6UL +DVWXWL 1RHU

Sri Hastuti Noer

ISSN 2087-8885

E-ISSN 2407-0610

Journal on Mathematics Education

Volume xx, No. x, January xxxx, pp. x-xx

1

THE EFFECT OF SELF-LEARNING AND ACHIEVEMENT

MOTIVATION ON STUDENTS’ MATHEMATICAL

COMMUNICATION ABILITY IN ONLINE LEARNING

Sri Hastuti Noer1, Mella Triana

2, Pentatito Gunowibowo

3, Bintang Regina Astuti

4

Mathematics and Science Education Department, Faculty of Teacher Training and Education, University of Lampung,

Indonesia

Email: [email protected]

Abstract

The Covid-19 pandemic has changed the order of life, including in education. The policy of learning from

home makes everyone involved in education ready to do online learning. Although technological advances

allow students to learn completely online, online learning requires a higher level of self-motivation and self-

learning. Therefore, increasing self-learning and achievement motivation by embedding various features in an

online learning environment seems to be effective in improving students' mathematics learning outcomes. With

the current condition of online learning, students have more difficulty learning mathematics if the teacher is not

able to manage learning. Some of the obstacles in online learning include the learning media used by the

teacher is dominantly monotonous and makes students feel bored, learning is not yet interactive and tends to be

online assignments. A preliminary study of 46 mathematics teachers showed that 81 percent stated that

students' learning motivation had decreased, 66 percent stated that teachers only distributed practice questions

to students. Most of the teachers have difficulty in delivering teaching materials, difficulties in making learning

tools, difficulties in choosing online learning methods and media. This quantitative research was conducted in

order to examine the results of developing an online learning model to facilitate increased self-learning and

achievement motivation and its impact on students' mathematical communication ability. The population in

this study were all students of class XI science at SMA Negeri 1 Sumberjaya, West Lampung Regency, Even

Semester for the 2020/2021 academic year, which were distributed in three classes. The sample in this study

was class XI IPA 2 as many as 33 students who were selected using cluster random sampling technique. The

design used is a causal correlational design. Research data in the form of quantitative data obtained from the

scale of student self-learning and achievement motivation as well as tests of mathematical communication

ability with sequences and series material. The data analysis technique used is multiple linear regression. The

results of data analysis show that there is a positive influence between self-learning and achievement

motivation on students' mathematical communication ability in online learning.

Keywords: achievement motivation, mathematical communication ability, self-learning

Abstrak

Pandemi Covid-19 telah mengubah tatanan kehidupan, termasuk di bidang pendidikan. Kebijakan belajar dari

rumah membuat semua orang yang terlibat dalam pendidikan siap untuk melakukan pembelajaran online.

Meskipun kemajuan teknologi memungkinkan siswa untuk belajar sepenuhnya secara online, pembelajaran

online membutuhkan tingkat motivasi belajar dan self-learning yang lebih tinggi. Oleh karena itu,

meningkatkan self-learning dan motivasi berprestasi dengan menggunakan berbagai fitur dalam lingkungan

belajar online tampaknya efektif dalam meningkatkan hasil belajar matematika siswa. Dengan kondisi

pembelajaran online saat ini, siswa lebih kesulitan belajar matematika jika guru tidak mampu mengelola

pembelajaran. Beberapa kendala dalam pembelajaran online antara lain media pembelajaran yang digunakan

guru dominan monoton dan membuat siswa merasa bosan, pembelajaran belum interaktif dan guru cenderung

memberikan banyak tugas online. Studi pendahuluan terhadap 46 guru matematika menunjukkan bahwa 81

persen menyatakan motivasi berprestasi siswa mengalami penurunan, 66 persen menyatakan guru hanya

membagikan soal latihan kepada siswa. Sebagian besar guru mengalami kesulitan dalam menyampaikan bahan

ajar, kesulitan dalam membuat perangkat pembelajaran, kesulitan dalam memilih metode dan media

pembelajaran online. Penelitian kuantitatif ini dilakukan dalam rangka menguji hasil pengembangan model

pembelajaran online untuk memfasilitasi peningkatan self-learning dan motivasi berprestasi serta dampaknya

terhadap kemampuan komunikasi matematis siswa. Populasi dalam penelitian ini adalah seluruh siswa kelas XI

IPA SMA Negeri 1 Sumberjaya Kabupaten Lampung Barat Semester Genap Tahun Pelajaran 2020/2021 yang

mailto:[email protected]

2 Journal on Mathematics Education, Volume xx, No. x, January xxxx, pp. xx-xx

terbagi dalam tiga kelas. Sampel dalam penelitian ini adalah siswa kelas XI IPA 2 sebanyak 33 siswa yang

dipilih dengan teknik cluster random sampling. Desain yang digunakan adalah desain korelasional kausal. Data

penelitian berupa data kuantitatif yang diperoleh dari skala self-learning dan motivasi berprestasi siswa serta

tes kemampuan komunikasi matematis dengan materi barisan dan deret. Teknik analisis data yang digunakan

adalah regresi linier berganda. Hasil analisis data menunjukkan bahwa terdapat pengaruh positif antara self-

learning dan motivasi berprestasi terhadap kemampuan komunikasi matematis siswa dalam pembelajaran

online.

