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Identifying trainees' computer self-efficacy in relation to some variables: the case of Turkish EFL trainees.

Introduction

Development of computers and their use in language have shaped the curriculum and created new areas such as computer-based learning, interactive teaching, distance education, the use of web tools in language learning, learning blogs, Apps for learning are few to mention. Nowadays, it is almost impossible to avoid the use of computers in learning any subject area. Studies reveal that the use of computers in the classroom helps learning (Yilmaz et al., 2004; Inal 2005, Ercan 2005, Philips 2005; Thao 2003) and especially is very effective in foreign language learning to facilitate the learning of authentic language and culture of the target language through communication with native speakers of that language via emails, twitter, Nimbuzz, facebook, Skype; to read online journals and newspapers, post to blogs in the target language. This will improve speaking as well as pronunciation. The use of computer eases and visualizes learning, expands the vocabulary through interactive vocabulary games; it provides freedom of learning, helps slower students to learn at their own pace and creates fun in the class. Search listserv and library database, watch films and listen to music in the target language are other benefits of computer use in learning. "The unique property of the computer as a medium for education is its ability to interact with the student," Naba'h, Hussain, Al-Omari, and Shdeifat (2009) as it "enables introvert students to interact better, and creates student-centered form of learning," (Tanveer 2011.)." On the other hand, the use of computer may reduce the overload work and the role of the teacher; and that of the students in the classroom. However, the integration of computers in the classroom and their effective use heavily depend on the attitudes of the teachers and how they consider them. Such kind of perception is called self-efficacy and accepted as a "thermostat of monitoring the effectiveness of one's own behaviour," (Rueda 2008). Self-efficacy is also believed to lead to high motivation (Bandura 1995, Idrus & Salleh (UD*), Rueda, 2008). To Busch (1995, cited in Sam, Ekhsan, Othman and Nordin (2005) high self-efficacy could be an important factor in helping people learn computer skills and use computers..

Self-efficacy and Social Cognitive Theory

Self-efficacy is first proposed by Bandura (1997) within the Social Cognitive Theory. Self-efficacy is "believing in one's own ability to perform the given type of task," (Bandura, 1997: 21). Self-efficacy is like the first step of the ladder which will take individuals to the satisfaction of performing their own commitments and most likely to achievement. The studies indicate the relationship between self-efficacy and high possibility of achievement. To Bandura (1982, 1994), self-efficacy perception is based on the idea that individuals set goals in life, and to achieve these goals they should have strong beliefs to perform them, as to him such belief has an impact on achievement and one's personal judgment about accomplishment is more important than anything. What people think, believe, and feel affect how they behave," (Bandura 1986, p. 25, cited in Pajares 2002). To Idrus and Salleh (UD), "low efficacy beliefs are characterized by low aspiration and weak commitment to goals and individuals with low efficacy beliefs are more likely to become frustrated when they encounter difficult challenges, and see these challenges as personal threats to be avoided rather than challenges to be mastered." Likewise, Pajares (2002), refers to the relationship between motivation and self-efficacy as: "Self-efficacy beliefs are correlated with other motivation constructs and with students' academic performances and achievement." "A strong sense of efficacy enhances human accomplishment and personal well-being in many ways," (Bandura 1994). To Bandura, this process is affected by self-regulatory mechanisms, (cited in Pajares 2002) and added, "individuals develop their behaviours rooted in three major concepts: self-concept, self-esteem and self-efficacy which all make up self-regulatory mechanism, and a part of individual's self-evaluation period," (Bandura 1995, 1986). "Self-efficacy beliefs help determine the choices people make, the effort they put forth, the persistence and perseverance they display in the face of difficulties, and the degree of anxiety or serenity they experience as they engage the myriad of tasks that comprise their lives.. Self-efficacy has received ample attention in educational research, where it has been shown to predict students' academic achievement across academic areas and levels," (Ellen & Pajares 2008).

