From the past to present, ongoing scientific and technological advances have led to changes in social structure. For the past two decades, the volume of information and knowledge in the world has increased, making the world a knowledge-based society (Mehdi and Sadat, 2011). Knowledge has become an important factor that determines the strength of any com-munity. Information producing communities have a voice in the world. To get to this level, individuals living in these communities should be involved in research, have access to   life-long   resources and information and above all, should be able to learn for life.

With the emergence of life-long learning concept, factors such as differences in the learning needs of individual financial problems, changes in education management and communication, increase in tech-nological possibilities, opening of new career area, increased competition in business life, changes in the expectations of employees and the necessity of acquiring new knowledge and skills play a significant role (Knapper and Cropley, 2000). Individuals’ renewal of existing knowledge and the requirement of developing their skills have made life- long learning mandatory (Gündüzet al., 2009). Peters (2009) indicates that life-long learning would manifest quickly in all educational institutions, and traditional institutions would have to keep up with this. The 21^st century successful people and life-long learners are required to constantly renew themselves (Erdogan, 2002).

The European Commission (2001) defines life-long learning as “all learning activities undertaken throughout life, with the aim of improving knowledge, skills, and competence within a personal, civic, social, and/or employment-related perspective”. Life-long learning is a deliberate learning that can and should occur throughout each person's lifetime (Knapp and Cropley, 2000). It involves people of all ages learning in a variety of contexts - educational institutions, work, home and leisure activities; it focuses mainly on adults returning to organised learning rather than the initial period of education or incidental learning (Schuller and Watson, 2009). Life-long learning means to invest more on knowledge and human beings; to promote basic knowledge and acquire skills, including digital writing and reading; to expand flexible and innovative learning opportunities (Lambeir, 2005; Akkoyunlu, 2008; Polat and Odabas, 2008). The aim of basic education is to train individuals who are life-long learners. Budak (2009) says individuals indulging in life-long learning must have specific skills (Commission Européenne, 2008, as cited in Budak, 2009): The four main language skills required for proficient communication, adequate communicate in a foreign language to a level of understanding other cultures, have basic competence in mathematics, science and technology, able to make ingenious use of information to adapt to digital technology, be involved in individual or group learning, have organizing and learning competence, be able to effectively participate in professional and social life, have  creativity competence, be involved in innovation, risk-taking, project development and implementation of enterprise and have self-expression in artistic ways.

Besides,Kanpper and Cropley (2000) state that individuals with life-long learning skill should be individuals that can plan their own life-long learning, determine learning skills, learn actively, learn in formal and informal context, learn from their peers, teachers,  integrate different subject areas when required and use a variety of teaching strategies for different situations. Information society facilitates individuals’ lifelong learning skills and ability to cope with changes (Demiralay and Karadeniz, 2009).Learning is a process of mental and social change in one’s entire lifetime (Sharples, 2000). In today’s rapid and developing technology, the ingenious use of digital technologies as part of the skills of individuals involved in life-long learning is expected. Digital technologies are used in many areas such as communication, research, polling and learning, and have led to a change in the skills needed in these areas. Future successful people will be individiuals who can use technology effectively to access information, solve problems and learn on their own (Demirel, 2009). 

Especially, access to information using computers is the most common means of getting knowledge, skills and attitudes expected to affect the level of life-long learning. This is reflected in different studies. Kirby et al. (2002) state that there is a lifetime prevalence of individuals’ access to information, the workforce has increased, while computers improve the quality of individuals’ learning by saving time and allowing them to work more efficiently. Gunduz et al. (2009) argue that to be able to perform life-long learning, e-learning environment is needed, which is not dependent on time and place. Laal (2011) argues that online courses can replace more traditional approaches to teaching and learning in the 21st century; this can be done by drawing on the experience of educational facilitators worldwide and evaluation of learners’ experience with computer mediated communication. World Wide Web (WWW) has increased noticeably, particularly in higher education institutions.People can create learning environments; they use the most portable and available tools for many purposes in everyday life. This makes persistent learning to occur.

