General interest in distance education, which is perceived
as a practical choice by many students, and education institutions is
increasing more and more in parallel with the advances in the information
and communication technologies. High motivation level, maturity, and self-discipline
are seen as necessary general characteristics of successful students for
the achievement of distance education programs and for the continuity
of students to the programs (Willis, 1994). A combination of cognitive
style, personality characteristics and self-expectations is asserted to
be able to predict the achievement in distance education (McIsaac &
Gunawerdena, 1996). By this study, it is aimed to determine the self-efficacy
beliefs for distance education, achievement goals, and self-regulation
abilities of students, which are some of the characteristics motivating
students of distance education, and to suggest a relationship between
these characteristics and academic success.
STUDIES ON STUDENTS CHARACTERISTICS IN DISTANCE
EDUCATION: A BRIEF
There has been many works performed on student characteristics
of distance education. In some of these Oxford, Re., Park-Oh, Y., Ito,
S., & Sumrall, M., in the Japanese language program published through
satellite television, it has been shown that student characteristics like
motivation, learning styles, gender, and, learning strategies played a
very important role in academic achievement (1993). Chan M. S. C, Yum,
J. , Fan, R. Y. K., Jegede, O. & Taplin, M. have compared high achieving
and low achieving open university students according to their study habits,
purpose for learning, approaches to study, use of support systems, other
commitments and self-perceptions and have shown that motivation is a factor
effecting achievement (1999). Roblyer (1999)’s study demonstrated
on factors that motivate community college and virtual high school students
to choose online or traditional course formats. Findings of this study
indicate that for students who chose distance learning, control over Face
and timing of learning was more important; for students who chose face-to-face
(FTF) course, interaction with instructor and students was paramount.
Lee (2002), examined gender differences in motivational and behavioral
learning strategies in the Internet-based cyber-learning environment and
found highly significant gender differences in the category of textual
encoding strategies, in which males showed stronger behavioral and motivational
As well as these student characteristics mentioned above, self-efficacy
studies are also very popular for distance education. Some of these can
be summed up as such: Joo, Bong & Choi (2000), examined effect of
student motivation on performance in Web-based instruction (WBI) and found
that student’s self-efficacy for self-regulated learning positively
related to his/her academic self-efficacy, strategy use, and Internet
self-efficacy. In a work aiming to form a model that can predict the satisfaction
of Web based adult distant learners and their intention to join again
in the distance education courses to be presented through Web in the future,
Lim (2001) has indicated that, self efficacy in computer knowledge was
the only statistically significant variable that can help predict the
achievement. Wang and Newlin (2002)’s study investigated college
student’s personal choice for taking web-based courses and whether
their self-efficacy for the course content and technological components
would predict their performance in on-line sections of a class. They have
found that measures of self-efficacy were predictive of final exam scores,
but demographic factors (age, gender, the number of hours employed per
week, the number of children living at home, and distance traveled to
campus) do not correlate with final grades in an on-line class.
The present investigation examined relationship among several motivational
characteristics (like self-efficacy for distance education, self-regulation
and achievement goals) and academic achievement in distance education
RELATIONSHIP AMONG SELF-EFFICACY
AND SELF REGULATION AND ACHIEVEMENT GOALS
Self-efficacy refers to an individual’s expectancy in his or her
capability to organize and execute the behaviors needed to successfully
complete a task (Bandura, 1977; Schunk, 1991). Self-efficacy beliefs can
determine how people feel, think, motivate themselves, and act. Bandura
points out that, in the basis of self-efficacy there lies a mechanism
of changing, continuing and generalizing of behavior (Bandura, 1977).
Self-efficacy beliefs effect behaviors through important means. Self-efficacy
beliefs effect choices of persons about whether will they be in similar
occupational activities in the future or not (Turner & Shallert, 2001).
These beliefs, do not only effect the choice of activities, but also help
persons in determining how much will they strive for achievement, how
long will they exert themselves against difficulties, and how will they
handle troubles and maintain their course (Bandura, 1977; Pajares, 2002).
In the case of education, self-efficacy is seen to be related with effort,
persistence and achievement. Chemers, Hu & Garcia (2001), in their
work on mathematical problem solving, have shown that children with higher
self-efficacy strived for longer periods and used more effective problem
solving strategies than students with lower self-efficacy.