Isksal & Askar (2005) "When individuals are uncertain about the nature of the task, their self-efficacy judgment can mislead them and this is why self-efficacy is a critical determinant of achievement." To Bandura (1995), four main sources can affect self-efficacy perception; good or bad experience, success or failures, social persuasion which is related to encouragement or discouragement, physiological and psychological factors such as fear or stress but among them individual's personal experience is seen as crucial. To Pajares (2002), "self-efficacy beliefs exercise a powerful influence on human action, and therefore it should not be overlooked in the teaching and learning process as if individuals believe they have the capacity to achieve the given task or approach a difficult one without fear they will attain their goals." It is also believed that people with a strong sense of self-efficacy volunteer and participate better in a task, (Kus 2005). Likewise, a Turkish proverb says "Believing is half of achieving."

Computers in language learning and computer self-efficacy

The concept of self-efficacy has been used in different disciplines as a basic for the belief and attitude, (O'Leary 1985; Lev 1997; Schunk 1985, cited in Oztiirk & Bozkurt, Kartal, Demir, Ekici 2011). Although the variety of technology and its extensive use has gone beyond one's imagination with the invention of iphones, webtools, apps etc, computers still remain in the core of teaching and especially language teaching. "Computer use has now become an influential component of second language learning pedagogy and educators recognize that utilizing computer technology and its attached language learning programs creates both independent and collaborative learning environments and provide students with language experiences as they move through the various stages of second language acquisition" (Kung, 2002, cited in Wang 2008). The rapid development and effective use of technology have added new sub definitions to the concept of self-efficacy; such as, internet self-efficacy, computer based-language self-efficacy, computer self-efficacy and so forth.

To Sam & et. al. (2005), computer self-efficacy is defined as a specific type of self-efficacy which means belief of one's capability to use the computer "to mobilize the motivation and cognitive resources (Wood & Bandura 1989:p.408-506, cited in Arani 2001). Participants with little confidence in their ability to use computers might perform poorly on computer-based tasks (Sam & et. al., 2005). Studies also state that good or bad computer experience may affect one's beliefs toward the use of computer in their learning', (Sam et. al. 2005), Brosnan (1998, cited in Sam & et.al. 2005) argued that "better computer self-efficacy could increase persistence in studying computing" and this could lead to increase persistence in other computer based subjects such as computer-based science, computer based-art design, computer based-language learning and accordingly this will facilitate learning of related subject. Miura (1987) stated that self-efficacy may play a crucial role affecting the acquisition of computing, however some factors such as ownership of a compute andthe frequency of use of a computer may also have an impact on self-efficacy which affects learning (Topkaya 2010).

Studies on Computer self- efficacy and language teaching

The use and usefulness of computers in language teaching is an undoubted fact (Egbert et al. 2002, Brinton 2001, Philips 2005, Thao 2003). Some studies have been conducted in Turkey on computer self-efficacy and its relation to certain variables. Ustuner et al. (2009) found a relationship between high attainment level and self-efficacy of secondary school English language teachers. Oztiirk & et. al. (2011) found a significant difference between prospective teachers' computer self-efficacy perception and grade level but no relationship between achievement and computer self-efficacy perception; their study also differed according to gender in favour of male and showed that the self-efficacy of prospective teachers who took part in the study are at medium level.

Hismanoglu (2011), examined the relationship between computer anxiety and computer attitude of prospective EFL teachers and found no correlation between computer ownership and degree of access to computers and computer attitude of the Turkish EFL students whereas Aydm (2007) found that EFL students have positive attitude in relation to the role of the Internet. Topkaya (2010) examined the computer self-efficacy and the self-efficacy perception of prospective EFL trainees in relation to different variables. She found that high self-efficacy level of Turkish students are at a moderate level and that the high self-efficacy could be related to owning a computer as owning a computer means having more experience and this could lead to high self-efficacy. It is even hard to imagine language learning without integration of technology and especially that of computers. However, in order for students to develop high self-efficacy in the use of the computer, the teacher themselves should notice the significant use of it in language learning and develop this as attitude. This idea triggered to further our understanding of and identify the prospective teachers' computer self-efficacy in relation to variables such as PC ownership, grade level, previous computer experience, time of first computer use, length of trainees' weekly computer use, and length of weekly internet use.

