Humankind has always made efforts to keep up with the age and acquire any kind of cultural accumulation. And this is possible as individuals perceive the information that develops, deepens and changes day by day.  One of the various ways of perceiving information is reading.

Reading not only establishes a bridge between the past and present but also enables individuals to have a place for themselves in their social surrounding. Here, the purpose for reading does not mean studying at school or reading course books, but means a way of studying related to adapting to the society and being at peace with the self (Yakıcı et al., 2015).

In recent years, these properties that can be gained through reading, contribute to raising individuals who can understand what they read. In this sense, the countries that want to determine the academic success of their students at a national level have revised their systems by participating in some assessment studies (BerberoÄŸlu and Kalender, 2005). As known, Program for International Student Assessment (PISA) project is remarkable as one of these studies.

The main purpose of PISA project is to put 15-year-old students to knowledge and skill tests such as reading skills, mathematic literacy and science literacy once every three years since 2000, and to achieve results from the data obtained in these tests (OECD, 2005).

As an international reference, the main purpose of PISA is to measure to what extent the educational systems of any countries have educated the young in age group of 15. Organisation for Economic Co-operation and Development (OECD) countries and several other countries have recently attended PISA which was first held through the participation of OECD countries in 2000. Totally, 65 countries including 34 OECD countries attended  PISA 2012, whose results were explained on 3rd December, 2013 (China did not join PISA as a country; the attendance was from the economies depending on China).

In 2012 measurement, data were collected from 510.000 students representing 28 million young individuals at the age group of 15 living in these countries. One of the main reasons why PISA is an international reference is that science, mathematics and reading skills it measures are the factors that directly determine economic productivity. In PISA, which basically focuses on the necessary skills to take part in economic life, not only the basic skills but also different skills like critical thinking, analysis, synthesis and creativity are measured (Şirin and Vatanartıran, 2014).

This project started with reading skills test in 2000. The first three-year period ended with science literacy test performed in 2006. 2000 was tagged the year of reading skill, 2003 was for mathematics literacy and 2006 for science literacy. Although all three tests were included in each of these years, those areas were prominent for the above mentioned years. The second three-year period started in 2009 through reading skill tests, and these tests continued following the same order and system (Batur and UlutaÅŸ, 2013).

In PISA, 7 competence levels related to reading skill are determined. The students who can accurately answer the items at the 6th level can cope with the concepts not expressed clearly within the text, and can interpret the abstract concepts. Considering several criteria variables, they can make critical assessments beyond the information in the texts; they can make inferences or can hypothesize.

The students who have success at 1b level can find information expressed clearly in a short, simple text supported mostly with illustrations. The students at 1a level can clearly express one or more independent information in a text; can understand the topic of the text and purpose of the author, and can establish relationship between the information in the text and daily information known commonly. Skills and thinking processes measured in reading areas in PISA can be listed as: accessing and remembering information, gathering information together and interpreting, reflecting their ideas and assessing the text.

Turkey lately got acquainted with PISA in 1997 when the first-period pilot test studies started. They could not participate in both pilot and formal test studies due to some reasons that arose from Education Research and Development Directorate’s focusing on other projects (Savran, 2004). Turkey joined PISA project in 2003, and has attended all studies carried out since then.

Tests and questionnaire of PISA 2013 project including Turkey were given to 4855 students studying at 12 elementary schools and 147 high schools chosen randomly from seven geographical regions (EARGED, 2005). In this implementation, Finland had the highest success in reading with 543 points, Turkey took the 34^th rank with average score of 441 among 40 countries.

PISA 2013 results were used in shaping Curriculum Reform that started in 2004. Elementary and secondary education curriculums developed according to the obtained results were put into practice, and it was explained that assessment of these curriculums would be made with PISA 2006, and these curriculums would be developed according to the results (EARGED, 2005).

In PISA 2016, Korea ranked first, with average score of 556; and Turkey ranked the 37^th,with average score of 447 among 56 countries (EARGED, 2010a), and it was at the 39^th rank among the countries with 464 average score in PISA 2009 (EARGED, 2010b).

According to PISA 2003 results, two out of third (67.7%) of the students who took the exam (EARGED, 2005) in Turkey scored below the determined proficiency levels. It was observed that this rate decreased to 63.2% in PISA 2006 (EARGED, 2010a), and to 56.7% in PISA 2009(EARGED, 2010b). Moreover, reading skills of 3.8% of the students in PISA 2003 (EARGED, 2005), of 2.10% of the students in PISA 2006 (EARGED, 2010a), and of 1.8% of the students in PISA 2009 were included in the 5th competence level. And it was remarkable that there was no student from Turkey in the 6^thcompetence level in 2009 PISA (EARGED, 2010b).

