ACTIVE LEARNING TO
FIND CONCEPTS AND ALGORITHMS IN DECIMAL MATERIAL IN CLASS V ELEMENTARY SCHOOL
Taruly Tampubolon, Robert Harianja, Sariayu Sibarani*
Faculty of Education,
Universitas Sisingamangaraja XII Tapanuli, Silangit, Indonesia
Email:
[email protected]*
Article
Information |
|
ABSTRACT |
Received:
December 28, 2022 Revised:
January 7, 2023 Approved:
January 14, 2023 Online:
January 27, 2023 |
|
Prior to learning, pre-tests and
questionnaires were given to determine students' abilities and interests in
learning decimal. Based on the results of the initial test, it was found that
students' initial abilities were very low with an average grade of 15.50, and
from the results of the questionnaire, all students said they did not like
decimal learning. After active learning to find the concept of algorithms in
decimal material, the class average value was 86.27, meaning that the level
of classical student mastery was 86.27. This indicated that the student
mastery level was relatively high. Of the 20 students, there were 19 people
or 95.0% who had finished studying, so that classically learning decimal
material had been completed. Judging from the specific learning objectives,
all of them achieved above 65%. The results of the student questionnaire
after the decimal material learning outcomes test was completed, obtained
data that students felt happy with the learning they had just participated
in. Students argue, the way is easy to understand and understand. With simple
but interesting teaching aids, it can increase students' enthusiasm and
interest in learning Mathematics. The classical learning outcomes have been
completed based on the learning completeness criteria specified in the curriculum,
specific learning objectives have been achieved based on the learning
objectives achievement criteria, the student's response to learning is
positive, the student's mastery of the material is high. It can be concluded
that learning on decimal material in class V Elementary already effective. |
Keywords |
|
|
active learning; finding algorithms; Mathematics |
|
INTRODUCTION
Learning
is what students do, not what teachers do for students (Edwards & Protheroe, 2003).
Learning is an active and purposeful process, not a passive process. This
process may be more successful if appropriate learning tools are used and
students are directed to the required activities at the right time (Nartiningrum & Nugroho, 2020).
Learning conditions are closely related to the expected results. If only
mastery of Mathematical operations is desired, then a learning process that is
rote, exercises and tests is very sufficient. However, the expected results
from teaching Mathematics today are much broader and deeper than just mastering
Mathematical operations. A very important responsibility of the Mathematics
teacher is to encourage creativity by helping students discover the basic
ideas, rules and principles of Mathematics (Lopes et al., 2019).
As a result of this emphasis on understanding and skills, many students will
eventually find that the most interesting thing is studying Math. One feature
that stands out in present-day Mathematics teaching is the increasing attention
to developing the ability to find, examine and make generalizations. If
students are expected to master these abilities, teachers must pay more
attention to concept development and terminology.
From
studies and findings of experts and researchers that in the process of thinking,
children go through various cognitive levels. One way to minimize this
happening is to help students find certain ideas and ways for themselves.or
algorithms to solve problems (Lorensia & Wea, 2015).
According
to Nurhadi quoted in the 2004 Curriculum Book Questions and Answers (2004) says
that the objectives of learning Mathematics are as follows (Hadi, 2004):
1. Train
ways of thinking and reasoning in drawing conclusions, for example through
investigation, exploration, experimentation, showing similarities, differences,
consistency and inconsistency.
2. Develop
creative activities involving imagination, intuition, and discovery by
developing divergent, original thinking, curiosity, making predictions and
conjectures, and experimenting.
3. Develop
problem solving skills.
4. Developing
the ability to convey information or communicate ideas, among others through
oral conversations, notes, graphs, maps, diagrams, in explaining ideas.
We
admit that every child learns at his own pace with a different style if they
are prepared to learn. The Master's responsibility here is not only to
encourage and motivate this readiness by providing a favorable environment, but
also to provide it with diverse and effective experiences (Tampubolon, 2018).
Thus, a teacher can design learning according to the readiness of his students (Gustiati, 2017).
The
successful teacher always stimulates his students to plunge into a process and
find the rules or methods for himself and then follow it with a discussion.
Teachers and learning theorists have done just that. Students need time to
investigate and discover patterns and relationships (Fitrina et al., 2016).
They must make observations, organize these observations and then make
conjectures and test the truth of these conjectures. The ability to make
generalizations from these observations is at the core of the learning process.
The
importance of students doing their own research becomes very clear when we
realize that learning Mathematics is participating and not just watching a
sports match (Ekawati, 2015).