Researches show that self-efficacy beliefs have positive effects on student
motivation and achievement (Pintrich & De Groot, 1990; Zimmerman,
Bandura & Martinez-Pons, 1992; Pajares & Miller, 1994). For example,
Pintrich & De Groot (1990), reported that academic self-efficacy positively
correlated to various outcome measures such as grades seatwork performances,
scores on exams and seat work performances, scores on exams and quizzes,
and quality of essay and reports. Researchers have established that self-efficacy
is a strong predictor of academic performance. Multon, Brown, & Lent
(1991) (cited in Chemers et al, 2001) found that self-efficacy was related
both to academic performance (r=.38) and to persistence (r=.34). In the
same context, Pajares & Kranzler’s (1995) study has demonstrated
that the direct effect of mathematics self-efficacy on mathematics performance
(B=.349) was as strong as was the effect of general mental ability (B=.324).
Schunk (1991) stated that individuals who have a high sense of self-efficacy
for accomplishing a task work harder and persist longer when they encounter
difficulties, whereas those who do not feel efficacious may quit or avoid
a task. Bandura (1994) stated that self-efficacy beliefs play a key role
in the self-regulation of motivation. According to Bandura, people motivate
themselves and they form beliefs about what they can do, they set goals
for themselves and plan courses of action designed to realize valued futures.
Researchers in academic domain, have studied the relationship among self-efficacy
and other motivational constructs such as self-regulation (Pintrich &
De Groot, 1990); Zimmerman & Martinez-Pons, 1990) and goal orientation
(Middleton & Midgley, 1997; Pajares, Britner & Valiante, 2000).
In academic contexts, self-regulation refers to processes that involve
the activation and maintenance of cognitions, behaviors and affects which
are systematically oriented toward the attainment of goals (Zimmerman,
1989; Schunk, 1989). According to Butler & Winne (1995) self-regulation
is a learning style for students comprising of strong abilities like setting
goals for developing knowledge, and choosing balancing strategies against
unwanted situations by determining goals. And self-regulated students
are aware of their knowledge, their beliefs, motivation, and qualities
of their cognitive processes. Kovach (2000) stated that self-regulated
learners set academic goals, select appropriate learning strategies to
achieve these goals, and continually monitor goal progress. Self-efficacy
is related to self-regulated learning variables. Findings in this area
suggest that students with stronger self-efficacy make better use of cognitive
strategies and self-regulatory practices and persist longer than those
who do not.
In this area, Pintrich & De Groot (1990) suggested that academic self-efficacy
beliefs were positively related to intrinsic value and cognitive and self-regulatory
strategy use. Zimmerman & Martinez-Pons (1990) reported that, there
is a positive relation between self-efficacy and self-regulation strategies.
Goals too are seen as an important cognitive process effecting student
motivation. Goals enhance self-regulation due to their effects on motivation,
learning, self-efficacy and evaluation of the process (Bandura, 1997;
Schunk, 1995). In this study, achievement goals refer to the reasons that
students have for doing their academic work. Achievement of goals has
two general types: mastery and performance. Task goals (sometimes called
learning or mastery goals), are aiming of a person for improving his/her
efficacy for attaining the new knowledge and ability. And performance
goals (also called ego goals) are aiming of a person for a better efficacy
performance than others. In this study, mastery goals (or learning goals)
are preferred. As distance-learning students do not have any means for
comparing their performances with others, using performance goals was
not found appropriate. Barron & Harackiewicz (2001) stated that, students
following learning goals work hard against difficulties for longer than
the students following performance goals, pay more attention to studying
strategies, and develop a more positive manner against learning. A review
of the literature on achievement goals has shown that task goals are positively
related to self-efficacy and self-regulation. For example, Middleton and
Midgley (1997) reported that task goals were positively related with mathematics
self-efficacy and with self-regulated learning. In a similar manner, Pajares,
Britner, & Valiante (2000) suggested that task goals were positively
related to self-efficacy, self-concept, and self-efficacy for self-regulation.
Consequently, since learning is more personal and responsibility is more
on the shoulders of the students in distance education in comparison to
traditional education, motivational constructs are more important also.
