THE CORRELATION OF STUDENTS’ ACADEMIC SELF-CONCEPT
TOWARD STUDENT LEARNING ACHIEVEMENTS IN ENGLISH LEARNING
I Ketut Wiriawan
STKIP Agama Hindu Amlapura, Bali, Indonesia
|
KEYWORDS |
ABSTRACT |
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students, academic self-concept, learning achievements. |
This study aimed at determining the correlation between students' academic self-concept toward student learning achievement in English learning in grade XI of Social Class of SMA Jagadhita Amlapura. This study is ex-post-facto research with a correlational technique and survey method. The population sample of this study was 33 students in XI of Social Class at SMA Jagadhita Amlapura in the academic year 2021/2022. A Questionnaire of Academic Self-Concept and documentation of students' report cards were used to collect the data. Descriptive statistics, Pearson Product Moment correlation and determination test, were used to analyze the data. Based on the data analysis, it was found that there is no significant correlation between academic self-concept toward student learning achievement of XI Social Class in SMA Jagadhita Amlapura with correlation value (-0.283) and p-value (0.130) > 0.05. While based on the determination test, only 8% of academic self-concept explained the variance of learning achievement, and 92% was predicted by another variablvariablest not examined in this study. The results of this study are not following the theory and differ from previous studies, which mainly obtained results that there was a significant correlation between academic self-concept and learning achievement. This could be due to the small sample size cannot prove a significant relationship between the two variables of the study or other limitations in this study. |
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DOI: 10.58860/ijsh.v2i4.39 |
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Corresponding Author: I Ketut Wiriawan*
Email: berutdada@gmail.com
INTRODUCTION
Language is a
system of communication humans use in their life. The language was used to
express ideas and feelings (Dictionary,
2008). In the globalization
era, English is important to learn in communicating. Many countries in the
world use English as a communicative language. According to the Cambridge
Encyclopedia of the English Language data, "85% of the world's
international organizations use English as their official language in
transnational communication (Rao,
2019)." Based on the data,
many people use English as their first language daily and learn English as a
Foreign Language.
Additionally,
in Indonesia, English is a foreign language. The importance of learning English
as a global language makes English implemented as a subject in classroom
activities. The aims of learning English at every level of students are to make
it easier to understand and apply international languages
The curriculum
2013 (K-13) is the implemented curriculum in Indonesia. The education system
aims to improve student quality of human resources, able to compete nationally
or international
Implementing
the K-13 curriculum has a long-term and short-term impact on students' English
skills. This is caused by the reduced time for English lessons, especially for
students outside the language major, such as science classes, or social studies
at the high school level. English subjects are studied 2 x 45 minutes a week in
science and social studies classes. While 4 x 45 minutes a week in language
class. This differs from the previous curriculum; in KTSP, all majors study
English 4 x 45 minutes a week. Indirectly this situation has an impact on
students. It impacts students' learning outcomes
Individuals
have different potential and cognitive levels, affecting how students learn and
their learning achievements. (Elsjelyn,
2014) stated that some students
quickly learn English through listening, writing, or speaking without fear of
making mistakes. However, it was also found that some students had tried to
learn English but finally gave up. Problems in learning are always actual
problems and are faced by every student. Problems usually arise because of the
low interest of students in learning.
Meanwhile,
interest will arise if there are reasons and goals to be achieved, such as learning
English. Interests supported by goals will affect the intensity of learning and
can automatically improve student achievement. Students' interest and learning
intensity was positively correlated with students' mathematics learning
achievement (Fitriyani,
2019).
Each school
has different learning management to help students achieve competency
standards. Competence is the policy and responsibility of the school to help
students achieve proficiency. Not only remember and understand, but students
can use what they learn
Generally,
students have different abilities, from the lower to the brightest. Therefore,
student learning achievement needs to be measured to determine student
abilities and movements. Teachers can evaluate student achievement through
various ways of collecting data. The evaluation assesses student development in
the learning process
Every student
in learning aims to achieve the learning goal. Student learning achievement can
be measured when the teacher has already set the objectives of learning, and
the students can reach them
Refers to the
statements above, self-concept is one of the factors that can affect student
achievement. While measuring the student's achievements, has a meaningful
relationship to the human as unique because students have different
characteristics. Shavelson, Hubner, and Stanson (1976) define self-concept as a
human perception of himself that is formed from experiences and relationships
with the environment. According to Robert (Burns,
1993), self-concept is a very
personal, dynamic, and evaluative individual picture that humans develop in
their psychological environment throughout their lives. (Harwijayanti
et al., 2022) stated that self-concept
combines body image, self-ideal, self-esteem, self-role, and self-identity.