To Ozcelik & Kurt (2007, cited in Topkaya 2010), "the use of the computer in the classes is determined by the teachers' beliefs and this will eventually affect learners' beliefs. The teachers with high self-efficacy employ technology in the classroom more" According to Liaw (1997, cited in Ybarra and Green 2003) teachers should offer English language learners a language-rich environment in which students are constantly engaged in language activities, with computers facilitating this type of environment. The use of computers in class also helps students improve their technological ability and creates an effective learning environment, (Inal 2005, Yilmaz et al. 2004). It improves writing, (Thigpen 2002), and reading (Witkins 2005).

Warschauer (2008), in her research with 167 ESL and EFL students in 12 universities in Hong Kong, Taiwan and the U.S. found that the use of computers in writing classes positively affected students' motivation. Another study conducted by Lane et al. (2004) examined the relationship between academic performance and the self-efficacy perception of 205 postgraduates. The correlation results in the study indicated significant relationships between self-efficacy and self-esteem and likewise, multiple regression results indicated that self-efficacy mediated the relationship between performance accomplishments and academic performance.

The Purpose of Study

The purpose of this study was to determine prospective Turkish EFL teachers' computer self-efficacy in relation to the variables such as grade level, possession of a computer, first time use of computers, the length of computer and internet use weekly, and attendance at a computer training programme.

Method

This research is based on a descriptive study model and explores Turkish EFL students' computer self-efficacy perception and its relationship, if any, with the variables mentioned above. The participants are 305 Turkish ELF trainees attending 1st, 2nd, 3rd and 4th year classes at the ELT department in Buca Faculty of Education, Dokuz Eylul University, Turkey. The sampling group was chosen randomly.

2.1. Instruments and data analysis

A Likert type computer self- efficacy scale, whose alpha coefficient is 0.71, with five gradations (always, usually, sometimes, rarely and never) across 18 items, was used. The scale was developed by Askar and Umay (2001). In the five point Likert scale, the highest score that can be achieved across all 18 items is 90 (18x5=90), with the lowest being 18 (18x1=18), (see Chart 1). In the data analysis, arithmetic means, standard deviation, variance of analysis and Scheffe test were used. Each response to the questionnaire was calculated by multiplying the value of responses, which varies from 1 to 5, by the number of the questions as displayed below in Chart 1.

The instruments used in the study are:

1. Computer self-efficacy Perception Scale

2. Personal Data Form: the participant's grade level, time of first computer use, previously computer experience,

PC ownership, the frequency of computer and internet use were considered,

Research questions

This study addresses the following questions:

1. What is the level of self-efficacy perception of Turkish ELT trainees?

2. Does computer self-efficacy perception of trainees vary by their grade level?

3. Does computer self-efficacy of trainees vary according to PC ownership?

4. Does computer self-efficacy perception of the trainees vary on previous experience (previously attending a computer course)?

5. Does computer self-efficacy perception of trainees vary dependent on the time of first computer usage?

6. Does computer self-efficacy perception of trainees vary by frequency of computer use?

7. Does computer self-efficacy perception of trainees vary dependent on frequency of internet use?

Findings

Table 1 shows slight differences in arithmetic mean between the classes.

The arithmetic mean of the total sample is 54.73. This would indicate that the self-efficacy perception of Turkish students is at a moderate level. ANOVA was utilized to determine whether the differences in arithmetic mean between the classes are meaningful.

Table 2 indicates no significant change in computer self-efficacy perception of trainees in relation to grade level (p>.05).

Table 3 shows no significant difference in computer self-efficacy perception of trainees by PC ownership, despite the arithmetic means of the students who own computers being relatively higher than those who do not. However, p point does not change significantly.

Table 4 indicates that there is no a significant difference in computer self-efficacy perception of trainees dependent on their previously attending a computer course.

Computer self-efficacy perception of trainees using a computer for the first time in primary school shows difference, that is, the self-efficacy perception of trainees using a computer for the first time in primary school is relatively higher than the others. ANOVA was used to determine whether the difference between the arithmetic means and computer use period is significant, and Scheffe test was employed to determine the differences between the groups in terms of stages of education.