Thus, students will realize and understand what they are learning, how long
they can retain what they have learned and what kind of behavior arises as a
result of what they have learned.
METHODS
In
accordance with the expected goals, the approach taken is a qualitative
descriptive (Creswell
& Poth, 2016) approach which then from the
results obtained later, will be developed into an alternative learning to
increase the activity of finding algorithms in decimal material in elementary
schools. As subjects in the study were fifth grade students at Public Elementary School
177657 Siabalabal Kec. Sipahutar Kab. North Tapanuli for the 2020/2021 academic
year. Meanwhile, the object of this research is student learning outcomes as a
result of learning actions to increase activities to find algorithms in decimal
matter.
A. Research procedure
The steps taken in this
research are as follows:
1. Preparation
phase
At this stage the author
analyzes the decimal material contained in the textbook. Then the writer makes
a lesson plan (as contained in part B above), which is the result of being
discussed with several teachers and Mathematics lecturers.
2.
Implementation stage
a. Before
learning is carried out, the writer provides scissors, cardboard, ruler,
plastic bag, gives initial tests and questionnaires
b. Conduct
learning according to the steps in part B. During the learning process,
observations were made by two teachers at the school where the study was
conducted to observe student activity during learning.
c. After
learning is complete, practice doing the questions. A week later, a test was
carried out to determine student success in learning decimal material.
d. After
the test was carried out, students were given a questionnaire to find out the
student's response to the learning that had passed.
B. Data analysis technique
1. Analysis
of Learning Outcomes Tests
The learning outcomes test
used refers to the behavior criteria to be achieved or the Test Benchmark
Reference Assessment. This learning achievement test was prepared based on the
formulation of specific learning objectives (TPK), in its preparation the
author asked for responses from several Mathematics Teachers and Lecturers.
There are 10 questions in this test. Furthermore, these items were tested on 40
students of grade V Elementary
School, the trial data were
analyzed. Test data analysis is an evaluation procedure for test quality. In
the construction of the test, then the results of the analysis are used as
input for revising the questions and this is what is used for the test at the
end of the lesson. The intended trial data analysis includes:
2. Item Validity
Item validity is calculated
to find out how far the relationship between one item's answers and the total
score is. Arikunto (2013) states that to find out
whether a measuring instrument has empirical validity, is to correlate the
scores obtained on each item with the total score. If all statements compiled
based on the concept are positively correlated with a total score, then it can
be said that the measuring instrument has validity. This kind of validity
states the validity of the item. To determine the validity of the item, the
product moment correlation formula can be used as follows:
r
with x = item score
y = total score
r= correlation coefficient between the item scores and
the total score
N = the number
of students who took the test
(Arikunto,
2013)
For
the interpretation of the correlation coefficient, the following range is used:
r
≤ 0.20 degrees very low validity
0.20 < r ≤
0.40 degrees low validity
0.40 < r ≤ 0.60 degrees
moderate validity
0.60 < r ≤ 0.80 degrees
has high validity
0.80 < r ≤ 1.00 degrees
very high validity
3. Discriminatory Power
An item has good
discriminating power if the item can distinguish between smart students (upper
group) and weak students (lower group). The discriminating power index is
calculated using the –F statistic and –t statistic. Before the –t statistic is
used, it is necessary to test the similarity of variance between the upper and
lower groups. Due to the variance of the two groups, ie and is not known, then the variance is estimated
respectively with and
.
Formula to determine and are as follows:
= and =
with = upper group
variance
= lower group
variance
= score of
each upper group
= score of
each lower group
= average
score of the upper group
= average
score of the lower group
Moreover, we will test the
similarity of the two variances of the upper and lower groups using the –F
statistic. To that end, the following hypothesis is formulated:
H: = andH H: ≠ . The formula used is:
F
with criteria:
accept H, if F ≤ F ≤ . If the variance of the lower group is the same, then
the following t statistic is used to test the significance of the difference in
the mean of the upper and lower groups:
with (Ferguson,
1981: 182)
The
formulation of the hypothesis is: and
( and ) each
estimate o fand )
With criteria:
if t> t, then the test
items are significant, and
if t≤ t , then the
test items are not significant.
If the variances of the upper and lower
groups are not the same, then to test the significance of the differences in
the upper and lower groups the following formula is used:
and
If
>,
then the test items are significant and if ≤,
then the test items are not significant.