For individuals, life-long learning starts at school and continues in the family environment to gain skills. In the school atmosphere, the availability of the appropriate curriculum and the people responsible for the teaching and learning process will make the students to acquire certain skills. During the skills acquisition phase, teachers are the ones who provide the information the students need and also take the necessary measures to control it (Isik, 2013). With time, as the classrooms continue to become more inclusive and diverse, the number of students needing differentiated and personalized attention increases, as do the pressures on teachers to meet their needs (Looi et al., 2009).The teachers increasingly play the role of a planner, developer, organizer, educator, counselor, diagnostician, therapist and forecaster; coordinator, researcher (Jovanova-Mitkovska and Hristovska, 2011).In this regard, there are important roles and responsibilities of life-long teachers in creating a society of individuals with learning skills. Especially, the task of primary school teachers involved in the acquisition of basic skills such as learning is greater.

Teachers’ ability to inculcate these skills into their students is very important. If the teachers do not have the knowledge or skills, they will not be able to give them to their students. Thus, it is important for our teachers to have these knowledge and skills. At the same time, these knowledge and skills should also be supported by the faculties of education as teacher training institutions. As a result, the study tries to identify primary school teacher candidates’ maintenance of life- long learning and their perception of computer self-efficacy.

In several studies (Mehdi and Sabad, 2011;Looi et al., 2009;Dearnley et al., 2008;Nordin et al., 2010), it was argued that using computer affected learning and life-long learning. So, the aim of this study is to determine the relation between primary school teacher candidates’ propensity for lifelong learning and their perception of computer self-efficacy. 

In this section, the research model, the working group, the data collection tools and data analysis will be described.

Model of research

The main purpose of this study is to determine primary school teacher candidates’ lifelong learning propensity and perception of computer self-efficacy and the relationship between them. General screening model was used (Karasar, 2005). The research is a descriptive study, which aims to reveal the current situation and give detailed description (Cepni, 2005). In this study, the difference between primary school teacher candidates’ tendencies of lifelong learning and their perceptions of computer self-efficacy was examined based on independent variables such as sex, class, type of high school graduated from, location of the high school, general point average, teachers’ satisfaction from studying primary school teaching and desire to obtain postgraduate education. While independent variables were determined, the study of Gunuc et al. (2012) and samples’ characteristics were taken into account. The study’s design is correlational. Correlational studies aim to show correlational relationships between variables (Balci, 2011). So, it is determined that there are correlational relationships between the primary school teacher candidates’ lifelong learning tendencies and their perceptions of computer self-efficacy.

Working group

The study group consists of Faculty of Education students doing undergraduate programs at Bartin University, in 2014-2015 academic year.  164 students of 92 (56.10%) who continued in this program were enrolled in the working group. Details of the study group are shown in Table 1.

From Table 1, it is seen that of the 92 people in the working group, 68  (73.91%) were women; 24(26.09%), men; 31(33.70%), 1^st grade students; 26(28.26%), 2^nd grade students; 22(23.91%), 3^rd grade students; 13 (14.13%), 4^thgrade students; 46(50.00%), high school graduates; 36(39.13%), Anatolian High School graduates; 10(10.87%), other high schools’ graduates; 29(31.52%), graduated from high schools in big cities, 25(27.17%), graduates of high schools in provinces; 38 (41.30%), graduates of high schools in districts; 40(43.48%) have GPA between 3.01 and 4.00; 52(56.52%) have GPA between 2.01 and 3.00; 70(76.09%) are satisfied with studying primary school teaching; 19(20.65%) are partially satisfied with studying primary school teaching; 3(3.26%) are not satisfied with studying this course; 36(39.13%) want to do postgraduate education; 45 of (48.91%) are undecided; 11 (11.96%) do not want to do postgraduate education.

 

 

Data collection tools

Personal information questionnaire, Lifelong Learning Trends Scale developed by CoskunDiker (2009) and Computer Self-Efficacy Scale developed by Askar and Umay (2001) were used to collect data.

The personal information questionnaire used in the study contains the following items: sex of the students, classes, types of high schools graduated from, location of the high school, grade point average, being pleased to study primary school teaching or not; there are 7 items in the questionnaire on determining the students’ desire for postgraduate study.

The lifelong learning trends motivation scale developed by CoskunDiker (2009) consists of 4 parts: motivation, persistence, deprivation and lack of interest in learning arrangement. It is a 3 points-likert scale consisting of: "Very satisfied", "Partially satisfied" and "not satisfied". In the first two dimensions of the scale, 12 elements are positive and 15 substances are negative; the scoring was done accordingly. The reliability of the scale was calculated as 0.89 (CoskunDiker, 2009), which beats Nunnaly (1978)’s 0.7 acceptable reliability coefficient.

