A STUDY OF STUDENTS’ SELF-EFFICACY, PERFORMANCE AND ATTITUDES
TOWARD COMPUTERS AND INTERNET IN A COMPUTER LITERACY COURSE
AT FRESHMAN
Serpil Yalcinalp, Ph.D.
Faculty of Commercial Sciences, Department of Management Information Systems, Baskent
University, Ankara, Turkey
Paper presented at the European Conference on Educational Research, University College Dublin, 710 September 2005
Abstract
Understanding students’ attitudes and beliefs about computers is essential in designing effective
computer related courses. This study examined the relationship between self-efficacy, performance
and users’ attitudes toward computers and Internet. The participants were the 88 freshman students of
the computer literacy course at the Faculty of Commercial Sciences. Results indicated significant
relations between the attitudes, self-efficacy and performance of students on the course.
Keywords: self- efficacy, attitudes toward computers, attitudes toward Internet, performance in
computer literacy course
Information society is mainly a consequence of continuing development in new
technologies and requires people who use computer technologies. In this new era,
educational systems seek to prepare students for the work force and computer
literacy becomes vital in higher education. This is especially important for the Faculty
of Commercial Sciences and School of Applied Sciences since the graduates are
expected to involve intensively in businesses that are automating their operations at
an ever-increasing rate in order to improve productivity, competitiveness and profits
(Hakkinen & Paivi, 1995).
As pointed out by Torkzadeh, Pflughoeft & Hall (1999), while many students
approach their training positively and master the skills necessary for the effective
application of computers, others develop a dislike for technology. Aiken (1980)
described the attitudes as “learned predispositions to respond positively or negatively
to certain objects, situations, concepts or persons”. To achieve successful training we
need to be aware of the user’s attitudes toward computers (Zoltan & Chapanis 1982).
On the other hand, Brown et al. (1978) suggest that exposure to computer related
devices may be a factor in determining one’s attitudes toward computers.
Additionally, attitudes toward computers are expected to influence self-efficacy. Selfefficacy relates to students’ self-perceptions of their ability to perform a task (Bandura
1986). It is important to note that self-efficacy is related only to a specific field or
group of behaviors of an individual.
Specifically, computer self-efficacy could be described as the judge of an individual
about his/herself on using computers. Studies indicated that students having high
self-efficacy are more motivated to involve in activities related to computers. Also,
such students could more easily handle with the problems related to using computers
(Karsten & Roth, 1998). The importance of attitudes and beliefs for learning to use
new technologies is widely acknowledged (Bandolas & Benson, 1990: Dupagne &
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Krendl, 1992: Francis-Pelaton &Pelton, 1996: U.S. Congress Office of Technology
Assessment [OTA], 1995).
Several studies indicated that self-efficacy was associated with attitudes toward
computers and Internet. Delcourt and Kinize (1993) and Zubrow (1987) found that
self-efficacy associated with attitudes toward computer technologies. Additionally,
computer attitudes of comfort/anxiety and usefulness contributed significantly
predictive effects on self-efficacy of computer technologies in studies of Kinzie,
Delcourt & Powers (1994). Study of Zhang, Yixin, Espinoza & Sue (1998) reported
that students’ attitudes toward computers affected their confidence levels about
computers. Woodrow (1991) specifically claimed that students’ attitudes toward
computers were a critical issue in computer courses and computer based curricula.
Additionally, high correlation between self-efficacy and subsequent performance was
indicated in the literature (Bandura & Adams, 1977; Bandura, Adams & Beyer 1977;
Schunk, 1991). In the studies of Thuston and Linda (1999), Pintrich & DeGroot
(1990) and Chye, Walker & Smith (1997) also, self-efficacy and learning strategies
have been found to be associated with academic performance.
Akkoyunlu and Orhan (2003) examined the relationship between self-efficacy and
demographic characteristics of the students of computer literacy and instructional
technologies departments in Turkish universities. They found significant relations
between self-efficacy and age, and students’ preferences for their departments in
university entrance exam and type of high school that students had graduated.