4. Test Reliability
Test
reliability is measured using the formula:
with is the
reliability coefficient of the test
K
is the number of test items
is the total variance of the test items
is the total variance
5. Sensitivity Test
To obtain the
effectiveness coefficients of items based on learning, the teacher must give
the same test before and after learning. Effective items will be answered
correctly by more students after learning than before learning (Purwanto,
1984). The sensitivity
measure of an item is basically a measure of how well the item differentiates
between students who have received the lesson and those who have not. To
calculate the sensitivity of the items used the following formula:
with S = the
sensitivity of the item
and = each
subject's total score before learning.
Maximum score = maximum score for each test
item
Minimum score = minimum score for each test
item
N = Number of students who took the
pre-test and post-test
Test items are said to be
good if the sensitivity of the test items is between 0 and 1. The criteria used
to state that an item is sensitive to learning is if S ≥ 0.30.
C. Analysis of Learning Outcome
Test Data
To analyze the test data on learning outcomes
is carried out with the following steps:
1. Student
mastery level
According
to Nurkancana in Helen (2005), the level of student mastery will be reflected
in the high and low raw scores achieved and the conversion guidelines used are
on a scale of five absolute norms.
To
determine the level of mastery of students used the following formula:
PPS
=where,
PPS = percentage of student mastery
x
= score obtained by students
n
= the maximum score of the question
Table 1
Mastery level
criteria
No. |
Percentage |
Mastery level |
1 2 3 4 5 |
90-100 80-89 65-74 55-69 0-54 |
very high high moderate low very low |
2. Completeness
of student learning
To
determine the percentage of student absorption (PDS) individually, the
following formula is used:
PDS
=where,
PDS = Percentage of students' absorption
x
= score obtained by students
n
= maximum score of the question
with
criteria: 0% < PDS < 65%: students have not finished studying
65 % ≤ PDS ≤ 100%: students have
finished studying
To find out the percentage of
students who have studied classically, the formula is used:
D = where,
D = percentage of classical learning completeness
x = the number of students
who have completed learning
N
= total number of students
Based on the learning
completeness criteria, if in that class there are 85% who have achieved at
least 65% absorption, then classical learning mastery has been achieved.
The completeness of each TPK
is done by calculating the achievement of each item with the following formula:
T = where, T = the
attainment of each item
Si
= total student scores for each item
Smax = total maximum score for
item i (which represents each TPK
With the criteria: 0% ≤ T < 65%: TPK has not
been completed
65%≤ T
≤ 100%: TPK has been completed
The TPK achievement criteria are considered
complete if at least 75% of the entire set TPK has been achieved.
While the results of student responses were
analyzed descriptively quantitatively in the form of percentages. Student
responses are said to be positive if the average percentage obtained is more
than 65% of the percentage of each individual who is in the happy category.
RESULTS
A. Analysis of Question Items
The questions (research instruments)
that had been prepared were tested on 40 grade V elementary school students.
Based on the results of the trial tests, the correlation coefficient r was
obtained. r= 0,522 (the question has a moderate level of
reliability); the results of the validity and difficulty level of the questions
can be seen in the following table:
Table 2
Analysis of Questions
Items
Number |
Validity Coefficient |
Validity Level |
DK
coefficient |
Difficulty
Level |
1. |
0.432 |
Modereta |
58.3 % |
Modereta |
2. |
0.843 |
Very high |
50.0 % |
Modereta |
3. |
0.1916 |
Very low |
36.6 % |
Modereta |
4. |
0.472 |
Modereta |
58.3 % |
Modereta |
5. |
0.3198 |
Low |
33.3 % |
Modereta |
6. |
0.0827 |
Very low |
75.0 % |
Modereta |
7. |
0.603 |
High |
75.0 % |
Modereta |
8. |
0.555 |
Modereta |
66.7 % |
Modereta |
9. |
0.0276 |
Very low |
33.3 % |
Modereta |
10. |
0.602 |
High |
50.0 % |
Modereta |
Based on the reliability
analysis of the questions and the table above, it can be concluded that the ten
items can be used to measure the level of fifth grade students' mastery of the
subject matter of decimals.