It was significant in 2006 and 2009 that the number of students below basic competence level decreased. Increased average scores were provided, but it was noteworthy that the number of students at competence levels defined with high level reading skills decreased at the same time. In terms of PISA reading skill implementations, the increase Turkey had in average scores was associated with the motivation created throughout the country, with new Turkish curriculum arranged according to Curriculum Reform in 2004. Especially, the 17-point increase provided in PISA 2009 compared to the previous one should not be ignored. However, as indicated by the aforementioned statistical information, it has been a fact that this increase was at basic and medium levels of reading skill, and decrease instead of increase was observed in high-level skill scores (Batur and UlutaÅŸ, 2013).

When the results of PISA 2012 organized by OECD were  considered,  it  was  noticed  that  Turkey  had  475 point in reading skills. This indicated that Turkey increased the score (464 point) in 2009, and had an 11-point increase.

However, the recently held PISA 2015 results were not pleasant for Turkey. When the results were analyzed, it was possible to notice that the rank of Turkey decreased. Whereas the reading score of Turkey in 2003 was 441, the score decreased to 428 in 2015 (Özdemir, 2016).      

The reference point of this study is that Turkey does not have the desired success in reading skills as seen in PISA results. The primary and most efficient environment for the students to acquire reading skills is school. The pre-service teachers studying at Educational Faculties are required to have knowledge and skills on how they will make their students gain and develop reading skills. Reading motivation has a significant effect on acquiring reading skills. For that reason, reading purposes, reading tendencies and the time students take for reading are closely correlated with motivation.

Motivation positively affects several traits of students depending upon several behaviors such as attitude, and interest towards reading. Interested readers are motivated in reading in various ways, and they gain new understanding from their previous experiences. They can participate in different social interactions through the help of reading. The concept of “reading motivation” has been revealed by reading educationalists that motivation should be domain-specific. Reading motivation is a way used to measure the willingness of individuals to read, makes individuals to have continuous reading behaviors and reveals the deficiencies of individuals in reading (Aydemir and Öztürk, 2013).

It is possible to see several studies on reading motivation in the literature. In his research, Yıldız (2010) investigated the reading motivations of the 3rd, 4th and 5th grade elementary school students. According to the research results, external motivation was more efficient in female students’ tendency towards reading compared to the male students; and as the level of grade increased, internal and external motivation towards reading decreased.

Construct validity of the Reading Motivation Profile scale including 20 items and adapted into Turkish by Yıldız (2010) was tested using confirmatory factor analysis. At the end of the adaptation, a scale form of 18 items indicating the value towards reading in 9 items and indicating the readers’ sense of self factors in 9 items was obtained. This scale was used to investigate to what extent students valued reading and to what extent they considered themselves adequate as a reader.

Data were collected from 2015 individuals in the study carried out by Yıldız et al. (2013) in which they adapted Adult Reading Motivation Scale. The scale included 4 factors and 21 items. As a result of the analyses, the scale was finalized with 19 items. For the validity study of the scale, confirmatory factor analysis was performed. Within the scope of  reliability  study,  test-retest   method was used, and Cronbach alpha internal consistency coefficient was calculated. At the end of the study, a valid and reliable scale used for analyzing the reading motivations of adults was obtained.

Ä°leri and Öztürk (2013) developed a reading motivation scale for determining the reading motivations of elementary school students towards texts. Data of the study were collected from 259 fifth grade students. In this study, a 60-item pool was created from several studies (Wigfield and Guthrie, 1995; Chapman and Tummer, 1995; Gambrell et al., 1996) in the literature. The scale items decreased to 30; and after asking the opinions of experts there were 27 items.

In terms of the validity of the scale, the opinion of the expert was asked; and exploratory factor analysis was performed for the construct validity. In terms of the reliability, internal consistency coefficient was calculated. Appropriate values were obtained at the end of the analysis. In conclusion, a valid and reliable scale including 4 factors (perceiving the difficulty of reading, reading competence, effort for reading, and social aspect of reading) and 22 items was obtained.

Durmuş (2014) readapted the reading motivation scale previously adapted into Turkish by Yıldız (2010) in a different group. Data of this research were collected from totally 357 students in 5, 6, 7, and 8th grades. In the study, 29 out of 54 items in the scale were used. Exploratory factor analysis method was used for revealing the construct validity of the scale, and Cronbach alpha internal consistency coefficient was used for the reliability. At the end of the study, appropriate results were obtained, and a valid and reliable scale including 4 factors (importance and attention, competition, social environment, and type and quality of the book) and 29 items was created.