Kata kunci: kemampuan komunikasi matematis, motivasi berprestasi, self-learning

How to Cite: Noer, SH, Gunowibowo, P, Triana, M, Astuti, BR. (2021). The Effect of Self-Learning and

Achievement Motivation on Students’ Mathematical Communication Ability in Online Learning. Journal on

Mathematics Education, x (x), xx-xx.

INTRODUCTION

During this pandemic period, all students are required to be independent in learning, because

learning activities are carried out online. Such learning is an educational innovation to answer the

challenges of the current situation by maximizing the role of technology in education. Online learning

really requires students' independence in self-regulation, self-discipline and responsibility for

themselves.

Self-learning according to Mujiman (2011) is an active learning activity that is driven by the

desire to master a competency to solve a problem, using the knowledge that has been possessed.

Self-learning is not self-study, but learning on one's own initiative. Those who are independent are

those who are responsible, intend, take the initiative, have courage, and are able to accept risks.

According to Kompri (2016), in addition to providing the right direction for learning activities,

motivation will also receive positive consideration.

In addition to independent learning, student learning is also influenced by motivation.

Motivation has an important role in generating the desire to learn. Students who have strong

motivation will have high fighting power and enthusiasm to carry out learning activities. Keller

(2010), Suryabrata (2011), and Uno (2014) state that motivation refers to the desire in a person who

encourages him to do certain activities or what he chooses to do and decides his commitment to

achieve a goal.

In online learning, there are still many problems with technology disparities between

households, internet network disparities between regions, and varying teacher technological literacy.

Many teachers experience limited skills in using information and communication technology. One of

the junior high school teachers told at Kompas.com, as written Monday (14/9/2020), that the entire

education program was conducted online. If you don't understand IT, the teacher will have difficulty

with the process. Moreover, each task must be prepared every day. The Head of Balitbangbuk

Kemendikbud in the Public Hearing Meeting Commission X DPR RI, as reported by Republika.co.id

(21/01/21), said that the signs of learning lost had begun to appear. Based on the diagnostic

assessment, it is known that the overall percentage of achievement of student competency standards is

Sri Hastuti Noer, Mella Triana, Pentatito Gunowibowo, Bintang Regina Astuti, The Effect of Self-Learning and Achievement

Motivation on Students’ Mathematical Communication Ability in Online Learning 3

below 50 percent. Considering some of the problems above, it is necessary to take an action to

overcome them.

Depaepe, De Corte and Verschaffel in Afandi (2016) explain that many students have difficulty

solving mathematical problems. With the current condition of online learning, students have more

difficulty if the teacher is not able to manage learning. Some of the obstacles in online learning

include the learning media used by the teacher is dominantly monotonous and makes students feel

bored, learning is not yet interactive and tends to be online assignments. Safitri, RS, and Retnasary, M

(2020), Hamid, R., Sentryo, I., and Hasan, S (2020), stated that online learning had not been carried

out effectively, students and teachers were not ready, learning media were not supportive, carrying

capacity of network access and devices to access the internet, teacher competence in designing

learning needs to be improved. Based on this, it is necessary to develop online learning that is able to

facilitate increased self learning and student achievement motivation. This quantitative research was

conducted in order to examine the results of developing an online learning model to facilitate

increased self-learning and achievement motivation and its impact on students' mathematical

communication ability.

METHOD

This research was a part of developmental research that begins with: (1) research samples

determination, (2) model development , (3) research instruments development, models and research

instruments validation, (4) trialling research instruments, (5) analysing the results of trials, (6)

experiment to applying the developed learning models, (7) analysing the results of the application of

the models. This paper was present the step 6 and 7 from this research. The population in this study

were all students of class XI science at SMA Negeri 1 Sumberjaya, West Lampung Regency, Even

Semester for the 2020/2021 academic year, which were distributed in three classes. The sample of this

study were students from class XI IPA 2 as many as 33 students. Experiments carried out to apply the

developed model, using the one-shot case study. In this one-shot case study design, we assess the

effect of the treatment.