B. Analysis of Student Learning
Outcomes
Based on the results of the
calculation of data analysis (scores) of student learning outcomes obtained as
follows: The average score of student learning outcomes is 86.27, meaning that
the learning outcomes of fifth grade elementary school students for decimal
material are high, thus the level of student mastery of decimal material is
high ; classical student learning completeness, out of 20 students there are 19
people or 95.0% complete learning. Judging from the specific learning
objectives, all of them achieved above 65%. From the results of observing
student activities, all students were very active, the results of the
questionnaire given to students after the learning outcomes test on decimal
material was completed, obtained all data that students felt happy with the
learning they had just participated in. Students think that this way is easy to
understand and easy to catch. In addition, with simple but interesting teaching
aids, it can increase students' enthusiasm and interest in learning
Mathematics.
From the description above,
it is obtained that the results of classical learning have been completed based
on the learning completeness criteria specified in the curriculum, specific
learning objectives have been achieved based on the criteria for achieving
learning objectives, student response to learning is positive, student mastery
of material is classified as moderate. Thus it can be concluded that learning
on decimal material in class V Elementart School
has been effective.
CONCLUSION
Based
on the discussion and research results including the experience of researchers
during the research, it can be concluded as follows; (1) the
average score obtained by fifth grade elementary school students for decimal
material was good, namely 76.27, (2) the
level of student mastery of decimal material is moderate, namely 76.27%, (3) of the
20 students, there were 19 people or 95.5% of the 20 students who completed the
study, meaning that classically learning for decimal material had been
completed, and all of the specific learning objectives were achieved above 65%.
Thus that learning for decimal material has been completed., and (4) student
response to learning decimal material is positive.
REFERENCES
Arikunto, S. (2013). Prosedur penelitian suatu
pendekatan praktik. Jakarta. Google Scholar
Creswell, J. W., & Poth, C. N. (2016). Qualitative
inquiry and research design: Choosing among five approaches. Sage
publications. Google Scholar
Edwards, A., & Protheroe, L. (2003). Learning to
see in classrooms: What are student teachers learning about teaching and
learning while learning to teach in schools? British Educational Research
Journal, 29(2), 227–242. Google Scholar
Ekawati, A. (2015). Pengaruh kecemasan terhadap hasil
belajar matematika siswa kelas VII SMPN 13 Banjarmasin. Math Didactic:
Jurnal Pendidikan Matematika, 1(3). Google Scholar
Fitrina, T., Ikhsan, M., & Munzir, S. (2016).
Peningkatan Kemampuan Berpikir Kreatif dan Komunikasi Matematis Siswa SMA
melalui Model Pembelajaran Project Based Learning Berbasis Debat. Jurnal
Didaktik Matematika, 3(1), 87–95. Google Scholar
Gustiati, M. (2017). Profil kemampuan penalaran
matematis dalam pemecahan masalah ditinjau dari kecerdasan emosional dan gaya
belajar siswa. Pascasarjana. Google Scholar
Hadi, N. (2004). Kurikulum 2004 Pertanyaan dan
Jawaban. Jakarta: Gramedia. Google Scholar
Hamalik, Oemar
(2003), Proses Belajar Mengajar, Bumi Aksara, Jakarta. Google Scholar
Lopes, J., Silva, H., Catarino, P., Morais, E., &
Vasco, P. (2019). Cooperative learning on promoting creative thinking and
mathematical creativity in higher education. REICE. Revista Iberoamericana
Sobre Calidad, Eficacia y Cambio En Educacion, 17(3), 5–22. Google Scholar
Lorensia, M., & Wea, M. Y. (2015). Keefektifan
Problem Posing Ditinjau dari Kemampuan Memecahkan Masalah Matematis dan
Kreativitas Siswa SD Di Kabupaten Manggarai. Jurnal Pendidikan Dan
Kebudayaan Missio, 7(1), 32–39. Google Scholar
Marsini. (2006), Penerapan Pendekatan Kontekstual
(Contextual Teaching and Learning). Depdikbud, Jakarta Google Scholar
Nartiningrum, N., & Nugroho, A. (2020). Online
learning amidst global pandemic: EFL students’ challenges, suggestions, and
needed materials. ENGLISH FRANCA: Academic Journal of English Language and
Education, 4(2), 115–140. Google Scholar
Purwanto, M. N. (1984). Theoretical and Practical
education. Bandung: Youth Work. Google Scholar
Sukino, dkk.
(2018) Matematika untuk S.D. Kelas VII, Penerbit, Erlangga Jakarta
Tampubolon, T. (2018). Pembelajaran Aktif Dengan
Percobaan Pada Bilangan Cacah Di Kelas V SDN 173189 Sosorpahu Kecamatan
Sipahutar. Tapanuli Journals, 1(1), 43–55. Google Scholar