Microsoft Word - [Edit] Ainun Rahma Firdausy 20190626.docx Indonesian Journal on Learning and Advanced Education (IJOLAE) | p-ISSN 2655-920x, e-ISSN 2656-2804 Vol. (1) (2) (2019) 29-37 29 The Contribution of Student Activity and Learning Facilities to Learning Independency and its Impact on Mathematics Learning Outcomes in Junior High School The Contribution of Student Activity and Learning Facilities to Learning Independency and its Impact on Mathematics Learning Outcomes in Junior High School Ainun Rahma Firdausy1, Nining Setyaningsih2, La Suha Ishabu3, Mohamad Waluyo4 1,2Education Faculty, Muhammadiyah University of Surakarta, Indonesia 3Education Faculty, University of Pattimura, Indonesia 4School of Educational Sciences, University of Szeged, Hungary DOI: 10.23917/ijolae.v1i2.8104 Received: January 1st, 2019. Revised: January 14th, 2019. Accepted: June 19th, 2019 Available Online: June 26th, 2019. Published Regularly: July 1st, 2019 Abstract This study aims to: (1) examine the contribution of student activity and learning facilities to mathematical learning outcomes indirectly through learning independence, (2) examine the contribution of student activity and learning facilities to learning independence, (3) test the contribution of student learning independence to results learn math. This type of research is quantitative with the research subjects being all VII grade stu- dents of the Muhammadiyah Middle School Surakarta Special Program in 2018/2019. Data collection is done by questionnaire and documentation. The data analysis technique used is path analysis which has pre- viously been carried out in five tests of data analysis prerequisites, namely: normality test with liliefors, linearity test, multicollinearity test, heteroscedasticity test and autocorrelation test. The results of the study with a significance level of 0.05, namely: (1) there is a contribution of student activity and learning facilities to learning outcomes indirectly through learning independence by 23.9%, (2) there is a contribution of stu- dent activity and learning facilities to learning independence by 64%, (3) there is a contribution of learning independence to mathematics learning outcomes of 15.68%. Keywords: learning facilities, student activity, learning independent Corresponding Author: Ainun Rahma Firdausy, Education Faculty, Universitas Muhammadiyah Surakarta, Indonesia Email: inunrahma29@gmail.com 1. Introduction Mathematics according to Hosnan (2014: 177) is a subject that requires a high level of understanding and has a relationship with real life. Based on a survey conducted by the Organization for Economic Co- operation and Development (OECD) in 2015 using the Program for International Student Assessment (PISA) test, Indonesia was ranked low in education equity. For mathe- matics in 2015, Indonesia reached 359 (me- dian) with an average of 403. This value still places Indonesia below the average of OECD countries which is 490. In the continuation of the implementation of education there are various factors that influence, where the fac- tor if used will bring education towards a better than before. Success in the learning process can af- fect the future produced by Lile, R., & Bran, C. (2014). This makes students aware of ac- ademic support and encourages them to get good grades. However, as reported above, the results of mathematics learning in Indo- nesia are still the lowest rank in the world. This situation is really ironic when mathe- Indonesian Journal on Learning and Advanced Education http://journals.ums.ac.id/index.php/ijolae Indonesian Journal on Learning and Advanced Education (IJOLAE) | p-ISSN 2655-920x, e-ISSN 2656-2804 Vol. (1) (2) (2019) 29-37 30 The Contribution of Student Activity and Learning Facilities to Learning Independency and its Im- pact on Mathematics Learning Outcomes in Junior High School matics is the parent of science but in fact until now it has not been able to become a favorite subject for students. Mathematical subjects are often considered a frightening lesson for most students both at the elementary and upper secondary level. Of course, this is inseparable from the factors that influence it. Factors allegedly can come from the side of students, teachers or the environment. Factors originating from stu- dents can include the level of intelligence, activeness, independence and motivation when learning mathematics. While the fac- tors that come from the teacher are the strat- egies or learning methods used and the read- iness of the teacher to master the mathemat- ics learning material. In terms of school, it can be a facility, judging from the availabil- ity, completeness and maintenance of availa- ble mathematical facilities. According to Paramita, S., & Indarwati, T. A. (2015) the activeness of student learn- ing is the ability of students to be active on a regular basis which involves body, mind and all aspect that associated with the learning process. Selim Gunuc's research (2014) in "The Relationship between Student In- volvement and Their Academic Achieve- ment" shows a significant academic relation- ship between student involvement