Based on results of their study, researchers suggested the need for further studies
investigating the relationship between self-efficacy and attitudes toward computers in
Turkish universities.
The purpose of this study is to examine the relationship between a) self-efficacy and
users’ computer attitudes b) self-efficacy and users’ attitudes toward Internet c) selfefficacy and students performance in a computer literacy course in the Faculty of
Commercial Sciences at Baskent University. The following hypotheses were tested.
Hypothesis 1: There is no statistically predictive effect of attitudes toward computers
on self-efficacy
Hypothesis 2: There is no statistically predictive effect of attitudes toward the Internet
on self-efficacy
Hypothesis 3: There is no statistically predictive effect of performance on self-efficacy
METHOD AND DATA SOURCES
Subjects participating in this study were 88 first year students taking the first
semester computer literacy course in the Faculty of Commercial Sciences in Baskent
University. All students have to complete the same course during the first two
academic years. The self-efficacy in computers was measured through the MSLQ
that were adopted into Turkish by Hendricks, Bulut and Cekici (2003). The alpha
reliability of the MLSQ was 0,93. Attitude scales for computers (ATC) and Internet
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(ATI) were developed by the researcher to assess students’ attitudes toward
computers and the Internet respectively. The alpha interval consistency reliability
estimate of the total score was determined as 0.88 for the Attitudes Toward
Computers scale. The alpha reliability coefficient of the Attitudes Toward Internet
scale was 0.78.
The performance of the students was based on their final grades from this computer
course.
DATA ANALYSIS
To test out hypotheses, the Pearson product-moment was used to determine the
correlations of the selected variables such as attitudes of students toward computers,
Internet, their self-efficacy in computers and their performance at that course. Also,
multiple regression analysis as a general linear model was used to detect all the
significantly predictive effects of the attitudes toward computers, the attitudes toward
the Internet, and performance on computer self-efficacy.
RESULTS
The following four variables were stated as ; students’ attitudes toward computers
(ATC), students’ attitudes toward Internet (ATI), students’ performance from this
computers course (PIC) and students’ self-efficacy in computers (SEC) in that
course.
Simple regression analysis results were indicated significantly high and positive
correlations between attitudes toward computers (ATC) and self efficacy in
computers SEC (r= 0,436, p<0,05). Also, it was found that there was a significantly
high, and positive correlation between the performance in course (PIC) and selfefficacy in computers (SEC) (r= 0, 575, p<0,05) (table 1). On the other hand, no
correlation was indicated between attitude toward Internet (ATI) and self-efficacy in
computers (r=0,189 p>005) (table 1).
The multiple regression analysis was conducted to further predict the self-efficacy of
students from the independent variables of ATC, ATI and PIC. The results of the
multiple regression indicated that when other two variables, ATI and PIC were
controlled, the correlation coefficient between self-efficacy in computers (SEC) and
attitude toward computers (ATC) was lowered (r=0,268 p<0,05) (table 2), but it was
still significant. Therefore, Hypothesis 1 was rejected.
Multiple regression analysis also revealed that, when the other variables, ATC and
PIC were controlled, no significant correlation was observed between the attitude
toward Internet (ATI) and self-efficacy in computers (SEC) (r= -0,097 p>0,05) (table
2). So, Hypothesis 2 was accepted.
Regarding the results of the multiple regression, controlling for other variables (ATC
and ATI) the partial correlation coefficient between the self-efficacy in computers
(SEC) and performance (PIC) was slightly decreased but there was still a significant
and positive correlation (r=0,482 p<0,05) (table 2). Therefore Hypothesis 3 was
rejected.
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Results of multiple regression indicated that combination of three variables; -attitude
toward computers (ATC), attitude toward Internet (ATI) and performance in the
course (PIC)- are contributing significantly high to the correlation with self-efficacy.
(R=0,616, R2=0,379 p<0,05). These three variables all together could explain the
37,9 % of the variance in self-efficacy.