There were 2 factors (love of reading and reason for reading) and 14 items in the reading motivation scale that Katrancı (2015) developed with the participation of 1224 students in the 4th grade of elementary, and the 5 and 6th grades of secondary education. Katrancı used exploratory and confirmatory factor analyses to calculate the construct validity of the scale, and calculated Cronbach alpha internal consistency coefficient for the reliability of the scale. At the end of the study, a valid and reliable scale used for investigating the reading motivations of the students was obtained.

Considering the aforementioned mentioned studies, it can be said that measurement of motivation was the focus of several studies on reading motivation in general, and scales were developed in this sense. This study aimed to determine the reading motivations of the students in the Faculty of Education based on some variables, and in accordance with this purpose, answers to the below mentioned questions are sought for:

(1) What is the reading motivation level of Education Faculty students in general?

 (2) Do the reading motivations of the students studying at the Faculty of Education differ according to:

(a) Their gender

(b) Their department

(c) The educational level of their father,

(d) The educational level of their mother

(e) The profession of their father,

(f) The profession of their mother,

(g) Their economic status,

(h) The frequency of buying newspapers,

(i) The frequency of buying magazines

(j) The frequency of reading in an electronic environment

(k) The reasons for reluctance towards reading

Purpose and importance of the research

The role of reading in acquiring cultural accumulation is significant. It has been known that being cultural is a condition for being successful in social life. In this sense, reading enables students to have a better understanding of their own self, their own surrounding and social values. The students should also be made to think that they can have cultural accumulation through reading. And in order to make students gain this consciousness, pre-service teachers should have reading habit, and be conscious of this. Due to these reasons, this study aims to determine the variables affecting the reading motivations of the students studying at the Faculty of Education. Based on the findings obtained in this study, the variables that affected the reading motivations of the students studying at the Faculty of Education were determined, and suggestions related to overcoming the basic factors that prevent reading and developing reading habits were offered.

Problem sentence

Do reading motivations of the students studying at the Faculty of Education differ according to the following factors:

(1) Gender

(2) Department

(3) Educational level of their mother and father

(4) Profession of their father and mother

(5) Economic status

(6) The frequency of buying newspapers and magazines

(7) Internet access, and

(8) Unwillingness to read? 

In this section, the research model, study group, data collection and data analysis were emphasized.

Research model

This research was carried out on relational screening model as one of the screening models. The purpose of screening models is to describe a past or current situation as it is (Karasar, 2004). Totally, 304 students studying at Sinop University, Faculty of Education in Sinop Province participated in the study. A form including two section; demographical information and “adult reading motivation scale” was given to the students.

Variables of the research

The variables are grouped into three according to the control variables:

(1) Dependent variable

(2) Independent variable

(3) Control variable

According to Karasar (2004), dependent variable is a kind of result, and can be irritating for the researcher. The dependent variable is chosen by the variable, and is expected to shed light on solution of a problem. The dependent variable of this study is the reading motivation of students. The independent variable is the stimulant variable that has an effect on the dependent variable. The independent variables affect the dependent variable in a way. The independent variables of this research are gender, department, educational level of mother and father, profession of father and mother, economic status, frequency of buying newspapers and magazines, internet access, and unwillingness to read. On the other hand, control variables are surprising variables which are different from the independent variables but also similar to them with regard to the strong possibility of affecting the dependent variable in one way or another. The control variables of this research were different classroom environments, implementation period and different departments.

Population and sample

The target population of the research included Faculty of Education students in Sinop, Turkey and the sample included totally 304 volunteer students studying at 5 different departments in the Faculty. However, the information of 19 students was not included because there was too much missing data for these students, and the study was completed with 285 students. The statistical information related to these students is presented in Table 1.

 

 

In Table 1, the percentage of female students in all departments except Social Sciences Teaching Department was more than the percentage of male students. All students in Computer Teaching Department were females. It is possible to mention here that female students preferred Faculties of Education more than the males. Whereas 76% (218) of the 285 students who participated in the study were females; 24% (67) of the students were male students. When the percentage of the departments was considered, majority of the students participated in the study were from Pre-School Teaching Department.

Collection of data

In order to obtain data for the study, “Adult Motivation Scale” was used. The study group included the students studying at the Faculty of Education. This sample was preferred in the research as being easily accessible.

Data collection tools

Adult Reading Motivation Scale was used in order to collect the data necessary for the statistical analysis of the sub-problems in the research. The detailed information related to the scale is presented below.