Furthermore, Shavelson, Hubner & Stanson (1976) hierarchically dimensioned
self-concept as academic and non-academic. Academic self-concept is divided
into four, namely: history, mathematics, language and
science.
Academic
self-concept is part of self-concept. Academic self-concept is the human
perception of competence and ability in various subjects, such as English
learning
The teachers
and friends are the main self-informant at school, which could be individually
influenced positively, neutral, or negatively by the student self. (Marsh,
2003) suggested that academic
self-concept refers to the perceptions and individual's feelings towards
himself related to academic abilities. Student self-concept also creates an
ethos in relationships that can increase or decrease student achievement
Based on
direct observations in 9 meetings on teaching practices at SMA Jagadhita
Amlapura, one of the high schools in Karangasem, regarding the process of
English learning, many students stated that they had difficulties following
English subjects which had an impact on their learning achievement. For
example, (1) the students said they didn’t understand
what the teacher explained, (2) they were not confident when asked to speak or
read in front of the class, (3) they were embarrassed to ask the teacher, were
lazy to look for words that difficult in the dictionary and prefer to cheat on
their friends' work, and (4) they only study at school and when there has a
test. These showed that students had lack confidence in their abilities and had
low interest in learning English.
Based on observation
made by the researcher in SMA Jagadhita Amlapura, there are 21 of 33 students
whose scores were incomplete with scores below the minimum score criteria, 75,
with a percentage of 61.8 %. Based on an interview with one of the English
teachers at the school, he argued that most students assumed that English
subjects had difficulty learning, resulting in decreased learning achievement.
Based on the
explanation above, the researcher assumed that students' achievement,
especially in English learning, correlated with academic self-concept. Students
have positive perceptions of themselves, which relate to their abilities in
academic. Positive perceptions mean describing themselves well, having
confidence and motivation, and wishing for success. But students have a
negative perception of themselves, like feeling as a person is less adequate
than others, and ultimately makes their efforts less. English as a foreign
language also makes students find difficulty in learning English. Therefore, it
is important to measure the correlation between students' academic self-concept
toward student learning achievement in English learning.
From another
source, it could be seen that academic self-concept affected student
achievement; the different researchers measure academic self-concept on
specific parameters such as level of study and in the same programs. However,
the researcher wants to examine the correlation between academic self-concept
and learning achievement in social studies classes in English learning. Similar
studies from this study are:
(Ramadhan,
2017) examined the relationship
between student's academic self-concept and academic achievement. Three hundred
ninety students as a sample of English study programs at universities showed
that students' academic self-concept contributes 5.9% to students' academic
achievement. Meanwhile, (Rehanja,
2017) examined the effect of
academic self-concept on economic learning achievement, with 67 students as a
sample showing a result of 55.1% of the power of students' academic
self-concept in explaining the variance of student learning achievement. (Fitriyani,
2019) examined the relationship
between interest and learning intensity with student learning achievement and
showed a positive and significant relationship between learning interest and
learning intensity on the mathematics learning achievement of 29.6%.
Therefore, it
is interesting to determine whether there is any significant correlation
between students' academic self-concept toward student learning achievement in
English learning. In this regard, the researcher wills conduct a study entitled
"The Correlation between Students' academic self-concept toward Student
learning achievement in English Learning (An ex-post facto research in grade XI
of social class in SMA Jagadhita Amlapura)."
METHOD
The research design used in this study was an
ex-post facto design using a survey method with correlational techniques.
Suharsimi Arikunto (Maulidya, 2021) stated that
if a research subject or the population does not reach 100 people, it would be
better if all of them were taken. Thus, the total number of class XI students
at SMA Jagadhita Amlapura a total of 33 students, was used as a sample in this
research. The variable in this study consists of two variables. The first is
students' academic self-concept as the independent variable (X), and the second
is students' learning achievement as the dependent variable (Y). A
questionnaire with a Likert scale consisting of 35 item questionnaire that had
valid and reliable was used to measure the academic self-concept variable, and
documentation of report cards was used to measure student learning achievement
in English learning. The results were interval data; the analysis used
descriptive statistics, pre-requisite analysis, correlation, and determination
tests with a significant α = 0.0.