and their academic achievement. Blasco-Arcas, et. al. (2013) study shows the significant of students activity with term of interactivity with peers and teachers on learning performance. They hypothized that students’ interactivity will stimulate students to participate in the classroom, develope their engagement in learning and improve the learning performance. In other word, when students are active in a learning, it means that they engage to the learning process and will promote their understanding, performance and achievement (Reyes, et. al., 2012; Wang & Holcombe, 2010). Aforementioned factor can only occure in the learning circumtances and controlled by instructor. While the main factor influences the success of learning is student independency or students’ self-regulation. Independency or self-regulation in learning is very important even from early chilhood (McClelland & Cameron, 2012). Evidences of key components of self-regulation predict academic achievement are shown by several studies namely Valiente, et. al. (2008), Liew, et. al. (2008), and Blair & Razza (2007). Specifically, according to Nagpal (2013) in "Independent Learning and Student Devel- opment" implied that independent learning provides significant results on learning out- comes. Study of external effect influences students’ performance by Akomolafe & Adesua (2016) in "The Impact of Physical Facilities on the Level of Motivation and Academic Performance of Students in High Schools in South West Nigeria" said that there was an influence of facilities in learn- ing on student learning outcomes. Other re- search with similar interest, Otieno (2010) and Olimi et. al. (2012) reveals that the high physical facilities, human facilities and other facilities can also influence student motiva- tion towards learning. Also supported in re- search (Rejeki, Setyaningsih, & Toyib, 2017) which say that the use of LEGO in learning activities supports the understanding of frac- tions for students both high-ability students and students with low abilities in mathemat- ics. The other research involving the computer based facilities like computer assisted instruction or e-learning resulting the similar evidence (Yusuf & Afolabi, 2010; Giesbers, 2013). By those introduction, the authors’ pur- pose of this study is, (1) to examine the con- tribution of student activity and learning fa- cilities to mathematics learning outcomes Indonesian Journal on Learning and Advanced Education (IJOLAE) | p-ISSN 2655-920x, e-ISSN 2656-2804 Vol. (1) (2) (2019) 29-37 31 The Contribution of Student Activity and Learning Facilities to Learning Independency and its Impact on Mathematics Learning Outcomes in Junior High School indirectly through learning independence, (2) examine the contribution of student activity and learning facilities to learning independ- ence, (3) test the contribution of student learning independence to mathematics learn- ing outcomes. 2. Method This type of research is based on the approach of quantitative research. Quantitative research aims to find relationships and explain the causes of change in measurable social facts (testing theories) (Sutama, 2015: 32). This research was conducted at the Surakarta Muhammadiyah Middle School Special Program, located on Pleret Raya Barat Street, number 9, Banyuanyar, Banjarsari, Surakarta, Central Java, 57137. The subjects of this study were all VII grade students in the odd semester of 2018/2019. Data analysis techniques in this study using path analysis. Prerequisite tests include normality test with liliefors, linearity test, multicollinearity test, heteroscedasticity test and autocorrelation test. Riduwan and Kuncoro (2013: 115) state that path analysis techniques are used to test the magnitude of the contribution shown by the path coefficients on each path diagram of the causal relationship between exogenous variables X1 and X2 towards endogenous variables Y and Z. Data collection techniques used are: (1) questionnaire method used to retrieve student activity data, learning facilities and learning independence, (2) documentation is used to retrieve student learning outcomes data. The learning outcomes used are the scores of the Intermittent Middle Semester Examination of mathematics in seventh grade students of the Muhammadiyah Junior School Surakarta Special Program in 2018/2019. Procedure and data analysis techniques should be emphasized to literature review article. The research stages should be clearly stated. 