Adult reading motivation scale (ARMS)

In this study, Adult Reading Motivation Scale (ARMS) developed by Schutte and Malouff (2007) (Appendix 1), and adapted into Turkish by Yıldız et al. (2013) (Appendix 2) was used as the data collection tool. The theoretical framework of this scale is structured in Reading Commitment Model and Reading Motivation Scale. The original scale included 4 factors and 21 items; however, the scale that was adapted into Turkish included 4 factors and 19 items. The 14 and 17th items in the original scale were excluded from the scale because the factor loads of the items were below 0.30 (Yıldız et al., 2013).

The four factors in the scale were “reading as part of self,” “reading efficacy,” “reading for recognition,” and “reading to do well in other realms.” While naming these dimensions, Self (Reading as Part of Self) expressed the importance of being a reader; Efficacy (Reading Avoidance versus Reading Efficacy) expressed being a competent reader; Recognition (Reading for Recognition) expressed being accepted as a good reader as reading performance’s being known by anyone else; and other (Reading to Do Well in Other Realms) expressed being a reader in order to be successful in other areas. Whereas Cronbach alpha reliability coefficient of the original scale is α=0.85, self- sub-dimension Cronbach alpha reliability coefficient is α=0.87, efficacy is α=0.72, Recognition is α=0.83, and other is e α=0.70 (Schutte and Malouff, 2007). In the scale adapted into Turkish, the Cronbach alpha reliability coefficient of the scale isα=.86, and the reliability coefficient is α=0.82; self, α=0.60 for Efficacy, α=0.78 for Recognition, and α=0.72 for others (Yıldız et al., 2013).

In the scale adapted into Turkish by Yıldız et al. (2013), the state related to the current structure of the scale was determined. For that purpose, a pilot implementation was performed with 190 students by the researchers. In this way, confirmatory factor analysis (CFA) based upon structural equality model was performed, and this structure is presented in Figure 1. In Figure 1, the relationships between ARMS factors and the items in the relevant factor are presented. It was determined that the relationship coefficients calculated between the factors and items varied between 0.46 and 0.83.

 

 

According to Büyüköztürk (2002), the values at and over 0.60 could be defined as having high correlation coefficient and the values between 0.30 and 0.59 could be defined as having medium correlation coefficient. When the numerical values were analyzed, it was noticed that the relationship coefficients calculated between the factors and items fit. At the end of the research, it was determined that x²=388.103, p=.000, df=146, and x²/df=2.66. As could be seen in Figure 1, the adapted scale included 4 sub-dimensions and fitting with the original scale was provided. Confirmatory factor analysis results are presented in Table 2. 

 

 

When Table 2 is examined, it can be said that if the value obtained by proportioning chi-square to the degree of freedom(x2/df=2.66) is below 5, then it is an acceptable value. (Marsh and Hocevar, 1988). The value below 3indicates perfect fit, and its being below 5 indicates good fit (Kline, 2005). Thus, the model is said to have a perfect fit.

RMSEA is the square root of average error of squares. In order for the model to be significant, the values on which RMSEA was 0.05 or lower should indicate perfect fit, and the values below 0.10 should indicate good fit (Steiger, 1990; Anderson and Gerbing, 1984; Cole, 1987). The value obtained in the research was 0.094, and this indicated good fit.

CFI was a fit index comparing covariance matrix predicted by the model and covariance matrix of the null-hypothesis model (Hooper, Coughlan and Mullen, 2008). CFI had values varying between 0 and 1. It is possible to mention that a model with CFI value between .95 and 1 had good fit, and a model that had CFI value between 0.90 and 0.95 had acceptable fit (Hu and Bentler, 1999).

In terms of this research, CFI value found to be 0.93, indicating good fit. CFI index is the fit index that is most commonly used in structural equality models (Fan, Thompson and Wang, 1999). NFI is normed fit index, and was developed by Bentler and Bonett as an alternative to CFI. This index searched the fitting of the assumed model with basic or zero hypotheses. NFI value was obtained as 0.96, and this indicated the model to have perfect fit. Moreover, NFI value as normed fit index was determined to be 0.92, and this indicated good fit (ÅžehribanoÄŸlu, 2005).

GFI indicated general covariance amount between the observed variables calculated by the assumed model. GFI value varied between 0 and 1. GFI values being over 0.90 was accepted as a good model indicator. This meant adequate covariance was calculated between the observed variables (Hooper, Coughlan and Mullen, 2008). AGFI is adjusted goodness of fit index (Schumacker and Lomax, 1996). GFI value being over .85 and AGFI value being over .80 indicated the values to be acceptable (Anderson and Gerbing, 1984; Cole, 1987). In this model, GFI value was obtained to be 0.92, and this indicated the model to have acceptable fit. AGFI value was obtained to be 0.96, and this indicated the model to have perfect fit.