RESULT AND DISCUSSION
Based on the
descriptive statistics of academic self-concept, it was found that the total
number of participants was 33 students. The minimum score was 110, and the
maximum score was 173.
Table 1. Descriptive Statistic
|
|
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
Academic Self-Concept |
33 |
110.00 |
173.00 |
138.3333 |
14.83801 |
|
Valid N (listwise) |
33 |
|
|
|
|
Source: SPSS 16 (Data Processed)
Based on interval data, it
was found
two students (6%) whose scores belonged to an average category, 22 students
(67%) whose scores were into a high category and nine students (27%) fell into
a very high category. In other words, the academic self-concept in students of
XI Social Class at SMA Jagadhita Amalapura was high.
Table 2.
Data Description of Result Academic Self-Concept
|
Interval |
Frequency |
Percentage |
Category |
|
35 – 63 |
0 |
0% |
Very Low |
|
64 – 91 |
0 |
0% |
Low |
|
92 – 119 |
2 |
6% |
Average |
|
120 – 147 |
22 |
67% |
High |
|
148 – 175 |
9 |
27% |
Very High |
|
Total |
33 |
100% |
- |
Source: Data Processed
Table 3.
Descriptive Statistics of Student Learning Achievement
|
|
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
Learning Achievement |
33 |
79 |
88 |
80.12 |
2.288 |
|
Valid N (listwise) |
33 |
|
|
|
|
Source: SPSS 16 (Data Processed)
From the table
description of learning achievement, the result showed that no students were in
the less and less category. Meanwhile, 28 students (85%) scored belonged to the
average category, five (15%) scored in a high category, and no student fell
into the very high category. In other words, learning achievement in English
learning students of XI Social Class at SMA Jagadhita Amalapura was enough.
Table 4. Description
of Student learning achievement
|
Interval |
Frequency |
Percentage |
Category |
|
0 – 60 |
0 |
0% |
Very Less |
|
61 – 70 |
0 |
0% |
Less |
|
71 – 80 |
28 |
85% |
Enough |
|
81 – 90 |
5 |
15% |
Good |
|
91 – 100 |
0 |
0% |
Very Good |
|
Total |
33 |
100% |
- |
Source: Data Processed
The
researcher tested the normality of the data with a normal P-P Plot and 1-Sample
Kolmogorov Smirnov in SPSS Version 16.0 for Windows. If the p-value was higher
than 0.05, the data were normally distributed. The following is the result of
the data normality test:
|
|
|
|
Figure
1.
P-P Plot of Academic Self-Concept |
Figure
2.
The plot of Learning Achievement |
|
Source: SPSS 16 (Data Processed) |
Source: SPSS 16 (Data Processed) |
Based on the result of the output
SPSS standard P-P Plot in Figure 1, it could be described that the distribution
of academic self-concept data points spreads around the diagonal line. The
spread of the data points is in the direction of the diagonal line. So, the
data on the academic self-concept variable was normally distributed. Meanwhile,
figure 2, a standard P-P plot of learning achievement, describes that the
distribution of learning achievement data points spreads away from the diagonal
line. The spread of the data points was in the not direction of the diagonal
line. So, the data on learning achievement was not normally distributed.
Because the data of learning
achievement was not customarily distributed when tested with a P-P plot or, in
other words, parametric statistics, the researcher continued the normality test
with a non-parametric statistic test which the researcher in this study chose
the Kolmogorov-Smirnov test.
Table 5. Result
of Normality Test 1
|
|
|
Unstandardized Residual |
|
|
N |
33 |
|
Normal Parameters |
Mean |
.0000000 |
|
Std. Deviation |
2.26056531 |
|
|
Most Extreme Differences |
Absolute |
.301 |
|
Positive |
.301 |
|
|
Negative |
-.219 |
|
|
|
Kolmogorov-Smirnov Z |
1.731 |
|
Asymp. Sig. (2-tailed) |
.005 |
Source: SPSS 16 (Data Processed)
The normality
test aimed to test whether, in the model regression, the confounding variable
(residual) is normally distributed or not. A good regression model uses good
data usually distributed. Residual data that were normally distributed is the
Asymp value. Sig (2-tailed) > level of significant (
= 5%. The normality test results in this study
can be reviewed in Table 4.7. Based on the Kolmogorov-Smirnov test above, the
data is not normally distributed. This can be proven with Asymp. Sig.