Test and non-test techniques were used to collect data in this study. The test technique is in the

form of an essay test and a non-test in the form of a questionnaire. Essay tests were used to measure

students' mathematical communication skills, while questionnaires were used to measure students'

self-learning and achievement motivation. The steps involved in analysing research data are: 1)

normality test, 2) linearity test, 3) multicollinearity test, 4) autocorrelation test, 5) heteroskedasticities

test, 6) simultaneous F test, 7) partial t test.).


RESULTS AND DISCUSSION

The data obtained from this study are data on students' mathematical communication ability,

student self-learning questionnaires, and achievement motivation questionnaires from class XI IPA 2

SMA Negeri 1 Sumberjaya. The mean, median, mode, maximum value, minimum value, and standard

deviation are described in Table 1.

Table 1. Data of Mathematical Communication, Self-Learning and Achievement Motivation

Student’s

mathematical

communication

Student’s self-learning Student’s

achievement

motivation

N 33 33 33

Average 23,63 48,93 54

Maximum Score 32 67 70

Minimum Score 14 40 40

Deviation

Standard

5,44 6,11 8,91

Variance 29,61 37,43 79,45

Based on the data in Table1, can be seen that the smallest variance is the variance for students'

communication ability data and the largest variance is the variance of achievement motivation data.

This indicates that data on communication ability is more homogeneous than data on self-learning and

achievement motivation

From the data that has been described in Table 1, several hypotheses are tested related to

influence between self-learning and achievement motivation on students' mathematical

communication ability. For this purpose, the normality test is performed using the Kolmogorov

Smirnov test to all of data. The test of linearity uses a residual plot with a fitted value (predicted

value), 3) the test of multicollinearity is carried out by looking at the correlation value between

independent variables, 4) to test the assumption of autocorrelation by looking at the Durbin-Watson

statistics. After testing all these assumptions, the simultaneous F test and t test will be carried out.

Based on the results of the analysis of the data normality test, it is known that the data is

normally distributed. The linearity test of the data found that the plot formed a random pattern, then

the linearity assumption was met. Based on the output of the analysis with SPSS 22, it can be seen

that the value of Sig (2-tailed) between achievement motivation and self-learning is 0.000 <0.05,

which means that there is a significant correlation between the achievement motivation variable and

the self-learning variable. then we can conclude that there is multicollinearity in the regression model.

Based on the value of du seen from the Durbin-Watson test bounds table, the values of du = 1.6511

and dl = 1.2576 are obtained. So that DW = 1.134 < dl = 1.2576, then the autocorrelation coefficient

is greater than zero, meaning that there is a positive autocorrelation. Based on the output of



heteroscedasticity testing, it is known that the sig value for the self-learning variable is 0.434 and the

sig for the achievement motivation variable is 0.834. Since the significance value (sig) of both

variables is greater than 0.05, there is no heteroscedasticity symptom.

After testing the assumptions, then testing the hypothesis for multiple linear regression analysis

to find out how changes occur in the dependent variable (Mathematical Communication ability), the

value of the dependent variable based on the value of the independent variable (Self-Learning and

Achievement Motivation). The hypothesis in this study is as follows.

H0: There is no significant effect of the independent variables (self-learning, achievement

motivation) with students' mathematical communication ability.

H1: There is at least one independent variable (learning independence, motivation) that has a

significant effect on mathematical communication skills.

With the test criteria, reject Ho if Sig. < 0.05. The test statistic used is multiple linear

regression-test using SPSS 22. The test results are presented in Table 2.

Table 2. Summary of Multiple Linear Regression Test Results

Model Sum of Squares df Mean

Square

F Sig

Regression 3100.933 2 1550.467 8.305 0.001

Residual 5600.962 30 186.699

Total 8701.895 32

a. Dependent Variable: Mathematical Communication Ability b. Predictors: (Constant): Achievement Motivation, Self-Learning

Based on the results presented in Table 2, the results of the test analysis with the level = 0.05;

it can be seen that the sig value (simultaneous test p-value) = 0.01 <0.05, so that at least one

independent variable (self-learning, achievement motivation) has a significant effect on mathematical

communication ability.

The model of the relationship between the independent variables X1 and X2 to the dependent

variable Y is expressed in a regression equation formed from data on learning independence and

achievement motivation and students' mathematical communication skills. The summary of the

regression equations is presented in Table 3.