In conclusion, obtained findings proved the model to be acceptable. Internal consistency coefficient indicating the reliability of the scale was α=0.89, and the reliability coefficient was α=0.84 for Self, α=0.75 for efficacy, α=0.75 for recognition, and α=.75 for others. The results of this study are similar with the studies carried out by Schutte and Malouff (2007) and Yıldız et al. (2013) on scale.

From these findings, it can be said that the scale is valid and reliable as a result of the confirmatory factor analysis performed for Adult Reading Motivation Scale. Because Adult Reading Motivation Scale was structured on Likert type, each choice was scored as below. The scale had totally 19 items. The 2nd, 3rd, 4th, 5th, 6th, 9th, 10th, and 11th items (8 items) were related to “reading as the part of self;” 1st, 15th, 17th and 18th items (4 items) were related to “efficacy;” 12th, 13th, and 14th items (3 items) were related to “recognition;” and 7th, 8th, 16th, and 19th items (4 items) were related to “reading to do well in other realms” (other) factor. Numerical values of the choices:

I totally agree: 5 point, I agree: 4 point, neither agree nor disagree: 3 point, I disagree: 2 point, I totally disagree: 1 point.

Because all items of the scale were positive expressions, scoring was the same for all items. According to this, the highest score possible to be taken from the scale was 95, and the lowest score was 19.

Analysis of the data

Quantitative method was used in the research, and obtained data were analyzed using Independent Samples t-Test and One-Way Variance Analysis (ANOVA). The level of significance was accepted to be 0.05 in the statistical analyses used in the research. For analyzing the quantitative data of the research, the statistical techniques were:

(1) Independent samples t-Test

(2) One-Way Variance Analysis (ANOVA) according to type and purpose were obtained. Assumptions of these parametric tests are as follows:

(a) The data should be constant. The data in the study were obtained from Adult Reading Motivation Scale. All the data were constant.

(b) The data should have normal distribution. The analyses performed to determine whether the data are distributed normally or not are presented below. In Table 3 below, skewness-kurtosis coefficients were presented, and inference was made on the normality of the data. 

 

 

In Table 3, it was noticed that skewness-kurtosis coefficients varied between -1 and +1 interval. These values between -1.5 and +1.5 indicated the value to be acceptable according to Tabachnick and Fidell (2014), and the values between -2.0 and +2.0 indicated the values to be acceptable according to George and Mallery (2010). However, skewness-kurtosis was not adequate for normality alone. For this, Kolmogorov-Smirnov and Shapiro-Wilk tests were performed to reading motivation scale variable. In Table 4, the data are distributed as homogenous. This assumption was presented before the sub-problems were determined during the analyses. Because the data used in the study was appropriate for the required assumptions, the statistical calculations were made. 

 

In this section, analysis results related to the sub-problems prepared to answer the research problem and interpretations related to these results were included.

Problem

Do reading motivations of the university students differ according to the following factors: gender, department, educational level of mother and father, profession of father  and  mother,  economic  status,  the  frequency  of buying newspapers and magazines, internet access, and unwillingness to read? The sub-problems below were answered in order to look for an answer to this problem.

First sub-problem

What is the level for the reading motivations of the university students? Arithmetic average and standard deviation values related to the first sub-problem are presented in Table 5. When reading motivation level of the students was considered in terms of sub-dimensions of the scale, the average level was  27.48 in dimension of “self.” There were 8 items in this dimension of the scale. The highest score possible to be taken from this dimension was 40, and the lowest score was totally 8 including all the positive. As the highest possible score to be taken from “self” dimension and the average was 27.48, it was determined that students’ belief of the importance of being a reader was at a good level. In “efficacy” sub-dimension, the average was 12.58. 

 

 

In this dimension of the scale, there were all positive 4 items. The highest score possible to be taken in this dimension was 20, and the lowest score was 4. As the highest possible score to be taken from “efficacy” dimension was 20 and the average was 12.58, it was determined that students’ belief of the importance of being an efficient reader was at a good level.

In “recognition” sub-dimension, the average was 9.48. There were all positive 3 items in this dimension of the scale. The highest possible score to be taken from this dimension was 15, and the lowest score was 3. As the highest possible score to be taken from “recognition” dimension was 15 and the average was 9.48, it was determined that students’ belief of being accepted as a good reader by anyone was at a relatively high level. In “other” sub-dimension, the average was 13.56. There were all positive 4 items in this dimension of the scale. The highest possible score to be taken from this dimension was 20, and the lowest score was 4.

In this sense, students’ belief of being successful in other realms was found to be relatively high. When the sub-dimensions in adult reading motivation scale were considered, “self” dimension scores expressing students’ belief of the importance of being a reader were higher than the other dimensions.

