2000 ) that advocated for
the inclusion of an introductory computer skills training course in the
counseling curriculum. Counselor educators who desire to use online
components in their class might also consider the possibility of
offering tutorials and sample exercises early in the semester. These
experiences could help acclimate students to the process of using online
technologies without having to worry about any negative impact on course
grades that their initial inability to understand an online modality may
cause.
The significant
finding for student age differs from the distance learning literature.
Previous research has suggested that non-traditional college aged
students were more likely to persist and succeed in online courses than
traditional aged students (Rekkedal, 1983 ;
Cookson, 1989 ). In the
current study it was found that efficacy scores decreased among older
sample participants. Many of the current technologies used in online
courses are relatively new interventions. It is likely that
traditional-aged students who have grown up with this technology might
have gained more experience in using these online applications than
those non-traditional students who might be returning to academe after
an extended stay in the workforce. The significant finding of age, and
previous online experience, suggest that it is important for counselor
educators planning to implement online technology into their current
courses to evaluate their students to determine their perceptions of
their ability to be successful in courses integrating this new course
delivery system.
According to Davis
(1989
) even the most well-intended and structured attempts to implement
online instruction will be rendered ineffective if they are not
perceived as useful by students. Students who are less confident in
their abilities to use online technology may spend more time focusing on
the applications than on course content. As a result, their learning
may suffer. The educational backgrounds of students in online courses
can serve as early warning indicators for failure or success in the
online learning environments. Identifying those students who feel less
confident about their ability to manage an online course allows
instructors to provide additional assistance or training opportunities
for these students. Enhancing the self-efficacy perceptions of students
in online courses will lead to improved academic performance and
decreased attrition rates in online courses.
For those counselor
educators who choose to implement technology and web-based applications
it is critical that they utilize online technology consistently.
Whether by email, discussion board, WebCT or Blackboard course modules,
Internet searches, or chat rooms, courses should require students to
regularly engage in online learning. The more experiences students have
with online tools the more confident they can become in their abilities
to use the Internet and other online components. It also is suggested
that educators monitor their students’ online activity. Tracking a
student’s online course activity is important because it can reveal
several warning indicators of student performance (Wang
& Newlin, 2002). Tracking allows educators to identify when and
where students may be having trouble and allow them to offer relevant
remediation suggestions. The software needed to track students’ online
activity is readily available with most online course modules (WebCT,
Blackboard) and through some Internet service providers.
Overall, online
learning is considered the preferred mode of future educational delivery
(Keeton, 2004 ). Increased availability of technology and acceptance of
online learning as a viable alternative to traditional forms of
education are motivating this change in philosophy. As this change
occurs Culpan (1995 ) cautions educators that no matter how
sophisticated and how capable the technology, its effective
implementation depends on users having a positive attitude towards it.
Therefore, educators must consider their students’ attitudes and
perceptions of online learning if the approach is to be successful.
Students with low self-efficacy are more likely to give up earlier in
their academic pursuits than students with high self-efficacy. Repeated
exposure and expanded opportunities for practice should increase the
self-efficacy perceptions of online learners and lead to a more positive
approach toward online learning.
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Author's Biography
Joshua C. Watson is
an Assistant Professor of Counselor Education in the Department of
Counseling, Educational Psychology, and Special Education at the
Mississippi State
University Meridian Campus. He
can be reached at:
jwatson@meridian.msstate.edu