(2-tailed) which is 0.005; it means more minor than the significance level
(0.05).
Because the data were not normally distributed,
it was necessary to do treatment data is not normal. One way that could be used
to treat data, not usually to be routine data, was to delete the data outliers;
Outlier data was data that has a very high value different from the value of
other observations (data with extreme values)
Figure 3. Box Plot of Data Outlier 1
Source: SPSS 16 (Data Processed)
According to Figure 3,
there were some data with a value of extreme. The outlier data to be removed is
the first, with asterisks at the top. Data to be deleted is excessive data
numbers 5 and 6. Removing data outliers is expected to normalize the data
residuals. After removing the outlier data, re-check whether the residual data
is standard.
Table 6. Result
of Normality Test 2
|
|
|
Unstandardized Residual |
|
N |
31 |
|
|
Normal Parameters |
Mean |
-.3675055 |
|
Std. Deviation |
1.70824659 |
|
|
Most Extreme Differences |
Absolute |
.258 |
|
Positive |
.258 |
|
|
Negative |
-.208 |
|
|
Kolmogorov-Smirnov Z |
1.438 |
|
|
Asymp. Sig. (2-tailed) |
.032 |
|
Source: SPSS 16 (Data Processed)
After
performing the deletion process on the outlier data and then reviewing whether
the residual data were normally distributed or not yet, the normality of the
data after the first outlier can be seen in Table 7. Based on the
Kolomogorov-Smirnov test, it was found that the residual data was not normally
distributed. This could be checked via Asymp. Sig. (2-tailed) whose magnitude
is 0.032, lower than the significance level (0.05). Therefore, it was necessary
to eliminate the data outliers back.
Figure 4. Box Plot of Data
Outlier 2
Source: SPSS 16 (Data Processed)
According
to Figure 4, data with extreme values were found. Therefore, the outlier data
that would be deleted next is data number 5, previously number 7. After
deleting the outlier data, check whether the data was standard or not.
Table 8. Result of
Normality Test 3
|
|
|
Unstandardized Residual |
|
N |
30 |
|
|
Normal Parameters |
Mean |
-.6299539 |
|
Std. Deviation |
.89991455 |
|
|
Most Extreme Differences |
Absolute |
.164 |
|
Positive |
.164 |
|
|
Negative |
-.105 |
|
|
Kolmogorov-Smirnov Z |
.898 |
|
|
Asymp. Sig. (2-tailed) |
.396 |
|
Source: SPSS 16 (Data Processed)
The results of
the normality test in this study can be reviewed in Table 8. Based on the
Kolomogorov-Smirnov test above, it could be seen that the residual data was
normally distributed. This could be proven with Asymp. Sig. (2-tailed) Its
magnitude of 0.396 was higher than the significance level (0.05).
For the
linearity test, deviation of linearity was obtained. The two variables were
linear if the probability of Deviation from Linearity was higher than 0.05.
Furthermore, to find out whether the distribution of the data was linear or
not, the result of the distribution can be seen in Table 8 below.
Table 8. The result of the
Linearity Test
|
|
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Learning Achievement * Academic Self-Concept |
Between Groups |
(Combined) |
13.967 |
24 |
.582 |
1.940 |
.238 |
|
Linearity |
1.237 |
1 |
1.237 |
4.123 |
.098 |
||
|
Deviation from Linearity |
12.730 |
23 |
.553 |
1.845 |
.257 |
||
|
Within Groups |
1.500 |
5 |
.300 |
|
|
||
|
Total |
15.467 |
29 |
|
|
|
||
Source: SPSS 16 (Data Processed)
The result of
the linearity test in this study can be reviewed in Table 4.10. Based on the
Anova Table above, it could be seen the academic self-concept variable (X)
toward the learning achievement variable (Y) is linear. This can be proved by
the significant deviation from linearity, whose magnitude is 0.257, which is
larger than the level of significance (0.05). Based on the result of normality
and linearity above, it could be concluded that the variables in this study it
was normal and linear, which means correlation analyses can continue this
study.
Based on
correlation analysis, there was no significant correlation between students' academic
self-concept toward student learning achievement, proven by the p-value of 0.130 >
0.05, with a coefficient correlation of - 0.283. The coefficient correlation cannot be
interpreted. In other words, when academic self-concept has decreased or
increased, it cannot influence learning achievement.