Second sub-problem

Do reading motivations of university students differ according to their gender? In Table 6, adult reading motivation scores according to gender were presented.

 

 

In Table 6, whereas ARMS score average of female students was 63.94, and the standard deviation was 71, ARMS score averages of male students was 59.78, and the standard deviation was 1,42. Scores of both groups were different from each other. Independent Samples t-Test results in Table 7 were regarded for determining whether there was a statistically significant difference between the scores of the groups.

 

 

According to Levene’s test results, because our assumption related to the homogeneity of variance was confirmed (sig=0.329; sig>0.05), the independent samples t-Test was done. The final premise of the Independent Samples t-Test was performed. Subsequently, ARMS scores of the male and female students were assessed according to independent-samples t-Test results. The difference obtained here was found to be statistically significant (p=0.006; p<0.05).

This difference was in favor of the experiment group (K_63.94>E_59.78). It is possible to conclude that reading motivations of female students were higher than the motivations of male students.

Third sub-problem

Do   reading   motivations  of   university   students  differ according to their department?

Whether the difference between ARMS score averages was significant in terms of departments was analyzed with F-test, and the analysis results are presented in Table 8. In Table 8, the difference found as a result of one-way variance analysis (ANOVA) to determine whether ARMS scores differed significantly according to the variable of department was not significant (F=1.039; p=0.388; sig>0.05). It was concluded that reading motivations of the pre-service teachers were independent from the department they studied at. 

 

 

Fourth sub-problem

Do reading motivations of university students differ according to educational level of father?

In Table 9, ARMS scores and statistics according to the educational level of father are presented. In Table 9, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of educational level of father was not statistically significant (F=0588; p=0.671; sig>0.05). It could be concluded that the educational status of father did not have an effect upon reading motivation. 

 

 

Fifth sub-problem

Do reading motivations of university students differ according to educational level of mother?

In Table 10, ARMS scores and statistics according to the educational level of mother are presented. In Table 10, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of educational level of mother was not statistically significant (F=0.937; p=0.458; sig>0.05).It could be concluded that educational status of mother did not have an effect upon reading motivation.

 

 

Sixth sub-problem

Do reading motivations of university students differ according to profession of father?

In Table 11, ARMS scores and statistics according to  the profession of father are presented. In Table 10, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of profession of father was statistically significant (F=3.643; p=0.003; sig<0.05). Subsequent to this process, subsidiary post-hoc analysis techniques were performed to determine from which sources the difference arose from. 

 

 

After ANOVA, the hypothesis related to whether group distribution variances were homogenous or not was tested with Levene’s test in order to decide which post-hoc multiple comparison technique should be used, and the variances were specified to be homogenous (LF=0.312; sig>0.05). After this, Scheffe multiple comparison technique was used which is highly preferred for cases when the variances are homogenous. The reason for preferring Scheffe test was the test’s being sensitive towards alpha type error.

After the one-way variance analysis (ANOVA) performed for determining among which groups ARMS scores differed in terms of the profession of father, a statistically significant difference (p<0.05) in favor of self-employed fathers was found between the students with farmer fathers and self-employed fathers. Socio-economic status has affected access to today’s reading instruments, and also financial possibilities were also efficient upon accessing these instruments. The differences between other sub-dimensions were not statistically significant (p>0.05).

Seventh sub-problem

Do reading motivations of university students differ according to profession of mother?

In Table 12, ARMS scores and statistics according to the profession of mother are presented. In Table 12, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of profession of mother was not statistically significant (F=0.937; p=0.458; sig>0.05). It was concluded that reading motivations of pre-service teachers were independent of the profession of their mothers. 

 

 

Eighth sub-problem

Do reading motivations of university students differ according to their economic status?

In Table 13, ARMS scores and statistics according to the monthly income are presented. In Table 13, the difference found as result of one-way variance analysis(ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of monthly income was statistically significant(F= 2.495; p=0.007; sig<0.05).Subsequent to this process, subsidiary post-hoc analysis techniques were performed to determine which groups the difference arose from. 

 

 

After ANOVA, the hypothesis related to whether group distribution variances were homogenous or not was tested with Levene’s test in order to decide which post-hoc multiple comparison technique should be used, and the variances were specified to be homogenous (LF=0.380; sig>0.05). After this, Scheffe multiple comparison technique was used which is highly preferred for cases when the variances are homogenous. The reason for preferring Scheffe test was the test’s being sensitive to alpha type error. After one-way variance analysis (ANOVA) performed for determining among which sub-groups ARMS scores differed in terms of the variable of monthly income, a statistically significant difference (p<0.05) was found between the one with less than 500TL monthly income and the other groups in favor of the latter as result of post-hoc Scheffe test.

