Building Sport Student Self-Esteem in Learning Statistics through
SRLE
Statistical Reasoning Learning Environment
Nidaul Hidayah, Wahyudin Wahyudin, Turmudi Turmudi and Dadan Mulyana
Universitas Pendidikan Indonesia, Bandung, Indonesia
Keywords: Self-esteem, Sport Students, SRLE.
Abstract: Self-esteem is a person’s overall judgements of himself. The results of previous research showed that students
with high self-esteem looked more optimistic, confident, and positive about everything and their failure.
Therefore, self-esteem is very important in the learning process, especially in statistical learning for sports
students. This study described the level of self-esteem of sports students in statistical learning through SRLE
learning model. SRLE stands for Statistical Reasoning Learning Environment, a student-centred learning
model proposed by Garfield dan Ben-Zvi (2007) aims at developing statistical reasoning skill. It is also a
learning model based on constructivist social theory with six learning principles designed by Cobb and
McClain (Garfield, 2002). These principles focus on developing statistical content, using real data, using
classroom activities and technology assistance, improving classroom conversations and using alternative
assessments. The instrument used is questionnaire referring to Coppersmith which defines self-esteem as a
person’s judgment of capability, successfulness, significance, and worthiness expressed in form of attitude
toward himself. Of 43 students attending statistics lecture, the overall descriptions about self-esteem level was
obtained. 34.88% of the students had low self-esteem, 58.14% belonged to medium self-esteem, and 6.97%
to high self-esteem. From the gender perspective, 28 male students were categorized to have low self-esteem
with the percentage of 25%, medium self-esteem 64.3%, and high self-esteem 10.7%. 15 female students had
a low self-esteem rate of 53.3%, medium 46.7% and a high self-esteem rate of 0%. While viewed from the
profession perspective between athletes and non-athletes, 29 athletes were included to have low self-esteem
with the percentage of 34.5%, medium self-esteem 58.6%, and high self-esteem 6.9%. In the other hand, 14
non-athletes had low self-esteem 34.5%, medium 58.6%, and high self-esteem 7%. From the overall results,
it can be concluded that the sport students’ self-esteem level in learning statistics in terms of gender and
professions (athletes or non-athletes) still needs to improve.
1 INTRODUCTION
The statistics course is seen as a fairly difficult course
for most sports students and some of them are even
shocked to learn it. This perception is one of the
obstacles for the lecturers in this course. Besides,
students’ field activities also affect their
concentration during the statistic lecture in the
classroom. This problem motivates the lectures to
provide the material presentation more creative and
innovative. A preliminary study was conducted on
sports students regarding statistical learning. Four
questions were given to the students: (1) Is learning
statistics fun? Why? (2) Is learning statistics difficult?
What are the difficulties? (3) What do you know
about the benefits of statistical courses for sports? (4)
What do you expect in a statistical course study?
These questions were given to 20 students of the sport
coaching program who had attended statistical
lectures. The results of preliminary survey showed
that 90% of the students enjoyed learning statistics
because it was not boring and very useful for
processing and measurements of the data in sports,
the learning process also used technology which
made it more interesting, the presented material was
understandable and delivered well. Contrarily, 10%
of the students were not pleased to study statistics as
it was difficult course. With regard to the question of
whether it is difficult or not in the lectures of
statistics, 80% of students had difficulties in learning
470
Hidayah, N., Wahyudin, W., Turmudi, T. and Mulyana, D.
Building Sport Student Self-Esteem in Learning Statistics through SRLE - Statistical Reasoning Learning Environment.
In Proceedings of the 2nd International Conference on Sports Science, Health and Physical Education (ICSSHPE 2017) - Volume 1, pages 470-475
ISBN: 978-989-758-317-9
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

statistics, especially on understanding and analyzing,
selecting and using statistical approaches (formulas)
and concluding meaning of the
calculation/processing results and 20% of the
students had no difficulties in learning statistics. The
survey also revealed some benefits of statistics course
for sport students such as processing data for the
research paper (30%), understanding the athletes’
development and making statistics as the reference in
planning better exercise program (45%), and the other
25% responded that statistics was useful to process
the data before the decision made and to become a
reference in making exercise program so it could
produce the best athlete. It is expected that the results
of learning statistics can be applied in sport activities,
especially for the coaches in planning exercise
program and for the students in writing the research
paper and for their future work.