Computer self- efficacy scale developed by Askar and Umay (2001) was prepared on a 5 Likert point. There are 10 positive and 8 negative material substances in the scale, and scoring was made ​​accordingly. The reliability of the scale was calculated as 0.71 (Askar and Umay, 2001). According to Nunnaly (1978), reliability coefficient of this scale is acceptable. Further information on the lifelong learning trends and computer related self-efficacy scales is shown in Table 2.

 

 

As seen in Table 2, in the lifelong learning trends scale, motivation dimension consists of 6 items; persistence dimension, 6, regulation of learning dimension, 6. The lowest score that can be taken from these dimensions is 6, the highest score is 36, while the median score is 21.  In the deprivation dimension, the lowest point obtained is 9, the highest score is 54, and the median score is 31.5. The lowest points that can be taken from life-Learning Trends Scale is 27, the highest score is 162, while the median point of the scale is 94.5. The lowest possible score of Computer Self Efficacy Scale is 18, the highest score is 90, and the median point of the scale is 54.

Data analysis

Normality analysis was conducted to know if there is a normal distribution for each variable of the data collected in the research.  After the analysis, the non-parametric tests were performed using the Mann-Whitney U and Kruskal-Wallis tests because Life-long Learning Trends analysis did not demonstrate normal distribution of the total score of dimensions and sub dimensions of the variables.

The computer related self-efficacy scale scores exhibit normal distribution based on the variables, and variances were homo-geneous. So analyses were performed using t-test and one-way analysis of variance parametric test. After reaching a significant difference in the results from one way variance analysis, Bonferroni test is preferred to post-hoc tests. As one of the scales used could not give normal distribution of the scores of the variables, Spearman rank difference correlation factor was calculated.

The results of Mann Whitney U test which was applied to determine whether the points from lifelong learning trends scale differed according to gender and GPA variables are shown in Table 3.

 

 

In Table 3, the values indicate that students’ life-long learning propensity to study primary school teaching program does not vary according to gender and GPA. The lifelong learning trends descriptive statistical results obtained from the motivation size and the results of the Kruskal-Wallis test conducted to determine whether it differed according to variables are shown in Table 4.

 

 

In the motivation dimensions, gender, grade point average, class, type of high school graduated from, location of the high school, satisfaction from studying primary school teaching and desire to study postgraduate education seem to be close to each other. This ​​indicates that the  students’  motivation  to  do  life-long  learning  is very high (Table 4).

The values in Table 4 indicate that, the students’ motivation for lifelong learning vary according to class, type of high school graduated from, location of high school, and satisfaction from studying primary school teaching. According to the analysis results, motivation of the students to study primary school teaching differs according to their desire to do postgraduate education in a meaningful way (p<0.050). These differences were formed between those who wish to receive postgraduate training and those who think of postgraduate education. When the average scores are examined, the motivated people who want to get postgraduate education ( =33.86) seem to be higher than those who think of getting post graduate education ( =31.45).

Descriptive statistical results of the persistence dimension and Kruskal-Wallis test conducted to determine whether these points differ according to variables of the score or not are shown in Table 5.

 

 

When the values are examined in the Persistence dimension, the scores obtained in the lower variable (GPA) seem to be close to each other (Table 5). The scores of 4th grade students, high school students and Anatolian High School graduates, students who have completed high school in the country, students who are satisfied partially from studying primary school teaching and those who want to get postgraduate education are higher than the others. Generally, the values ​​indicate that the students’ persistence scores are high.

The students’ persistence scale scores vary according to class, type of high school graduated from, location ofthe high school and being satisfied with studying primary school teaching. From the analysis results, it is seen that, there is a meaningful difference between the scores of the students studying primary school teaching and the students who want to get postgraduate training (p<0.050). These differences were formed between the students who wish to receive postgraduate training and those who think of getting postgraduate.When the average scores were examined in the persistence scale, the ratings of those who want to get postgraduate education ( =31.03) seem to be higher than those who consider taking post-graduate education ( = 25.73).

Descriptive statistical results of the scores obtained from deprivation of learning regulation and Kruskal-Wallis test performed to determine whether it differed according to variables of the points are shown in Table 6.