Distance education requires students to monitor and regulate their own
learning. In order to achieve, students should have self-efficacy beliefs,
determine achievement goals, control their own learning, and regulate
themselves. For this reason, determining this type of characteristics
of distance education students is extremely important for distance education
institutions in order to give students the support and counseling they
need. The present research examined the relationship between academic
achievements and student’s characteristics like demographic properties
(age, gender, employed/unemployed), self-efficacy beliefs of distance
education, and self-regulation and achievement goals for distance education.
Participants and Procedures
Participants were 124 freshmen students who enrolled in Anadolu University’s
distance learning programs, including such undergraduate programs as economy,
finance, public administration, working economy, industrial relations
and business administration. These students were at the same time attending
to academic counseling courses administered in province of Eskisehir.
Because of the variations in the number of students attending academic
counseling courses, student samples are selected randomly within a time
frame. 50 % of the students were female and 50 % were male. They had an
average of 20, ranging from 17 to 40 years old. Number of students working
full-time was one fifth of students who do not work. The questionnaire
was administered at the end of the semester in 2002.
The Questionnaire. The questionnaire was designed based on relevant researches.
Primarily, questions on students’ demographic characteristics (e.g.
age, gender, employed/unemployed) were asked. Gender was coded as 1 (male)
and 2 (female). In the same manner, student who does not work was coded
as 1 and working student was coded as 2. The questionnaire was organized
into three categories; student’s self-efficacy beliefs of distance
education (8 items), self-regulation skills (10 items) and achievement
goals (8 items). Each item was designed with 5-point Likert scales, using
values of 1 for “strongly disagree” and 5 for “strongly
The Self-efficacy subscale and self-regulated learning strategies subscale
of the Motivated Strategies for Learning Questionnaire (MSLQ) were used.
All items used by Pintrich & De Groot (1990) were adopted. “I’m
certain I can understand the ideas taught in this course” item contained
in MSLQ was adapted as “I’m certain I can understand the subjects
presented in the books of distance education”; similarly the item
“I’m sure I can do an excellent job on the problems and tasks
assigned for this class” was adapted as “I’m sure I
can do an excellent job on the problems asked at the end of chapters of
distance education text books” and finally the item “I think
I will receive a good grade in this class” as “I’m sure
I will receive good grades from tests.” Items on the MSLQ which
prompt explicit social comparison (e.g., “Compared with other students
in this class I think I know a great deal about the subject”) were
deleted or rephrased. Because, students of distance education do not have
any means of comparing themselves with other students. Other questionnaire
items were as follows: “I am sure I can learn in distance education
at least as better as in traditional education”, “I am sure
I can learn at any time and any place by method of distant learning.”
The self-regulation subscale of the MSLQ was used and adopted. Sample
items for self-regulation were: “I ask myself questions to make
sure I know the material of distance education I have been studying,”
“I work on practice exercises and answer end of chapter questions
even when I don’t have to,” and “I work very hard to
receive good grades even though I don’t like a certain lesson of
distance education program.”
For the achievement goal subscale, 5 items of mastery goal orientation
subscale of Patterns of Adaptive Learning Scales (PALS) (Midgley et all.,2000)
were rephrased for distance education. For example “It’s important
to me that I learn a lot of new concepts this year” item was adapted
as “It’s important to me that I learn a lot of new concepts
in distance education lessons this year”; similarly, “It’s
important to me that I thoroughly understand my class work” item
as “It’s my fundamental purpose that I thoroughly understand
my distance education books”; and “One of my goals in class
is to learn as much as I can” item as “One of my goals this
year is to learn as much as I can.”
Two experts in related fields of educational psychology and educational
technology were consulted to verify the validity of translated and adopted
items. After receiving the expert opinions, necessary arrangements were
made on the items of the questionnaire and the comprehensibility of it
was tested by applying on students carrying the characteristics of the
sampling. In order to test the reliability of the questionnaire, it was
applied two times with two weeks intervals to 10 persons who are outside
the sample group but who have the characteristics of it and the Pearson
correlation coefficient between the two applications was found to be r=0.82
Academic achievement measures. At the end of the 2001-2002-education year
during when the questionnaire was administered, achievement grades for
all the lessons received by all the students who filled in the questionnaire
were obtained. Achieved grades were summed and the total obtained was
divided into the number of lessons received by the student. Thus, for
each of the students who filled the questionnaire, an academic achievement
grade was obtained for that educational year.