Statistics has very important roles in sports
because there are many measurements which need to
be processed and analyzed statistically. The results of
processing and analyzing the data are very useful in
obtaining conclusions or decisions to improve the
quality of physical education, to develop an exercise
program or to choose the right measuring tools in
improving achievement. The use of statistics at sport
cannot be avoided because in a variety of
competitions there will be some achievements
according to statistic calculations, such speed (in
sport and running), frequencies (multiple scores) in
basketball, soccer, badminton, volleyball and so
forth. Hence, the results of matches and race
competition result the data that can be processed and
presented statistically. There are a number of
previous researches related to the sports and statistics.
One of them is a research conducted by Kuper dan
Elmer from University of Groningen entitling
“Modelling the Development of World Records in
Running”. This research described a new
development model for a world record run from 100
meters to marathon both for men and women by using
time-series method. Another study was "Statistical
Analysis of The Effectiveness of the FIFA World
Rankings" conducted by Ian McHale and Stephen
Davies from the University of Salford. This study
proposed a model for predicting the soccer match
result for the national teams, and assessed the extent
to which such result contributed to the FIFA rank of
one country (Albert J. Koning, 2008).
Statistics learning is taught by making sport as its
context. The real data for sports investigation as
discussed in various media either through internet or
directly from field was given in statistics learning
(Tabor, 2013). Referring to the importance of
statistics for research, education, and evaluation in
practice or competition, the previous research showed
that the literacy ability and statistical reasoning of
sports student were still not satisfied. This indicated
that the results of learning process had not reached the
expected goals. Therefore it is necessary to engage
the psychological factors that students need in the
learning process to encourage learning statistic
results. One of the psychological factors that can
support success in the learning process is self-esteem.
Rusli Lutan (2003) states that self-esteem is self-
acceptance, by oneself that we are worthy, valuable,
capable and useful no matter what is, or will be. The
growing feeling of "I can and I am worthy" is the
essence of self-esteem. He further elaborates that self-
esteem for someone is like the foundation of a house
building. Self-esteem is an important structure for the
development of other abilities. Based on self-esteem
there will be an achievement. When self-esteem and
self-assessment are low then anything we build on
will undoubtedly be cracked easily. That is why self-
esteem should be built as strong as possible in order
to achieve a better quality of life. Coopersmith (1967)
defines self-esteem as a person's judgment of
capability. Someone’s success, significance, and
worthiness of himself are expressed in his attitude to
himself. Pujiastuti (2014) stated that a person's self-
esteem in a particular field is a person's judgment
about his or her own ability, success, usefulness, and
worthiness in the field. Statistical self-esteem is a
person's judgment of capability, successes,
significance, and worthiness in statistics.
In this study we will illustrate how the level of self
-esteem of sports students in statistical learning is
reviewed in whole, by gender (male, female) and by
profession (athlete, non-athlete).
1.1 Self-esteem Statistics
Self Esteem is the way in which a person evaluates
himself. This evaluation will show how the
individual's judgment of respect for himself,
believes himself to have the ability or not, the
admission (acceptance) or not. The Self Esteem as
defined by Coopersmith (1967: 4-5): “Self Esteem
was the evaluation which the individual makes and
customarily maintains with regard to himself: it
expresses an attitude of approval or disapproval,
and indicates the extent to which the individual
believes himself to be capable, significant,
successful and worthy. In short, self Esteem is a
personal judgment of worthiness that is expressed in
the attitudes the individual holds toward himself”.
Building Sport Student Self-Esteem in Learning Statistics through SRLE - Statistical Reasoning Learning Environment
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Self Esteem is an evaluation made by
individuals and habits of seeing themselves
especially about acceptance or rejection, and an
indication of the magnitude of individual
confidence in capability, One’s success,
significance, and worthiness of himself. The level
of Self Esteem is a "personal judgment" of a
valuable or meaningful feeling expressed in the
individual's attitudes toward him. thus, aspect of self
esteem studied in this research is capability aspect
that is showing a high performance to fulfill
requirement to reach achievement where level and
duties depend on age variation of someone.
successness of a person's ability to manage and
control behavior and gain recognition of the
behavior from others. The significance refers to the
concern, attention, affection and expression
received by someone from others who show the
acceptance and popularity of the individual from the
social environment. Worthiness implies an
obedience to the moral and ethical standards and
religions in which the individual will stay away
from behaviors that should be avoided and conduct
the behavior permitted by morals, ethics and
religion.