Table 9. The
Correlation Between Academic Self-Concept and Learning Achievement
|
|
|
Academic Self-Concept |
Learning Achievement |
|
Academic Self-Concept |
Pearson Correlation |
1 |
-.283 |
|
Sig. (2-tailed) |
|
.130 |
|
|
N |
30 |
30 |
|
|
Learning Achievement |
Pearson Correlation |
-.283 |
1 |
|
Sig. (2-tailed) |
.130 |
|
|
|
N |
30 |
30 |
Source: SPSS 16 (Data Processed)
Meanwhile, based on the
determination test, the value of the coefficient of determination equals = -0.283 x (-0.283)
= 0.08. Meant the power of the independent variable in explaining the variance
of the dependent variable is 8%, and 92% of the variance of the dependent
variable which explained by other factors not examined in this study. The table
below shows the results of the determination test using SPSS version 16.0.
Table 10.
Determination Test in Regression Analysis (Model Summary)
|
Model |
R |
R Square |
Adjusted R Square |
Std. The error in the Estimate |
|
1 |
.283a |
.080 |
.047 |
.713 |
Source: SPSS 16 (Data Processed)
Based
on the result using 33 students of XI Social Class at SMA Jagadhita Amlapura
could be concluded that two students (6%) whose scores belonged to an average
category, 22 students (67%) whose scores into a high category and nine students
(27%) fell into very high category. In other words, the academic self-concept
in students of XI Social Class at SMA Jagadhita Amlapura was high. Frey and
Carlock (Nugraha,
2017) stated that academic
self-concept is divided into two: positive and negative.
In this study,
the total scores obtained by every student in answering the questionnaire
indicated the negative or positive academic self-concept that the students
have. The biggest score meant the higher student's academic self-concept, and
vice versa. Based on the results of the descriptive analysis, it could be
explained that no one student of XI Social Class at SMA Jagadhita Amlapura had
a low academic self-concept. In other words, most of the students in the XI
Social Class of SMA Jagadhita Amlapura tend to be high academic self-concepts,
and the little of the students have an average academic
self-concepts. It could be concluded that students of XI Social Class at
SMA Jagadhita Amlapura more have positive academic self-concepts.
Based on
direct observation in SMA Jagadhita Amlapura, the researcher saw that students'
behaviour indicated that they had low interest, less confidence, and low
learning achievement in English Learning. But, the result of this study
described that most of the students of XI Social Class in SMA Jadaghita
Amlapura have a high academic self-concept. The high academic self-concept
score indicates that students tend to have a positive academic self-concept.
This could happen because, most of the time, students in XI Social Class at SMA
Jagadhita Amlapura have a positive perception of their academic abilities. The
positive perceptions mean they described themselves well, having confidence,
motivation, and wish for success. So that when students had difficulty in
learning, they tended to be able to handle it better than students who had a
negative perception of themselves, with positive academic self-concept in
academic abilities able to create high enthusiasm for learning. Line with (Burns,
1993) stated that children with
a positive self-concept tend to be able to make more positive and more apparent
judgments about their ability to excel in the school environment, allowing for
better study results.
While based on
the student's learning achievement results in English learning at XI Social
Class of SMA Jagadhita Amlapura. The researcher got from a documentary on
students' report card scores from the teacher in homeroom of the class and
continued by descriptive analysis can be explained that were no students in the
significantly less and less category. Meanwhile, 28 students (85%) whose scores
belonged to the average category and five students (15%) who scored in a high
category and was no student fell into the very high category. From the data, it
could be concluded that most of the student's learning achievement in English
learning was enough category with the average (mean) score obtained is 80.12.
It means students of XI Social Class in SMA Jadaghita Amlapura tend to have
enough learning achievement.
Students who
have a positive perception of academic ability tend to be able to obtain better
learning achievement. It was proven that the data above showed that the
students of XI Social Class in SMA Jagadhita Amlapura could get scores above
the minimum score criteria in learning English, with the average (mean) score
obtained being 80.12.