A statistically significant difference (p<0.05) was also determined between the students with monthly income of 15001 to 200TL and the ones with 4001 to 4500TL; and between the ones with a monthly income of 2001 to 2500TL and the ones with 3001-3500TL; and between the ones with a monthly income of 3001 to 3500TL and the ones with 4001 to 4500TL; and between the ones with a monthly income between 2501-3000TL and the ones with 4001 to 4500TL. It could be concluded that specific economic level increased reading motivation. The statistical difference between these groups of students was in favour of the ones with higher income.  

However, it was noticed that the economic increase after 4001 to 4500TL economic range did not have an effect upon this motivation. The difference between other sub-dimensions as result of the analyses performed in reference  to  this  was  not  found  statistically  significant

(p>0.05).

Ninth sub-problem

Do reading motivations of university students differ according to the frequency of buying newspapers?

In Table 14, ARMS scores and statistics according to the frequency of buying newspapers are presented. In Table 14, the difference found as result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of frequency of buying newspapers was statistically significant (F= 1.692; p=0.021; sig<0.05). Subsequent to this process, subsidiary post-hoc analysis techniques were performed to determine which groups the difference arose from.

After ANOVA, the hypothesis related to whether group distribution variances were homogenous or not was tested with Levene’s test in order to decide which post-hoc multiple comparison technique should be used, and the variances were specified to be homogenous (LF=0.498; sig>0.05). 

 

 

After this, Scheffe multiple comparison technique was used which is highly preferred for cases when the variances are homogenous. The reason for preferring Scheffe test was the test’s being sensitive to alpha type error. As result of one-way variance analysis (ANOVA) performed to determine among which groups ARMS scores differed according to the variable of frequency of buying newspapers, a statistically significant difference (p<.05) was determined in favor of subscribers between the students who have never bought newspapers and subscribers at the end of post-hoc Scheffe test.

As a result, it was noticed that reading motivations of the students who read newspapers regularly every day are higher than the ones who have never bought newspapers. The difference between the other sub- dimensions was not found to be statistically significant (p>0.05).

Tenth sub-problem

Do reading motivations of university students differ according to the frequency of buying magazines?

In Table 15, ARMS scores and statistics according to the frequency of buying magazines were presented. In Table 15, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of frequency of buying magazines was statistically significant (F= 2.513; p=0.039; sig<0.05). Subsequent to this process, subsidiary post-hoc analysis techniques were performed to determine which groups the difference arose from. 

 

 

After ANOVA, the hypothesis related to whether group distribution variances were homogenous or not was tested with Levene’s test in order to decide which post-hoc multiple comparison technique should be used, and the variances were specified to be homogenous (LF=0.223; sig>0.05). After this, Scheffe multiple comparison technique was used which is highly preferred for cases when the variances are homogenous. The reason for preferring Scheffe test was the test’s being sensitive to alpha type error. As a result of one-way variance analysis (ANOVA) performed to determine among which groups ARMS scores differed according to the variable of frequency of buying magazines, a statistically significant difference (p<0.05) was determined in favor of the students who often bought magazines between the students who have often bought magazines and who have never bought magazines at the end of post-hoc Scheffe test.

In general, reading motivations of the students who read magazines were higher than the ones who have never read. The difference between the other sub-dimensions was not found to be statistically significant (p>0.05).

Eleventh sub-problem

Do reading motivations of university students differ according to frequency of reading in an electronic environment?

As could be seen in Table 16, ARMS scores and statistics according to the frequency of reading in an electronic environment were presented. In Table 16, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of frequency of reading on an electronic environment was statistically significant (F= 2.565; p= 0.045; sig<0.05). Subsequent to this process, subsidiary post-hoc analysis techniques were performed to determine which groups the difference arose from.

 

 

After ANOVA, the hypothesis related to whether group distribution variances were homogenous or not was tested with Levene’s test in order to decide which post-hoc multiple comparison technique should be used, and the variances were specified to be homogenous LF=0.105; sig>0.05).

After this, Scheffe multiple comparison technique was used which is highly preferred for cases when the variances are homogenous. The reason for preferring Scheffe test was the test’s being sensitive towards alpha type error. As a result of one-way variance analysis (ANOVA) performed to determine among which groups ARMS scores differed according to the variable of the frequency of reading on an electronic environment, a statistically significant difference (p<0.05) was determined in favor of the students who have read on an electronic environment every day between the students who have never read on an electronic environment and who have read every day at the end of post-hoc Scheffe test.