3. Result and Discussion Mathematics learning outcomes are obtained using the method of the VII grade Midterm Semester Exam Assessment documentation in 2018/2019. There are four variables, namely student activity (X1) and learning facilities (X2) as independent variables, learning independence (X3) as intervening variables and mathematics learning outcomes (Y) as dependent variables. Data from student activity, learning facilities and learning independence were obtained from filling out questionnaires. Before the questions are given to the research sample, validity and reliability tests have been carried out. Before the hypothesis testing is carried out, the analysis prerequisite test is carried out which includes the normality test, linearity test, multicollinearity test, heteroscedasticity test and autocorrelation test. Based on the results of the analysis prerequisite test, it was found that the five prerequisite tests for this study could be fulfilled. From the normality test, it is obtained that the value of all variables (Lmax) is less than Ltabel. Even if the maximum is less than Ltabel then the data is declared to be normally distributed. So the conclusion is that all variables in this study are normally distributed. From the linearity test it is filled with the properties where the value of Fcount of each independent variable with the dependent variable is smaller than Ftable. This shows that between variables has a linear relationship. While from heteroscedasticity test, it was obtained that all p-Value values of each independent variable on the dependent variable were greater than 0.05. So it can be Indonesian Journal on Learning and Advanced Education (IJOLAE) | p-ISSN 2655-920x, e-ISSN 2656-2804 Vol. (1) (2) (2019) 29-37 32 The Contribution of Student Activity and Learning Facilities to Learning Independency and its Im- pact on Mathematics Learning Outcomes in Junior High School concluded that each variable in this study did not occur heteroscedasticity. Multicollinearity test aims to determine the existence of correlations between independent variables. The expected regression model is that there is no multicollinearity. From the data of student activeness (X1) on learning facilities (X2), it was found that the tolerance value > 0.1 and VIF value > 10, so that it was concluded that there were no multicollinearity between independent variables. In the uji autocorrelation the values for each variable are at du Ftable then this indicates that H0 is rejected. So the conclusion is that the ac- tiveness of students and learning facilities contribute simultaneously to the results of learning mathematics through learning inde- pendence. The contribution of student ac- tiveness, learning facilities and independence of learning simultaneously influence the mathematics learning outcomes of Rsquare = 0.239 = 23.9% and the remaining 76.1% can be influenced by other factors beyond this study which cannot be explained. Because H0 is rejected, it can be continued with a par- tial test using the t test. Based on the t test with α = 5%, it is ob- tained tcount = 2.043 and = 2.012 where tcount > means H0 is rejected. So that it can be concluded that student ac- tivity contributes significantly to mathemat- ics learning outcomes. There is a direct effect of student activity on mathematics learning outcomes of 0.469. This shows the magni- tude of the contribution of student activity directly affecting mathematics learning out- comes by 21,996%. Basically, active math- ematics learning is not passive so that with the activeness of students, it makes students the subject of learning. Where if students become subjects, students will get the full opportunity to be involved in learning so that it will improve the learning outcomes of mathematics. This shows that the activeness of students has a contribution to the learning outcomes of mathematics. This result is sup- ported by research by Lamanauskas & Au- giene (2017) in "The Aspects of Understand- ing, Situation and Improvement" which shows that student activity has an effect of 51.4% in doing assignments. In another study it was found that active learning can increase student motivation and when moti- vation increases it will also influence math- ematics achievement to be better too (M., A.A.A. & Yang, C., 2018) In the learning facilities variable, it was found that learning facilities did not have a contribution to the learning outcomes of mathematics. This is indicated by the results of tcount = 0.048 and = 2012. The re- sults of this study are not in line with Kwakye's research (2013) in the "Availabil- Indonesian Journal on Learning and Advanced Education (IJOLAE) | p-ISSN 2655-920x, e-ISSN 2656-2804 Vol. (1) (2) (2019) 29-37 34 The Contribution of Student Activity and Learning Facilities to Learning Independency and its Im- pact on Mathematics Learning Outcomes in Junior High School ity of Supportive Facilities for Effective Teaching" which says that learning facilities contribute significantly to mathematics learn- ing outcomes. This is possible due to differ- ences in sampling, where in this study the sample used was junior high school students while in Kwakye's study used a sample of high school. In addition, the equation = is also ob- tained. With interpretation, each increase in one student activity variable ( ) will in- crease learning independence ( ) by 0.843. But for every increase in one learning facility variable ( there will be a decrease in learning independence ( ) of 0.104. From the results of the study also con- cluded that the activeness of students and learning facilities have contributed simulta- neously to learning independence. This is evidenced by the value of Fcount = 42,667 greater than = 3.23. The contribu- tion of student activity and learning