Table 1 presents descriptive statistics of scales and academic achievement.
As Table 1 Shows, mean of student’s academic achievement was M=50.15;
self-efficacy beliefs for distance education M=28.43; self-regulation
M=38.20; achievement goals M=33.53.
Table 1. Descriptive Statistics of Scales and Academic
A Pearson correlation was computed to examine relations among variables.
At first, correlations between age (among demographic characteristics
of students), self-efficacy beliefs for distance education, self-regulation
and achievement goals (among motivating characteristics) and academic
achievement of students were examined.
Table 2 . Pearson Correlation Coefficients Between Student’s
Characteristics and Academic Achievement
The results are presented in Table 2. According to the
findings, the self-efficacy of distance education was found to be significantly
correlated to student’s academic achievement (r=.249, p < .01).
But a significant relation was not found between academic achievement
and other variables (age, self-regulation, and achievement goals).
However, other variables of demographic characteristics except age; self-efficacy
for distance education, self-regulation, and achievement goals were significantly
correlated among themselves. Age and such variables like self-efficacy
for distance education, self-regulation, and achievement goals were not
significantly correlated. Whereas self-efficacy for distance education
showed a significant correlation with self-regulation (r=.470, p <
.01) and with achievement goals (r=.477, p < .01). Similarly, self-regulation
also correlated highly with achievement goals (r=.632, p < .01).
In addition to these, Z tests were conducted in order to determine that
gender variable from demographic characteristics and employed/unemployed
statuses of students display a difference across academic achievement,
self-efficacy for distance education, self-regulation and achievement
Table 3. Z Ratios According to Gender
As it is shown also by Table 3, a significant difference
was detected only on self-regulation, Z=2.225, p < .05 ( s=37.04 for
males and 39.37 for females) favoring females. Other variables academic
achievement, self-efficacy for distance education and achievement goals
did not show a significant difference across genders.
Similarly, results of Z tests conducted for determining an existence of
difference displayed by employed/unemployed students across the same variables,
can be seen at Table 4. According to these results, employed/unemployed
students do not display a statistically significant difference in academic
achievement, self-efficacy for distance education, self-regulation and
Table 4. Z Ratios According to Working Status
Finally, regression analysis was performed to clarify
the influence of the student’s motivational characteristics including
self-efficacy of distance education, self-regulation and achievement goals
on academic achievement. As Table 5 shows, significant effect was observed
for self-efficacy of distance education (p < .01). The results indicated
that, self-efficacy of distance education significantly and positively
predicted student’s academic achievement.
Table 5. Regression Analysis of the Motivational Characteristics
on Academic Achievement
Motivational characteristics are very important in the literature of distance
education. Because for the achieving students, researchers agree on the
necessity of being motivated (Sewart, Keegan, & Holmberg, 1983). Especially
in the studies carried out on motivation in distance education, it is
often stated that motivation has a great importance in student achievement
and continuity (Murphy, 1989; Suciati, 1990; Oxford et al., 1993; Chan
et al., 1999). By this work, it is aimed to determine the relationships
between academic achievement, demographic characteristics of students
in distance education (like age, gender, employed/unemployed), and motivational
characteristics (like self-efficacy beliefs for distance education, self-regulation,
and achievement goals).
Within the present study, demographic characteristics like age, gender,
and employed/unemployed were not significantly correlated with academic
achievement. The results from Wang & Newlin (2002)’s study,
also demonstrate that demographic factors (like age, gender, the number
of hours employed per week) do not correlate with final grades in an on-line
class. There was truly a significant and positive correlation between
academic achievement and self-efficacy beliefs of distance education which
is one of the variables motivating students. Student’s self-efficacy
beliefs have strong and positive influence on their academic achievement.
According to the results of this study, it appears that the students with
higher self-efficacy beliefs of distance education have higher academic
achievement. Previous research documented significant relationship between
self-efficacy and achievement (e.g., Pintrich & De Groot, 1990; Chemers,
Hu, & Garcia, 2001; Joo et al., 2000).