The beginning of a healthy self-esteem coaching
is to teach students to understand who they are,
especially with regard to the advantages and
disadvantages of the students. In the context of
statistical learning, the environment in question is a
statistical learning activity that involves the active
participation of all students in implementing the
teacher's teaching. The goal is no other to provide a
successful experience through awarding (rewards that
become part of the feedback) to each student so that
each student is able to appreciate the advantages
possessed by each student.
A person with high self esteem tends to be more
attractive to have a good relationship with others and
can make good impressions than those with low self
esteem (Braumeister, 2003). In a group, a person with
a high self-esteem tends to be more daring to appear
and critical of his group. Although not directly
affecting self-esteem can also affect the nature of
one's leadership. This is because someone with high
self esteem tends to be superior than those who have
low self esteem.
According to Alhadad (2010), students with high
self-esteem look more optimistic, confident, and
always be positive about everything, also against the
failure that happened. At the time of failure, students
with high self-esteem tend to see the failure not as the
end of everything, but make the failure as a valuable
experience to move forward. Looking at the mistakes
that have been done before as a valuable lesson and
provision to achieve better results, it is because the
success basically achieved at this time can not be
separated from mistakes that have been done before.
Students with high self esteem, able to appreciate
himself and see the positive things that can be done
for success in the future.
On the contrary, students who have low self-
esteem believe and see that he is weak, unable to do
nothing, not have the ability, tend to feel himself
always failed, unattractive, disliked, and lose the
appeal to life. Students with low self esteem tend to
be pessimistic about life and opportunities. They do
not see a challenge as an opportunity, but rather as an
obstacle, give up easily before trying and when they
fail, blame themselves and blame others. It is possible
that the low self-esteem of students can negatively
affect their learning achievement. Therefore, self
esteem needs to get special attention from parents and
teachers.
Teachers and parents should focus on developing
student self esteem, because with high self esteem
many positive things that can arise from the students.
Braumeister (2003) also stated that high self esteem
is a part of good student achievement in school.
According to Alhadad, low student achievement in
mathematics lessons tends to frustrate students.
Students will assume that forever they will not be able
to achieve a good achievement in math lessons. When
dealing with mathematical problems, students feel
desperate and think they can not solve them, even
before they make the most of their efforts to solve
them. Attitudes like this certainly can negatively
affect the development of students in the learning
process. Therefore, teachers as educators have an
important role in building and developing self esteem
students.
One effort to develop self esteem of students is by
giving responsibility to students in learning (Muijs
and Reynolds, 2008). Teachers can assign tasks to
students in the form of challenging issues and give
them confidence and convince them that they can
accomplish these tasks well. Teachers can reward or
appreciate the results of student work. even they are
simple ideas, opinions, questions, or results obtained
by students, teachers still give appreciation to
students wisely. When students make mistakes, the
teacher must make sure that the error is part of the
learning process, not a failure. With this process,
students will feel appreciated, needed, and will slowly
awaken confidence and pride in themselves.
In addition, students' learning environment also
affects students' self-esteem. As according to Tran
(2012) that the learning environment is very
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influential on student self-esteem. A conducive-
learning environment can support and help students
develop their self-esteem. In this case, teachers have
an important role to play in creating a conducive
learning environment that provides opportunities for
students to contribute and be actively involved in
learning. Involvement and participation of students in
the learning process, will make students feel that their
existence is needed and appreciated. Therefore, to
develop student self-esteem, the teacher should
consider aspects of the self esteem. Tracy (2007: 50)
suggests that self esteem is a person's ability to
appreciate himself, appreciate the advantages and
know his own weakness.
Based on the definition and explanation described
above, by taking the definition of Coopersmith it can
be concluded that one's self esteem in a particular
field is one's judgment about the ability, success,
usefulness, and self-worth in the field (Pujiastuti,
2014). The self-esteem studied in this study is
particularly relevant to the context of statitics and
hereinafter referred to as self-esteem statistics (SES).
Thus, statistical self-esteem is a person's assessment
of capability, successnes, significance, and
worthiness of himself in statistics.
Students who have high statistical self esteem will
show optimism and positive thinking toward
statistics, feel that they have a high ability in
mathematics, and feel proud of the potential it has in
statistics. Students with high statistical self esteem
will view a statistical problem as a challenge to be
faced and strive to find its solution. When these
problems can not be solved immediately, they are not
easily discouraged.
Students with high statistical self esteem feel their
existence play a role and determine the success of
statistical learning process conducted in the
classroom. Feeling that he has contributed to the
implementation of learning that occurred. Questions,
opinions or ideas also provide its own color in the
learning process. Students with high statistical self
esteem feel that they deserve a high score in statistics,
and feel themselves needed by others in terms of
statistics.