 

 

In the deprivation of learning regulation scale, female teacher candidates’ scores are higher than those of male teachers. Teachers with general point average of 3.01 and 4.00 are higher than the teachers with 2.01 and 3.00. 1; and 4th year students are higher than 2^nd and 3^rd year students (Table 6). Anatolian High School graduates are higher than graduates from high school and other schools. Students who completed high school education in provinces and districts are higher than those who completed theirs in cities. Students who are satisfied with studying primary school teaching are higher than the ones who are partially satisfied and dissatisfied with the discipline. Students who want to receive postgraduate education are higher than those that do not want. Generally, the values ​​indicate that the students’ desire for learning of skills is higher. Values ​​in Table 6 show that the students’ editing skills differ according to class, type of high school graduated from, location of the high school, the desire to get post graduate education. According to the analysis results, it is determined that the organizational reading skills of the students studying primary school teaching program differ in a meaningful way from the students who are satisfied with studying primary school teaching (p <0.050).These differences were formed between the students who are pleased with studying primary school teaching and the students who are satisfied partially. When tbe average scores were examined, it was seen that the students who are satisfied with studying primary school teaching ( =30.81) seem to be higher than those who are satisfied partlially ( =25.33).

The Lifelong Learning Trends Scale of deprivation descriptive statistical results and Kruskal-Wallis test results conducted to determine whether it differed according to the points of variables are shown in Table 7.

 

 

When the values ​​in Table 7 were examined, it was observed that inLifelong Learning Trends Scale of deprivation, the higher average grade, 3rd grade students, Anatolian High School graduates, those who have completed high school in big cities, those who are partially satisfied with studying primary school teaching and those who want to get postgraduate training scores are higher than the others. The values show that generally the students are keen on learning.

In Table 7, the values show that the students’ curiosity for life-long learning does not vary according to class, type of high school graduated,  location  of  high  schoole, the state of being happy studying primary school teaching and the desire to have post graduate education.

The total scores of descriptive statistical results and the determination of whether scores differed according to variables using the Kruskal-Wallis test results are shown in Table 7.

When the values are examined in Table 8, those with higher GPAs, 3rd grade students, Anatolian High School graduates, those who have completed their education in high school in big cities, those who are pleased to study primary school teaching, and those who want to get post graduate education were found to be positive than others. The values ​​show that the students have positive attitude towards lifelong learning trends.

 

 

Students’ desire to study primary school teaching program for life does not vary according to class, type of high school graduated from, location of the school, the state of being pleased with studying primary school teaching and the desire to get post graduate education.

The results of t test performed to determine whether computer Self-Efficacy Scale points differed according to variables or not are shown in Table 9.

The values in Table 9 show that the perception of the students doing primary school  teaching  programs  about values

 

 

show that students’ perception of computer self-efficacy is high, generally.  Table 10 shows that the students’ desire for life-long learning does not vary based on class, type of high school graduated from, location of school, and the desire to get post graduate education. At the end of the analysis results, the students’ perception of computer self-efficacy differred in a meaningful manner according to the variable of being pleased with studying primary school teaching (p<0.050). This difference was found among those who are pleased with the primary school teaching, ( =60.11), those who are not satisfied with the  primary  school  teaching  ( =59.16)  and,  those who are partially satisfied with the primary school teaching ( =41.67). =59.16). When the average scores were analyzed, it was seen that those who were satisfied partially with studying primary school teaching had the lowest average.

 

 

The Spearman rank different correlation analysis results are shown in Table 11, which was conducted to determine the relationship between the scores they received from the sub-dimensions of computer Self-efficacy and students’ lifelong Learning trends scale.

 

 

The values in Table 11 show a low and non-significant relation between the scores obtained from computer  self-efficacy scale of the students and that of motivation and persistence dimensions; there was also a  low and non-significant relation between the students’ computer self efficacy scale and  deprivation learning regulation scores. The results of motivation dimension scores of 11% (r = 0.341), persistence dimension scores of 13% (r = 0.364), worrying over deprivation scores of 6% (r = 0.253) and a lifetime learning curve scale of 10% (r = 0.316) can be explained by the score of computer self-efficacy scale.