Especially intense use of informative communication technologies in today’s world was noticed to increase reading motivations of the students who have used this technology for reading. No statistically significant difference was found between other sub-dimensions (p>0.05).

Twelfth sub-problem

Do reading motivations of university students differ according to the reasons for their unwillingness to reading?

In Table 17, ARMS scores and statistics according to the reasons for their unwillingness to reading were presented. In Table 17, the difference found as a result of one-way variance analysis (ANOVA) performed to determine whether ARMS scores differed significantly according to the variable of the reasons for unwillingness to read was statistically significant (F= 3.869; p=0.002; sig<0.05). Subsequent to this process, subsidiary post-hoc analysis techniques were performed to determine which groups the difference arose from.

 

 

After ANOVA, the hypothesis related to whether group distribution variances were homogenous or not was tested with Levene’s test in order to decide which post-hoc multiple comparison technique should be used, and the variances were specified to be homogenous (LF=0.080; sig>0.05).

After this, Scheffe multiple comparison technique was used which is highly preferred for cases when the variances are homogenous. The reason for preferring Scheffe test was the test’s being sensitive towards alpha type error. As a result of one-way variance analysis (ANOVA) performed to determine among which groups ARMS scores differed according to the variable of the reasons for unwillingness to read, a statistically significant difference (p<0.05) was determined in favor of the students who have limited time to read between the students who have limited time to read and who do not like reading, are lazy, have different priorities and who have no habit of reading at the end of post-hoc Scheffe test. 

It was possible to mention that the students with high reading motivation considered having limited time as the most significant obstacle to reading. No statistically significant difference was found between other sub-dimensions (p>0.05).

At the end of the research, it was revealed that the variables, gender, profession of father, economic status, frequency of buying newspapers, frequency of buying magazines, frequency of reading in electronic environment, and the reasons for unwillingness to read were efficient upon reading motivations of students whereas variables such as department, educational level of father, educational level of mother, and profession of mother were not efficient.

It was determined in this study investigating the reading motivations of the Faculty of Education students that the most significant reason of the students for unwillingness to read was having “limited time.” Moreover, reading motivations of the students who read in an electronic environment were found to be higher. This result proved that the young individuals in today’s information age spend more time in electronic environment. High reading motivation of the students who were subscribed to a magazine or newspaper supported the assumption that reading newspapers or magazines constantly positively affected reading motivation. High motivation level of the students with more monthly income and with self-employed fathers supported the assumption that socio-economic level affected the access to the reading instruments of today’s world, and financial possibilities were efficient upon obtaining these.

In recent years, some implementations (Türkiye Okuyor, 100 Temel Eser, Okuma Saati, etc.) related to develop reading skills and gaining reading habits have been fulfilled in Turkey. It was revealed in research results that these implementations have not met the expectations. Although so much attention has been paid, the reasons for reading motivations of students to decrease should be investigated further. In accordance with the results of this research, the suggestions below are offered for implementers and researchers:

The data of this study were collected from the students studying at the 1st grade of different departments in The Faculty of Education in Sinop, Turkey. The relationship between high school sub-structure of a student at the 1st grade and reading motivation should not be ignored. For that reason, methods and approaches preferred for orienting students towards reading especially at schools should be revised. More efficient approaches that do not put off students from reading should be adopted.

The research results indicated that reading motivations of the students who have permanently bought newspapers or magazines or who were subscribers were high. In this sense, classroom bookcases at schools should be enhanced more with reading materials.

It is an incontrovertible fact that the most significant role in making students to have reading habit is on families. For that reason, participation of families should not be ignored in implementations related to developing the reading habit for the students at school age. Furthermore, studies to be carried out on investigating the thoughts of families on reading should be supported. When the studies in the literature were reviewed, it was noticed that there were no several studies on role of the variables related to reading upon academic success. The studies on reading motivation should be carried out more in Turkey, and the factors affecting reading motivation positively or negatively should be analyzed for University students.

But according to Åžahbaz (2012), reading attitudes of 8th grade students in primary education differ according to gender and this difference is on behalf of the female students and economic level of their family. The model developed and the relationships tested in this research can be re-discussed for different grades of faculties, for different socio-economic levels, and for different disadvantageous groups (students with reading disability, students with difference in native language, etc.).

In this sense, further studies can be carried out including new variables and excluding some others. In this study, the relationship of variables such as department, educational level of father, educational level of mother, and profession of mother with reading motivation was found to be insignificant. However, profession of father and economic status were among the factors affecting the reading motivation of the students. These findings could be reanalyzed through different models or analysis techniques. The relationship of fluent reading with academic success and exam success could be analyzed as independent from reading motivation and understanding.

 

The authors have not declared any conflict of interests.