Computer self-efficacy perception scores of trainees in terms of their length of computer use show difference in favour of the students using computers for the first time in primary, secondary and high schools. To determine the group differences, Scheffe test was used and the results of the test displayed in Table 7.

The results indicate a significant difference between the length of times devoted to computer use. To determine whether the differences in arithmetic means are meaningful ANOVA was used and to determine the differences within the groups Scheffe test is utilized. The results are presented in Table 8.

Table 8 indicates a significant difference in the computer self-efficacy perception of trainees in relation to the length of their weekly computer use. To determine the source of the difference Scheffe test was utilized.

The means related to the hours of weekly internet use shows that computer self-efficacy perception scores differ according to the length of the Internet use. To determine if there is a significant difference between arithmetic means ANOVA was used and the results are presented in Table 10.

Table 10 indicates that there is not a significant difference between trainees' computer self-efficacy perception in terms of frequent use of weekly internet use, (p >.05).

Results and discussion

Results show that prospective Turkish EFL teachers' computer self-efficacy perception is at a moderate level (X 54.73). Although this finding is not very high one can still say that Turkish ELT trainees have the necessary attitudes and perception to integrate computers in their classes. To increase the trainees' perception and help them improve their computer skills, computer courses taught at the faculties in Turkey should be tailled with English language teaching curriculum to teach how to integrate these skills into their teaching practice.

The trainees' self efficacy does not show any significant difference by grade level. This finding tallies with Topkaya's (2010) study of 288 EFL trainees which also found their self-efficacy perception to be at a moderate level. The results between the groups show that the third year students' self-efficacy perception is at the lowest, and first year students' at the highest level. This result does not reflect the expectations as the third and fourth year students were expected to have higher self-efficacy perception due to their increased levels of computer experience. It was expected that the older students gain higher levels of computer exposure in senior classes and would affect their self-efficacy perception, as mentioned in the earlier studies (Akkoyunlu & Orhan, 2003; Akpinar, et al., 2007).

No significant difference was found between prior computer experience and self-efficacy (see Table 4) as mentioned in the earlier studies, Askar & Umar (2001, Akpinar, et al. (2007).

The relationship between owning a computer and the level of computer self-efficacy was also explored; however, computer ownership does not affect computer self-efficacy perception in this study. A considerable number (50%) owns personal computers, thus having access to computers outside the workplace.

Although studies such as Hasan (2003) and Askar & Umay, (2001) found that attendance at a computer course positively affects computer self-efficacy perception, this study did not validate this finding. However, one possible explanation for those who had not previously attended a computer courses but who showed high self-efficacy perception, is the ease of access students now have to computers and the internet, with this increased accessibility being the potential cause of the difference.

The participants started using computers in primary school were found to have the highest self-efficacy perception compared to those who started at later stages of education. A meaningful difference was found between students using computers for less than 1 hour; for 1 to 10 hours, for 11 to 20 hours and 21+ hours a week. Self-efficacy perception is higher among the students using computer 21 and over hours per week. That is self-efficacy perception scores are the highest among the students using computers 21 hours or more weekly. Concomitantly, computer self-efficacy increases as duration of weekly computer use increases. Likewise, the self-efficacy perception of the participants using 21+ hours of internet is the highest and self-efficacy perception decreases in line with decreasing hours of internet use. This shows that the self-efficacy of students using computers and Internet more often is higher than those who do not. Accordingly, the longer time is spent on computers and Internet the higher computer self-efficacy will be. Based on this finding, one can posit that early experience of computer use, alongside frequent computer and the Internet use can positively impact on students' computer self-efficacy perceptions. This finding is consistent with the study of Akpinar and et al. (2007). Yang et al. (2007) found that the length of internet use significantly influenced both self-efficacy perception and language use. Given the teacher's guiding role and the rapid development of technology in learning, it is essential that teachers themselves have high computer self-efficacy perception in order to be able to effectively use technology in classroom as teachers' self-efficacy may eventually affect their students' self-efficacy. To have good attitudes and high self -efficacy are crucial in terms of integrating computer in foreign language classes as Turkish ELT students don't have much opportunities for practicing their language skills but this integration in a sense can provide this opportunity.