In this work, it was determined that the desire for lifelong learning by the students studying primary school teaching does not change according to gender and grade point average. Kirby et al. (2010) determined that university students’ lifelong learning tendency does not differ according to age and gender. Kılıç and Tunceli (2014), in their research with teachers, have set that lifelong learning trends are significantly more favorable to female teachers than male teachers. In this sense, it can be said that teachers carrying on their education for the future are doing self –development, irrespective of the sex.

Motivation scale in the sub-variables points was determined to be close to each other. The values ​​indicate that students’ motivation for lifelong learning trends is very high. The students’ motivation does not differ according to  class, type of high school graduated from, location of high school, being satisfied with studying primary school teaching, but it differs significantly according to the students’desire to obtain postgraduate education (p<0.050). This difference was formed between the graduates who wish to receive post graduate education and those who think of postgraduate education.Results obtained show that the students with high motivation for life-long learning want to take postgraduate education.

The point of the students’ persistence for life-long learning is high. Their persistence does not differ according to class, type of high school graduated from, location of high school, being satisfied with studying primary school teaching, but it differs significantly according to the students’desire to obtain postgraduate education (p<0.050). This difference was formed between the graduates who wish to receive post graduate education and those who think of postgraduate education. Results obtained show that the students with high persistence for lifelong learning want to obtain post-graduate education.

It was shown that the candidates’ skills of editing are high. This does not differ according to class, type of high school graduated from, location of high school, being satisfied with studying primary school teaching, but it differs significantly according to the students’desire to obtain postgraduate education  (p<0.050). This difference was formed between the graduates who wish to receive post graduate education and those who think of postgraduate education. Results obtained show that the students with high skills of editing want to take postgraduate education.

It was found that generally primary school teacher candidates are keen on learning and their lifelong learning trends are positive.  Coskun (2009)’s findings revealed that university students’ life long learning trend was not at the desired level. The curiosity of the students studying primary school teaching education for life does not differ according to class, type of high school graduated from, location of high school, being satisfied with studying primary school teaching and desire to do postgraduate education.

Kara and Kurum (2007) concluded in their study that for primary school teaching candidates,  life long learning is necessary and important for rapid increase of information and people’s adaptation to rapid developments. Kilic and Tuncer (2014), in their study, identified that teachers who have been working for 20 and more years have more negative attitude towards lifelong learning than the other teachers. In the literature, it is discovered that young teachers’ and teacher candidates’ lifelong learning ideas as individuals who learn their whole lives seem to be similar. Primary school teacher candidates’ perspectives tend to be positive towards life-long learning and whatever their situations, their ideas are not differentiated. This information in the literature supports this ​​dimension of the present paper.

The students’ perception of computer self-efficacy is high. This does not differ according to gender, GPA, class, type of high school graduated from, location of high school, being satisfied with studying primary school teaching and the desire to study post graduate education. It differs according to the students’ status in a meaningful way (p<0.050, _Y=60.11, _P=59.16, _N=41.67).

Akkoyunlu and Kurbanoglu (2003), in their study, determined that the computer self-efficacy of teacher candidates studying Computer and Instructional Tech-nology Teachers, Science and Math Teaching Programs is at the medium level, and sswhen grade level increases, self-efficacy also increases.Tekinarslan and Gurer (2009) have shown that the teachers doing computer course have high computer self-efficacy in a meaningful way, but is based on gender, statistically and significantly. Today, especially in faculties of education, many projects on technological development have been conducted by the Ministry of Education train teachers. It is very important to support school courses with technology materials. 

There is a positive and significant correlation between the  students’ score obtained from computer self-efficacy scale with motivation and persistence dimension scores; and also between it and deprivation scores, but on  ave-rage level; there is non-significant correlation between the students’ computer self efficacy and deprivation scores

The results of motivation dimension scores of 11% (r=0.341), persistence dimension scores of 13% (r=0.364), deprivation scores of 6% (r=0.253) and 10% of lifetime learning scale scores (r=0.316) can be explained by the score of computer self-efficacy scale.  The results obtained in this work have proven there is a significant correlation between computer self-efficacy and life-long learning tendency.Similarly, in their study, Kirby et al. (2002) stated that there is a significant relationship between life-long learning skills and computer use skills.  This is the reason for the formation of the lifelong learning concept that depends on the extent of the use of information technology.

The author has not declared any conflicts of interest.