Table 3. Regression Equations

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

(Constant) -1.605 19.798 -.081 0.936

Self-learning .650 .492 .241 1.323 0.196

Achievement

motivation

.767 .332 .421 2.307 0.028

Dependent Variable: Mathematical Communication Ability


From Table 3 obtained the value of = -1.605; the value of b1 = 0.650 and b2 = 0.767. So that

the multiple linear regression equation becomes Y = -1.605 + 0.65 X1 + 0.767 X2. Regression

coefficients b1 and b2 are positive, meaning that self- learning (X1) and achievement motivation (X2)

have a positive influence on students' mathematical communication ability (Y) which means that the

higher students' self-learning and achievement motivation, the students' mathematical communication

ability (Y) will also be higher.

To determine the magnitude of the correlation or relationship between self-learning and

achievement motivation on students' mathematical communication ability, an analysis of the Model

Summary Table is presented in Table 4.

Table 4. Model Summary

Model R R

Square

Adjusted

R Square

Std. Error of

the Estimate

1 0.597a 0.356 0.313 13.66377

a. Predictors: (Constant) Achievement Motivation, Self-Learning

From the data obtained in Table 4, the correlation coefficient (r) is 0.5927 and the

determination coefficient is 0.356. The correlation coefficient shows a relationship between learning

independence and achievement motivation on positive mathematical communication skills with a

moderate level of relationship (Sugiyono, 2017). While the coefficient of determination of 0.356 can

be interpreted that the influence of learning independence and achievement motivation on

mathematical communication skills is 35.6% while 64.4% is influenced by other factors outside of

self-learning and achievement motivation.

To see partially the effect of each independent variable on the dependent variable, then the

significance of each regression coefficient is tested. The table of the results of the significant

regression coefficient of self-learning data on communication ability is presented in Table 5 and Table

6.

Table 5. Summary Model of Degree of Determination

Model R R

Square

Adjusted R Square Std. Error of the Estimate

1 0.492a 0.242 0.218 5.41154

a.Predictors: (Constant), Mathematical Communication Ability

Based on the results of the analysis above, the R Square value = 0.242 or 24.2%. This value

means that the effect of self-learning (X1) on mathematical communication ability(Y) is 24.2%. The

ANOVA test table is presented in Table 6.



Table 6. ANOVA Test


Square

F Sig.

Regression 290.050 1 290.050 9.904 .004b

Residual 907.829 31 29.285

Total 1197.879 32

a. Dependent Variable: Self-learning

b. Predictors: (Constant), Mathematical

Communication Ability

The table of the results of the significant regression coefficient of achievement motivation data

on communication ability is presented in Table 7 and Table 8

Table 7. Summary Model of Degree of Determination

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .565a .319 .297 7.59059

a.Predictors: (Constant), Mathematical Communication Ability

Based on the results of the analysis above, the R Square value = 0.319 or 31.9%. This value

means that the effect of achievement motivation (X2) on mathematical communication skills (Y) is

31.9%. The ANOVA test table is presented in Table 8.

Table 8. ANOVA Test


Square

F Sig.

Regression 835.869 1 835.869 14.507 .001b

Residual 1786.131 31 57.617

Total 2622.000 32

a. Dependent Variable: Self-learning

b. Predictors: (Constant), Mathematical Communication Ability

Based on the results of data analysis and hypothesis testing it can be seen that: (1) in general

there is a significant influence of self-learning and achievement motivation on students' mathematical

communication ability. 2) Partially there is a significant effect of self-learning and achievement

motivation on students' mathematical communication ability. The results of this study are in

accordance with the results of research by Sumadi and Kusdinar (2019) here is a positive and

significant relationship of mathematical communication and learning motivation to students' problem-

solving skill.

The results of the research conducted shows that self-learning has an influence on the

achievement of students' mathematical communication skills, of course it cannot be separated from

the meaning of self-learning. Self-learning is the process of students monitoring and regulating their

abilities to the internal and external environment using self-awareness and self-reflection (Harding,


English, Nibali, Griffin, Graham, Alom, Zhang, 2019). Zimmerman (2008), Egok (2016), al Fatihah

(2016), and Asmar (2020) state that their activities refer to self-direction and state that their activities

refer to self-direction and self-confidence that allows students to change mental skills into Academic

performance skills are also used to acquire academic skills, such as setting goals, selecting and

implementing strategies, and self-monitoring the effectiveness of an action taken. In this way,

students' mathematical communication ability can be improved.

Students who have high self-learning tend to carry out activities that direct them to the goals to

be achieved. Zimmerman (Moos and Ringdal, 2012) suggests that there are 3 phases of self-learning,

namely: 1) Forethought: developing realistic expectations, setting goals with specific results, and

identifying plans to maximize success, 2) Performance control: processes that include specific

strategies such as self-talk and self-monitoring are used to maximize success. 3) Self-reflection:

students compare the learning outcomes obtained with the learning objectives. The above results are

in line with the results of research by Qohar and sumarmo (2013), Tandililing (2011) stating that there

is a relationship between students' mathematical communication skills and students' independent

learning abilities.