The present investigation, did not find a significant relationship between
self-regulation and academic achievement. This finding contradicts with
the previous research results (Zimmerman & Martinez-Pons, 1990; Pintrich
& De Groot, 1990). It can be said that students who answered the items
of the questionnaire in this investigation could not have formed the strategies
that serve their learning in distance education by self regulation and
for this reason their academic achievement have not been in a sufficient
level (M=50.15 out of hundred). Hence, there should be arrangements in
distance education system that enhances self-regulated learning skills
Schunk (1991) stated that, goals of persons do at the same time develop
self-efficacy beliefs. In the present study, a significant relationship
between self-efficacy beliefs and achievement goals were shown. Similar
to the previous works (Pintrich & De Groot, 1990), a significant relationship
between self-efficacy and self-regulation was also seen.
When the obtained findings were assessed against gender, male and female
students do not display any difference in academic achievement, self-efficacy
for distance education, and achievement goals. However, as it was found
in some of the previous researchs (Zimmerman & Martinez-Pons, 1990;
Joo et al., 2000), self-regulation characteristic becomes significant
for females. Females reported more record than males in use of self-regulated
strategies. In the current study, employed/unemployed students as demographic
characteristics did not display a significant difference in academic achievement
and other motivational characteristics (self-efficacy for distance education,
self-regulation, and achievement goals). According to regression analysis
of the motivational characteristics, self-efficacy of distance education
significantly and positively predicted student’s academic achievement.
This result is similar to the previous works (Joo et al., 2000). With
its primary emphasis on student characteristics in distance education,
the current study involved only a limited number of variables presumed
to influence distance learning. Future works on a larger student sampling
from various regions can be restructured in a similar manner by adding
different demographic characteristics like socio-economic structure and
culture. Additionally, by extending this study to longer time span, self-efficacy
beliefs of the students at the beginning and end of the program can be
compared with themselves and with academic achievements of students.
Finally, the present study indicates that academic advisors, teachers,
and instructional designers of distance education can make use of self-efficacy
beliefs of students. Especially academic advisors may find out about self-efficacy
beliefs of students by way of questionnaires applicable through Internet
and may help motivating these students and increasing their academic achievement
by means of feedback they receive from them.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral
change. Psychological Review, 84(2), 191-215.
Bandura, A. (1994). Self-efficacy. In V.S.Ramachaudran (Ed.), Encyclopedia
of Human Behavior (Vol.4, pp. 71-81) New York: Academic Press.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York:
Barron, K. E. & Harackiewicz, J. M. (2001). Achievement goals and
optimal motivation: Testing multiple goal models. Journal of Personality
and Social Psychology, 80, (5), 706-722.
Butler, D. & Winne, P. (1995). Feedback and self-regulated learning:
A theoretical synthesis. Review of Educational Research, 65 (3), 245-281.
Chan, M. S. C, Yum, J. , Fan, R. Y. K., Jegede, O. & Taplin, M.(1999,
October). Locus of control and metacognition in open and distance learning:
A comparative study of low and high achievers. Paper presented at the
13th. Annual Conference, Asian Association of Open Universities. The Central
Radio & TV University, Beijing, China.
Chemers, M. M., Hu, L. & Garcia, B. F. (2001). Academic self-efficacy
and first-year college student performance and adjustment. Journal of
Educational Psychology. 93(1), 55-64.
Joo, Y.-J. , Bong, M. & Choi, H-J. (2000). Self-efficacy for self-regulated
learning, academic self-efficacy and internet self-efficacy in web-based
instruction. Educational Technology Research and Development, 48 (2),
Kovach, J.C. (2000, October). Self-regulatory strategies in an accounting
principles course: Effects on student achievement. Paper presented at
the Mid-Western Educational Research Association, Chicago, Illinois, [On-line].
Lee, I-S. (2002). Gender differences in self-regulated on-line learning
strategies within Korea’s University context. Educational Technology
Research and Development, 50 (1), 101-109.
Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and
other predictor of satisfaction and future participation of adult distance
learners. The American Journal of Distance Education. 15(2), 41-51.