4.1. For Further Studies

Beyond the current findings, given the effects of individual attributes in learning it will be of value to study factors such as achievement, attitude, gender, and age which are not included in the present study but that may affect self-efficacy perception and its effectiveness in EFL classes. Age related studies may reveal interesting results as now the learners are considered as native digitals and non-native digitals.

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Dr. Sevim Inal

Canakkale Onsekiz Mart University

* Unknown Date
Table 1. Arithmetic means and standard
deviation of computer self-efficacy
perception by grade level.

Grade level          N    [bar.X]    SS

1st year students   60     55,63    9,82
2nd year students   58     55,00    12,49
3rd year students   86     53,91    9,77
4th year students   101    54,74    10,45
Total               305    54,73    10,53

Table 2 Analysis of Variance related
to computer self-efficacy perception of
trainees by grade level.

Source of the     Sum of     Sd    Mean of    F      P
variance          squares          squares

Between groups    109,818     3    36,606
Within groups    33639,670   301   111,760   ,328   ,805
Total            33749,489   304

Table 3 Comparison of computer self-
efficacy perception of trainees by PC
ownership

owning PC    N    [bar.X]    SS       t      P

YES         156    55,36    11,61
                                    1.070   .285
NO          149    54.07    9.26

Table 4 Comparison of computer self-
efficacy perception according to trainees'
previous computer experience.

Attending computer    N    [bar.X]    SS        t       P
courses previously

Yes                  93     54,49    10,96
                                               ,263    ,793
No                   212    54,83    10,36

Table 5 Arithmetic means and standard
deviation related to computer self-efficacy
perception of trainees in terms of their
first time of computer use.

First computer use    N    [bar.X]    SS

Primary              39     60,07    12,06
Secondary            134    53,35    10,51
High School          114    54,25    9,191
University           18     56,44    12,18
Total                305    54,73    10,53

Table 6 Analysis of Variance results of
trainees' self-efficacy perceptions in terms
of length of computer use.

The source of    Sums of     Sd    Means of     F      P
the Variance      square           squares

Between groups   1445,846     3    481,949
Within groups    32303,642   301   107,321    4,491   ,004
Total            33749,489   304

Table 7 Arithmetic means and standard
deviation related to computer self-efficacy
perception of trainees in terms of their
weekly computer use.

hours of computer    N    [bar.X]    SS
use weekly

Never               10     49,40    11,65
1-10                197    54,24    8,90
11-20               61     53,80    11,52
21 +                37     60,32    14,40

Table 8 ANOVA results related to
differences in terms of length of trainees'
weekly computer use and computer self-
efficacy perception.

The source of   Sums of     Sd    Means of     F       P
the Variance     squares          squares

Between         1541,037     3    513,679    4,801   ,003 *
groups
Within          32208,452   301   107,005
groups
Total           33749,489   304

Significant at * p < 0.01 level

Table 9 Arithmetic means and standard
deviation related to computer self-efficacy
perception of trainees in relation to the
length of weekly internet use.

hours of internet      N    [bar.X]    SS
use weekly

Never                  7     52,71    12,09
1-10                  208    54,03    9,05
11-20                 63     56,46    12,52
21 and more/onwards   27     56,59    14,89

Table 10 ANOVA results related to
trainees' computer self-efficacy perception
in terms of hours of weekly internet use.

Source            Sums of            Means
of the variance    squares    Sd      of        F      P
                                    squares

Between groups     410,198     3    136,733
Within groups     33339,290   301   110,762   1,234   ,297
Total             33749,489   304

Chart 1. Scoring and value for each
answer in the scale

Answer      Value   Calculation   Total score
category

Never         I        1x18           18
Rarely        2        2x18           36
Sometimes     3        3x18           54
Usually       4        4x18           72
Always        5        5x18           90
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Date:Mar 22, 2015
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