The results of the study also show that achievement motivation also has a significant effect on

students' mathematical communication ability. This result is certainly reasonable because students

with high achievement motivation, will direct their activities to achieve goals. According to

Sulistyarini and Sukardi (2016), motivation is an encouragement from individuals that can be created

through self-awareness or comes from within oneself (intrinsic motivation) and encouragement from

others or the environment (extrinsic motivation). Motivation according to Myers (2010), is a strong

desire to make an effort to achieve a goal. In addition, the results of this study are in accordance with

the results of research (Efendi and Marlina, 2021) which show that learning motivation affects

mathematical communication skills with a percentage of 56.8%.

Students with strong motivation will create and manipulate their environment to achieve

achievement. McClelland (1961) stated that individuals create and manipulate their environment in

various ways when they seek achievement. According to McClelland's theory, a person's motivation

arises from one of three motives, namely achievement, power or affiliation. Furthermore, internal or

external drives influence the manifestation of achievement, power or affiliation (Souders, 2020).. In

terms of learning, Elliot (Pantziara and Philippou, 2013) states that motivation in terms of quality,

focusing on how students think about themselves, their assignments, and their performance. Mueller,

Yankelewitz and Maher (2011), state that extrinsically motivated students engage in learning for

external rewards, such as praise and good grades. They do not require ownership of the mathematics

being studied, but focus on praise and avoiding negative feedback. Students who are intrinsically

motivated, driven by a desire to acquire knowledge and understanding of mathematics. Pintrich and

Groot (1990), stated that motivation is related to students' cognitive engagement and academic



performance in class. Students who are motivated to learn the material are more cognitively involved

in learning the material, have independent learning and never give up.

Waege (2010), Pantziara and Philippou (2014) stated that students' motivation can be seen from

students' focus on learning and understanding mathematical concepts; students' involvement in

mathematical activities; 3) students' attitudes towards mathematics; 4) willingness to take risks and

challenging tasks; 5) students are confident. The results of this study are in accordance with several

previous studies. The results of research by Sumadi and Kusdinar (2019) stated that mathematical

communication and learning motivation had a positive relationship with students' problem solving

skills.

The results of this research regarding the relationship between self-learning and student

learning motivation. As research conducted by Mustofa, Nabila, Suharsono (2019), which concluded

that self-learning and learning motivation are correlated with the contribution of learning motivation

to self-learning, which is 58%. Cheng (2011) states if students want to regulate themselves in the

learning process, they must have self-learning and motivation. The results of study (Efendi and

Marlina, 2021) indicate that there is an influence of learning motivation on mathematical

communication ability with a percentage of 56.8%.

If we look at the magnitude of the influence of self-learning and achievement motivation on

communication ability, we can conclude that there are other influences that have quite a large

influence on communication ability. Some of the allegations that cause it may come from students,

come from teachers, or come from the material being studied or from learning activities that occur.

Alawamleh, Al-Twait and Al-Saht, 2020) stated that one of the obstacles experienced by students

during online learning was the decreased level of communication between students and teachers.

Increased feelings of isolation caused by online classes. Therefore, in web-based learning, it is

necessary to build opportunities for interaction and communication between students and teachers by

making maximum use of discussion forum tools, which may offer opportunities to engage fellow

students and teachers with deeper dialogue. Student factors, such as readiness to learn, initial abilities

possessed, and maybe others. The teacher factor, it could be from the ability of classroom

management, the ability to develop teaching materials and media, and others. Material factors, it

could be the characteristics of the material that are difficult, the complexity of the skills needed to

understand the material. Therefore, it is necessary to study further what other factors affect students'

mathematical communication ability.

CONCLUSION

From the results of data analysis and discussion above, it can be concluded that: 1) There is a

positive influence between self-learning and achievement motivation on students' mathematical

communication ability; 2) The correlation between self-learning and students' mathematical


communication ability is categorized as a moderate level of relationship; 3) The correlation between

achievement motivation and students' mathematical communication ability is categorized as a

moderate level of relationship; 4) There are other factors outside of self-learning and achievement

motivation that affect students' mathematical communication which has a large enough influence.

Therefore, it is necessary to conduct further studies on these factors.

ACKNOWLEDGMENTS

This research can be carried out well thanks to the help of various parties. For this reason, the

authors would like to thank the University of Lampung which has provided financial support. The

authors also thank the principal and partner teachers of SMA Negeri 1 Sumberjaya who have provided

good cooperation in this research.

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