Mc Isaac, M. S. & Gunawardena, C. N. (1996). Distance education. In
Jonassen, D. H. (Ed.), Handbook of research for education communications
and technology (pp. 403-437). New York: Macmillan.
Middleton, M. & Midgley, C. (1997). Avoiding the demonstration of
lack of ability: A underexplored aspect of goal theory. Journal of Educational
Psychology, 89, 710-718.
Midgley, C., Maehr, M.L., Hruda, L.Z., Anderman, E. and others. (2000).
Manual for the Patterns of Adaptive Learning Scales. [On-line]. Available
Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy
beliefs to academic outcomes: A meta-analytic investigation. Journal of
Counseling Psychology, 38(1), 30-38.
Murphy, K.L. (1989, March). A study of motivation in Turkish distance
education. Paper presented at the annuel meeting of the American Educational
Research Association. San Fransisco, CA.
Oxford, Re., Park-Oh, Y. , Ito, S., & Sumrall, M. (1993). Factors
affecting achievement in a satellite-delivered Japanese language program.
The American Journal of Distance Education. (7), 1.
Pajares, F., & Miller, M.D. (1994). Role of self-efficacy and self-concept
beliefs in mathematical problem solving: A path analysis. Journal of Educational
Psychology, 86 (2), 193-203.
Pajares, F., & Kranzler, J. (1995). Self-efficacy beliefs and general
mental ability in mathematical problem solving. Contemporary Educational
Psychology, 20(1), 426-443.
Pajares, F., Britner, S.L., & Valiante, G. (2000). Relation between
Achievement goals and self-beliefs of middle school students in writing
and science. Contemporary Educational Psychology, 25, 406-422.
Pajares. F. (2002). Self-efficacy beliefs in academic contexts: An outline.[On-line].Available
Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated
learning components of classroom academic performance. Journal of Educational
Psychology, 82 (1), 33-40.
Roblyer, M. D. (1999). Is choice important in distance learning? A study
of student motives for taking internet-based courses at the high school
and community college levels. Journal of Research on Computing in Education,
Schunk, D. H. (1989). Social cognitive theory and self-regulated learning.
In. Zimmerman, B. J., & Schunk, D.H. (Eds.), Self-regulated learning
and academic achievement: Theory, research, and practice (pp. 83-110).
New York: Springer-Verlag.
Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational
Psychologist, 26, (3 & 4), 207-231.
Schunk, D. H. (1995). Self-efficacy and education and instruction. In
Maddux, J.E. (Ed.), Self-efficacy, adaptation and adjustment: Theory,
research, and application (pp.281-303). New York: Plenum Press.
Sewart, D., Keegan, D., & Holmberg,B. (1993). Distance Education:International
Perspectives. Billings & Sons. Limt.
Suciati. (1990). The effect of motivation on academic achievement in a
distance education settings: An examination of latent variables. Unpublished
doctoral dissertation, Syracuse University).
Turner, J.E. & Schallert, D. L. (2001). Expectancy-value relationships
of shame reactions and shame resiliency. Journal of Educational Psychology,
Wang, A.Y. & Newlin, M. H. (2002). Predictors of web student performance:
The role of self-efficacy and reasons for taking an on-line class. Computers
in Human Behavior, 18(2), 151-163.
Willis, B. (1994). Distance education strategies and tools. New Jersey:
Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic
learning. Journal of Educational Psychology, 81, 329-339.
Zimmerman, B. J. & Martinez-Pons, M. (1990). Student differences in
self-regulated learning : Relating grade, sex and giftedness to self-efficacy
and strategy use. Journal of Educational Psychology, 82(1), 51-59.
Zimmerman, B. J., Bandura, A., & Martinez-Pons, M. (1992). Motivation
for academic attainment: The role of self-efficacy beliefs and personal
goal setting. American Educational Research Journal, 29(3), 663-676.
Biodata of Author:
MS-Educational Technology, Social Science Graduate Institute, Anadolu
PhD-Communicational Science, Social Science Graduate Institute, Anadolu
Research Interests: Educational Technology; student characteristics; motivation;
self-efficacy; academic achievement
Contacts: Dr. Hülya Ergül
School of Civil Aviation, Anadolu University 26470- Eskisehir, TURKEY
Office Tel: +90 222 3222071 Ext. 6822