Based on the
problem formulation in this study, namely, there is any significant correlation
between students' academic self-concept toward student learning achievement in
English learning? The answer to the problem formulation in this study can be
seen in the hypothesis test results. Based on the hypothesis test using Pearson
correlation on the SPSS version 16.0 for Windows, the results showed in Table
4.11. The table stated that there is no significant correlation between
students' academic self-concept toward student learning achievement in English
learning of XI Social Class in SMA Jagadhita Amalapura. The value of sig proves
this. (2-tallied) of the correlation is 0.130 higher than the level of
significant value (0.05). So, H_0 is accepted and H_a is rejected. In addition,
the correlation coefficient is -0.283. Because there is no significant
correlation between academic self-concept toward learning achievement, the coefficient
correlation cannot be interpreted. It meant that when academic self-concept has
decreased or increased, it does not influence learning achievement.
Based on the
determination test, the coefficient determination value equals = -0.283 x
(-0.283) = 0.08. This means the independent variable's power in explaining the
dependent variable's variance is 8%. This means that 92% (100% - 8%) of the
dependent variable's variance is explained by other factors not examined in
this study. The low result indicates that the academic self-concept is not
sufficiently used to predict learning achievement. The results are supported by
Djalli, (2014) who stated that students' learning is influenced by several
factors such as self-concept, motivation, interest in learning, habitual
studying, and self-habits. Also in line with (Burns,
1993) who explained it would be
a surprise if the academic self-concept results had a very large impact.
Because more general explanations are needed, such as; IQ, social class,
parental attention, and others, that also influence producing a comprehensive
picture of why some students succeed while others fail.
(Nurahmah
et al., 2021) Who found that the
influence of self-concept on students' achievement is insignificant. Also
supported by (Basith,
2021), who explained that
academic self-concept with academic achievements has no significant
relationship. However, several studies have found contrasting results to this
result, where academic self-concept and learning achievement have a significant
positive correlation (Maulidya,
2021); (Ajmal
& Rafique, 2018); & (Njoki
et al., 2019) Also supported by
psychologists and education experts believe that self-concept and learning
achievement have a close relationship (Marsh,
2003);
Although this
study failed to show a significant correlation between academic self-concept
and learning achievement, the researcher wants to emphasize that academic
self-concept is still essential to help students achieve better study results
in academic. Supported by (Burns,
1993) stated that a mutually
influencing relationship exists between academic self-concept and learning
achievement. Academic success can increase or maintain a feeling of
self-esteem. In contrast, self-esteem affects performance through expectations,
standards, and recognition of personal strengths, motivation, and level of
persistence. The continued interplay of self-esteem enhances competencies that
are likely to increase learning achievement, as well as the effect of academic
success on self-confidence, expectations and rising
standards. In line with Frey and Carlock (in Machmud, 2008, pp. 19-20), who
explained the aspects of academic self-concept are knowledge, hope, and
self-assessment.
There was no
significant correlation between academic self-concept and learning achievement
in this study, were arose due to the lack of an adequate number of samples and
could not prove a significant relationship between the two variables. As stated
by (Nurahmah
et al., 2021) that statistically it is
stated that a larger sample size is expected to give better results.
In addition,
the limitations in the study were also unavoidable such as: 1) Weakness in the
data collection process, students who become respondents tend to be hasty in
answering statements, although previously given direction both in terms of the
objectives of this study and guidance in filling out the instrument. 2)
Weakness in terms of research instruments, even though researchers are
observant in formulating instruments to collect information about the
dimensions of variable indicators, it’s made and
developed in such a way and has been tested and rearranged in such a way. So,
the concern that there will overlap between items can be avoided. Although it
has been formulated in various formulations based on the theory used, there may
be deficiencies in the preparations and development of each item. 3) The lack of
theory regarding the academic self-concept and the results of previous studies
because most previous studies only discuss general self-concept.
Therefore,
several respondents were omitted in data processing because they were outliers,
namely observations data that appeared with extreme values. This extreme data
arises because of exceptional circumstances, such as the respondent's view of
something that deviates because there is a reason that the researcher does not
know the cause. Appears in the range of existing values, but when combined with
other variables, it becomes extreme (multivariate outliers).
CONCLUSION
Based on the
results of research and data analysis, it can be concluded that there is no
significant relationship between students' academic self-concept and student
learning achievement in English language learning. The implication of this
research is that this research can help teachers and teachers in understanding
the relationship between students' academic self-concept and student
achievement in English language learning. This research can also assist
students in understanding the importance of their academic self-concept in
achieving good learning achievement. This research can assist schools in
developing more effective learning strategies to improve students' academic
self-concept and student achievement in English.
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