This chapter focuses on providing the

results of the study which aims to investigate the relationship between

teachers’ experience and teachers’ burnout and self-efficacy. Therefore, it

presents the results obtained from the analysis of the data collected for this

study. The results are reported based on research questions.

4.1 Results

The present study aims to investigate the possible relationships

between teachers’ burnout, teachers’ self-efficacy and their experience to this

purpose next to collecting, the proper data this chapter presents the results

of statistical analysis have been provided in this chapter.

The data gathered to answer if there is there any significant

relationship between teachers’ self-efficacy and their feelings of burnout? And

is there any significant relationship between teachers’ burnout and their years

of the experiences?

To find the answer for research questions, the researcher hypothesized

the related null hypotheses: H01) There is no significant relationship between

teachers’ self-efficacy and their feelings of burnout. H02) There is no

significant relationship between teachers’ burnout and their years of the

experiences.

4.1.1

Results of Research Question One

Table 4.1 show the bio data of the participants along with their

teaching experience (M=15.36, SD= 7.19). As it is illustrated, the minimum

teaching experience was 5 years while the maximum amount of experience is 29

years. In the present study, 26 male and 59 female teachers were participated.

The age of the participants mostly fluctuates between 31 to 46 year olds. For

the investigations, a minimum experience was required and based on Table 4.1

all of the participants had, at least, five years of teaching experience.

Table 4.1

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Age

85

27.00

52.00

38.8000

7.64043

Experience

85

5.00

29.00

15.3647

7.19928

Valid N (listwise)

85

4.1.1.1

Descriptive Statistics of the Self-Efficacy and Burnout Questionnaire

Table

4.2 shows the summary of both the self-efficacy and Burnout questionnaire.

Accordingly it could be stated that the mean for self-efficacy is 63.90 (SD=

17.32) and the mean for burnout questionnaire is 67.14 (SD= 19.34). Moreover, it shows that all the collected

data was valid and was used in proceeding analysis.

Table 4.2

Descriptive Statistics

Mean

Std. Deviation

N

Self-efficacy

63.90

17.32

85

Burnout

67.14

19.34

85

As it is indicated in

Table 4.3, the correlation between teachers’ self-efficacy and teachers’

burnout is .58. This amount of correlation (Sig=.000) is significant at the .05

level implying a significant correlation between two variables of the study. In

other words a change in one of the variables brings about a change in the same

direction for the other variable. The higher amount of self- efficacy will lead

to a higher level of burnout.

Table 4.3

Person Product Correlation

Correlations

Self-efficacy

burnout

Self-efficacy

Pearson Correlation

1

.580**

Sig.

(2-tailed)

.000

Sum of Squares and Cross-products

25225.24

16316.12

Covariance

300.30

194.24

N

85

85

Burnout

Pearson

Correlation

.580**

1

Sig. (2-tailed)

.000

Sum

of Squares and Cross-products

16316.12

31422.30

Covariance

194.240

374.075

N

85

85

**. Correlation is significant at the 0.05 level

(2-tailed).

Figure 4.1 show the

correlation plot for teachers’ burnout and self-efficacy. As the degree, go

togetherness show there is a relatively low relationship between these two

variables.

Figure 4.1

Correlation Plot

4.1.2

Results of Research Question Two

By conducting the Chi-Square tests for teachers’

burnout and their years of experiences, the aforementioned results in Table 4.4

were achieved. We

observed a strong association between the teachers’ level of burnout and their

years of experience, ?2(2) = .722, p =

.697. Cramer’s V= .092″.

This results

means that there is a relationship between teachers’ burnout and their

experience; an increase in their years of experience will lead to a higher

chance of burnout.

Table 4.4

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

7.22a

2

.041

Likelihood Ratio

7.30

2

.049

Linear-by-Linear Association

7.12

1

.038

N of Valid Cases

85

a. 2 cells (33.3%) have expected count less than 5. The minimum

expected count is 1.55.

The most commonly used one is the

phi coefficient, which is a correlation coefficient and can range from 0 to 1,

with higher values indicating a stronger association between the two variables.

In this particular case, phi coefficient value is .230, which is considered a

small effect size, considering Cohen’s (1988) criteria of .10 for small effect,

.30 for medium effect and .50 for large effect.

Table

4.5

Symmetric

Measures

Value

Approx. Sig.

Nominal by Nominal

Phi

.230

.091

Cramer’s V

.230

.091

4.2 Discussion

The main purpose of this research

was to explore the relationship between Iranian EFL teachers’ self-efficacy and

burnout.

4.2.1 Discussion on Research Question One

The first research question of the study was to find if there is

any significant relationship between teachers’ self-efficacy and their feelings

of burnout? The related null hypothesis stated significant relationship between

teachers’ self-efficacy and their feelings of burnout. This null hypothesis was

rejected.

The data analysis reveals the fact that the

correlation between teachers’ self-efficacy and teachers’ burnout is .58. This

amount of correlation (Sig=.000) is significant at the .05 level implying a significant

correlation between two variables of the study. In other words a change in one

of the variables brings about a change in the same direction for the other

variable. The higher amount of self- efficacy will lead to a higher level of

burnout.

4.2.2

Discussion on Research Question Two

The first research question of the study was to find if there is

any significant relationship between teachers’ burnout and their years of the

experiences? The related null hypothesis mentioned that there is no significant

relationship between teachers’ burnout and their years of the experiences. This

null hypothesis was also rejected.

By conducting the

Chi-Square tests for teachers’ burnout and their years of experiences, we observed a strong association between the

teachers’ level of burnout and their years of experience.

This results

means that there is a relationship between teachers’ burnout and their

experience; an increase in their years of experience will lead to a higher

chance of burnout.