While students with low statistical self esteem
will view statistics as a burden. Feeling no pride and
any excess in statistics. It's more interesting to talk
about something else than to talk about statistics.
Despair and pessimism when faced with a statistical
problem. a statistical problem is regarded as a
problem that can never be solved well. In the
classroom learning process, students with low
statistical self esteem will feel that their existence
does not make any contribution and feel they can not
provide any assistance when others are experiencing
difficulties in statistics.
1.2 SRLE (Statistical Reasoning
Learning Environment)
This learning model is a learning model to develop
the ability of statistical reasoning introduced by
Garfield and Ben-Zvi (2007) that is "Statistical
Reasoning Learning Environment" or abbreviated as
SRLE. SRLE is a learning model based on
constructivist social theory with six learning
principles designed by Cobb and McClain (Garfield,
2002) focusing on developing statistical content,
using real data, using classroom activities, using
technology help, improving classroom conversations
and using alternative assessments .
Fundamental ideas or statistical content by
researchers has contributed to a learning approach
emphasizing Data Exploration Analysis (EDA),
focusing on building students 'conceptual
understandings, and curricula aimed at developing
students' reasoning, thinking and literacy (Ben-Zvi
and Garfield, 2004; Garfield and Ben-Zvi, 2008).
There are many ideas or statistical content that the
students must master in depth. This includes data,
distribution, concentration measures and data trends,
variability, etc. Many textbooks present materials
based on logical content analysis, students often view
the content as a set of tools or procedures and do not
see how concepts are interconnected. The focus of
learning objectives is no longer just that students can
count, but rather emphasize how they know the
reasons for the answers and help them recognize how
they form the supporting structures of statistical
knowledge.
The effectivity of learning and assessment of the
real situation depend on the data understanding and
analysis, and types of conclusions that can be drawn
through learning data. The students should collect
and produce their own data, find out why these
method affect the quality of the data, and know the
appropriate type of analysis. A set of interesting data
will encourage the students to engage in activities,
especially activities that require the students to
conjecture the data before analyzing.
One of important parts in SRLE is that it should
be designed carefully such as research-based
activities which improve the students’ learning by
means of collaboration, interaction, discussions of
interesting problem. There are two different
classroom activity models in SRLE. The first activity
involves the students in making conjecture related to
the problem or data. This method involves discussing
Building Sport Student Self-Esteem in Learning Statistics through SRLE - Statistical Reasoning Learning Environment
473

of student conjecture, collecting or accessing relevant
data, using technology to test conjectures, discussing
the results obtained, and reflecting on their actions
and thoughts. The second activity is based on
cooperative learning. The students are divided into
group consisting of two or more students for each
group. Then, the group is given questions to discuss
or problems to solve.
Recently, there are many various technologies
that support development of students' statistical
understanding and reasoning, such as computers,
graphing calculators, internet and statistical software.
Students are no longer supposed to spend time doing
complicated and monotonous calculations. Students
can focus more on the important task of how to
choose suitable analytical method and to interpret the
results. The use of activity and technology makes it
possible to form new class conversations. It is a
challenge to create SRLE with a classroom
conversation that allows students to engage in
discussions of significant statistical issues. The
presented arguments can be negotiated openly and
meaningfully by the students. There are several forms
of alternative assessments that can be used in
statistics class. in addition to quiz, homework, and
test, many teachers also use authentic assessment.
Other forms of alternative assessment are also used to
assess statistical literacy (eg, criticizing the graphics
of the media), assessing statistical reasoning (eg,
writing meaningful short essays), or giving feedback
to teachers (eg, short papers). Assessment should be
in line with the learning objectives focusing on
understanding key ideas and not just on calculated
skills, procedures, and answers. This can be carried
out through formative assessment during the
course(for example, quiz, small project, or observing
and listening the students in the class) and summative
assessment. The useful and timely feedback is very
important to assess the learning process.
2 METHOD
The research method used was descriptive method
with survey technique. The instrument used was
questionnaire to measure the level of self-esteem of
sports students in statistical learning. The instrument
consisted of 24 statements that could describe the four
aspects of self-esteem namely capability,
successfulness, significance, and worthiness. This
instrument used was adapted from Pujiastuti which
conducted a research to measure the level of student's
mathematical self-esteem SMP. The instrument was
firstly tested to the 16 students who had passed the
statistics course and the result showed the validity and
reliability for all items.
