# This teachers’ burnout and their years of

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

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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.