According to the standardized regression constant (β), the order of importance for
variables explaining the self-efficacy was indicated as; performance in course (PIC),
and attitudes toward computers (ATC). Results of the t-test related to the significance
of regression constants, presented PIC and ATC as having significant effects on selfefficacy.
table 1
Pearson Correlation SEC
ATC
ATI
PIC
Sig.
SEC
ATC
ATI
PIC
N
SEC
ATC
ATI
PIC
SEC
1,000
,436
,189
,575
,
,000
,068
,000
64
64
64
64
ATC
,436
1,000
,516
,434
,000
,
,000
,000
64
64
64
64
ATI
,189
,516
1,000
,285
,068
,000
,
,011
64
64
64
64
PIC
,575
,434
,285
1,000
,000
,000
,011
,
64
64
64
64
Correlations between (ATC), students’ attitudes toward Internet, students’ performance from the
computers course and students’ self-efficacy in computers
table 2.
Model
1
(Constant)
ATC
ATI
PIC
R=0,616
F(3,60)=12,223
Unstandardized Standardized
Coefficients
Coefficients
B
Std.
Beta
t
Error
-1,038
8,515
-,122
,197
,092
,273
2,152
-6,736E-02
,089
-,090
-,755
,372
,087
,483
4,262
R2=0,379
p=0,000
Correlations
Zero-order Partial
Sig.
,903
,035
,453
,000
,436
,189
,575
,268
-,097
,482
Part
,219
-,077
,433
Result of multiple regression: Zero order and partial correlations
Dependent variable: Self-efficacy in computers (SEC)
CONCLUSION AND DISCUSSION
The results of this study indicated that there was a high and positive relation between
students’ attitudes toward computers and self-efficacy, and also between students’
performance and their self-efficacy in computers. It can be said that students’ selfefficacy is important in predicting their attitudes toward computers.
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These results are in agreement with previous studies. This suggests that students
lacking positive attitudes toward computers must be taken seriously. Especially the
freshman, as the place of introduction to fundamental courses plays an important role
in such effort. So, new considerations and methods must be developed to increase
the attitudes of students toward computers in computer literacy courses at freshman.
These would also help in ensuring that these students feel themselves as appropriate
for their career goals and skills.
Additionally, in that study slight relationship was indicated between students’
attitudes toward the Internet and their self-efficacy. The Internet unit, as having a very
limited space and weight in comparison to others in the overall course content, could
be the reason for this relationship being weak.
On the other hand, a strong and positive relationship was obtained between students’
performance in that course and their self-efficacy in computers. As stated before,
Bandura & Adams (1977), Bandura, Adams & Beyer (1977), Schunk (1991), Thuston
& Linda (1999), Pintrich & DeGroot (1990) and Chye, Walker & Smith (1997) also
found similar results. This indicates that self-efficacy is a very important concept that
must be considered in designing courses. Results of this study suggest that, training
of students in self-efficacy is another important issue that must be taken carefully into
consideration in conducting such courses.
Although the improvement in self-efficacy was not measured in that study directly, it
seems that training of students in self-efficacy and integrating this issue in computer
literacy courses is unavoidable. The study of Frayne & Latham (1987) and Gist
(1986) indicated that, self-efficacy was improved with training. Torkzadeh, Pflughoeft
& Hall (1999) also stated, self-efficacy was improved expect for those with negative
attitudes. Further, studies examining the effects of training on self-efficacy in a certain
time span with more detailed student characteristics are required. This would help in
designing courses that leads to improve students’ self-efficacy in computers.
This study indicates relations between students’ attitudes, self-efficacy and
performance. Understanding students’ attitudes and beliefs about computers is
essential in designing effective computer related courses. This calls for better
equipped students having rich skills as the manpower of business world in our
technologically driven age. As pointed out by several researchers and Torkzadeh,
Pflughoeft & Hall (1999), if computer users understand the tools and have the
motivation to use them, then the full potential of end-user computing can be realized.
To get more clear picture for the self-efficacy phenomenon, future research is
required exploring the effects of the department, students’ backgrounds in
computers, and other students’ characteristics such as cognitive strategies on selfefficacy.
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