43 students of sport science taking statistics
course were selected as the research sample and the
statistical processing used was percentage.
3 RESULTS
Based on the results of the research, the overall
student had low self-esteem level with the percentage
of 34.9%, medium 58.1%, and high self-esteem 7%.
From the gender view obtained for 28 men, 25% of
the male students had low self-esteem, medium
64,3% and high 10.7%.and of 15 women, 53% female
had low self-esteem level, medium 46,7% and high
self-esteem level 0%. While viewed from the
profession perspective between athletes and non-
athletes, 29 athletes were included to have low self-
esteem with the percentage of 34.5%, moderate self-
esteem 58.6%, and high self-esteem 6.9%. In the
other hand, 14 non-athletes had low self-esteem
34.5%, moderate 58.6%, and high self-esteem 7%.
4 DISCUSSION
The results above shows that the percentage of sport
students who have high self-esteem level is still small
compared to medium self-esteem level which has the
highest percentage, and low level of self-esteem
percentage is still high enough. From the gender
view, no one has high level of self-esteem. Instead,
most female student had low level of self-esteem. For
the male students, the percentage of high level of self-
esteem is small (10.7%) and the most percentage is
for medium level of self-esteem (64.3%).
Furthermore, viewed from the professions as athletes
and non-athletes, most of them have moderate level
of self-esteem (58%) and the least percentage is for
high self-esteem (7%).
5 CONCLUSIONS
Self-esteem in statistical learning for sports students
is necessary, but the results show that the level of self-
esteem of sports students in statistical learning
through the learning model of SRLE still needs to be
improved in terms of overall aspects, gender or
professions as athlete or non athlete.
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474

REFERENCES
Albert J., Koning Ruud. 2008. Statistical Thinking in Sport,
Chapman and Hall CRC, Taylor and Francis Group.
Alhadad. 2010. Meningkatkan Kemampuan representasi
Multiple Matematis, Pemecahan Masalah Matematis,
dan Self Esteem Siswa SMP melalui Pembelajaan
dengan Pendekatan Open ended. Bandung. Disertasi
SPs UPI. Tidak diterbitkan.
Braumeister, R, F., Campbell, J. D., Krueger, J. I., Vohs, K.
D. 2003. Does high selfesteem cause better
performance, interpersonal success, happiness, or
healthier lifestyles? Psychological Science in the Public
Interest, 4, 1-44.
Coopeersmith, S. 1967. The Antecedents of Self –esteem,
W.H. Freemantand Company.
Garfield, J. B. 2002. The Challenge of Developing
Statistical Reasoning, in Journal of Statistics
Education, 10(3).
Garfield, J., Ben-Zvi, D. 2004. Statistical Literacy,
Reasoning and Thinking: Goal, Definition and
Challenges. In D. Ben-Zvi and J. Garfield (Eds), The
Challenge of Developing Statistical Literacy,
Reasoning, and Thinking. The Netherlands: Kluwer
Academic Publishers, USA.
Garfield, J. 2007. Helping Student Develop Statistical
Reasoning: Implementing A Statistical Reasoning
Learning Environment. Tersedia:
http://www.causeweb.org/workshop/aims/statistical
Reasoning Learning Environment.pdf.
Muijs, D., Reynold, D. 2008. Effective Teaching :
Evidence. Terjemahan : Soetjipto, H. P dan Soetjipto,
S. M, Yogyakarta: Pustaka Pelajar.
Pujiastuti, 2014. Pembelajaran Inquiri Co-opeartion Model
untuk Meningkatkan Kemampuan Pemecahan
Masalah, Komunikasi dan Self-esteem Matematis
Siswa SMP, Bandung, disertasi SPS UPI. Tidak
diterbitkan.
Rusli Lutan. 2003. Self-esteem: Landasan Kepribadian,
Ditjen Keolahragaan , Jakarta.
Tabor, 2013 Statistical Reasoning in Sports, W.H. Freeman
and Company, New York.
Tran, V. D. 2012. Predicting the Attitudes and Self-
esteemof the Grade 9th Lower Secondary School
Students Towards Perceptions of the Classroom
Learning Environment, World Journal of Education
vol. 2, N0.4, August 2012.
Tracy, B., 2007. Change Your Thinking, Change your life:
Bebaskan Potensi Dahsyat Anda untuk Kesuksesan
Yang Tak Terbatas, Bandung : Kaifa.
Building Sport Student Self-Esteem in Learning Statistics through SRLE - Statistical Reasoning Learning Environment
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