facilities simultaneously affecting learning independ- ence is equal to Rsquare = 0.640 = 64%. The remaining 36% can be influenced by other factors outside of this study. Because H0 is rejected, it can be continued with a partial test using the t test. On the variable of student activity to- wards learning independence with α = 5%, obtained tcount = 8.636 and = 2.012 where it means tcount > ttable which means H0 is rejected. So the activity of students has a significant contribution to learning inde- pendence. Students' active contribution di- rectly affects learning independence by 71.06%. With this value shows that the activ- ity of students during mathematics learning greatly affects the independence of student learning. When learning, the more often the teacher gives a stimulus to students, the more active the students will emerge. When stu- dents are increasingly active, independence in learning will also be higher. This is sup- ported by Beaudoin's study (2003) found that it was not easy to correlate student participa- tion with student learning outcomes. Even so, it was found that students who were very participatory in online classes could achieve higher results in learning. It also revealed that online participation does not always damage student learning outcomes. For the learning facilities variable to- wards learning independence, it was found that tcount = -1.065 and = -2.012. Because tcount = -1.065 > = -2.012 then H0 is accepted. So it can be concluded that learning facilities do not have a signifi- cant contribution to learning independence. The results of this study are not in line with the research of C. Nerantzi & C. Despard (2014) who say that the use of LEGO makes participating students feel more relaxed in preparation for discussion and focus on the assessment task ahead. In addition, LEGO can also make students more independent when activities are taking place. The differ- ence it is possible because of differences in the determination of learning facilities that help during learning, in this study less spe- cific for the determination of teaching aids used in learning while for research from C. Nerantzi & C. Despard (2014) has deter- mined LEGO as learning facilities in learn- ing. Individual testing of the learning inde- pendence variable (X3) on mathematics learning outcomes (Y) using the t test with a significance level of α = 5%, obtained tcount = 3.018 and = 2.021. Because tcount > ttable then it shows H0 is rejected. So there is a significant contribution to learning inde- pendence towards the learning outcomes of mathematics. The contribution of learning independence to mathematics learning out- Indonesian Journal on Learning and Advanced Education (IJOLAE) | p-ISSN 2655-920x, e-ISSN 2656-2804 Vol. (1) (2) (2019) 29-37 35 The Contribution of Student Activity and Learning Facilities to Learning Independency and its Impact on Mathematics Learning Outcomes in Junior High School comes is equal to ( )2 = (0.396)2 = 15.68%. Where when students have an inde- pendence attitude in themselves, they carry out learning activities that are not dependent on their friends so that when a math test is held, students consciously learn to take full responsibility for their learning outcomes. This proves that the higher the independence of students, the higher the learning out- comes. The results of this study are support- ed by Nagpal (2013) in "Independent Learn- ing and Student Development" which shows that independent learning provides signifi- cant results on learning outcomes. 4. Conclusion There is a contribution of student activity and learning facilities simultaneously to the learning outcomes of mathematics through learning independence with the value of Fcount = 4.920 with α = 5%. The contribution is 23.9%, the remaining 76.1% can be influenced by other factors outside of this study. The contribution of student activity directly affects the mathematics learning outcomes of 21.996%. When students have an independence at- titude in themselves, they carry out learning activities that are not dependent on their friends so that when a math test is held, stu- dents consciously learn to take full responsi- bility for their learning outcomes. This proves that the higher the independence of students, the higher the learning outcomes. The results of this study are supported by Nagpal (2013) in "Independent Learning and Student Development" which shows that independent learning provides significant results on learning outcomes. There is a contribution of student activeness and learning facilities simultaneously affecting learning independence with Fcount = 42,667 with α = 5%. The contribution is 64%, the remaining 36% can be influenced by other factors beyond the inexplicable research. Students' active contribution directly affects learning independence by 71.06%. There is a contribution of learning independence to the learning outcomes of mathematics with α = 5% obtained by the value of tcount = 3.018. The contribution of learning independence to mathematics learning outcomes is 15.68%. 5. References Akomolafe, C. O. dan Adesua, V. O. (2016). The Impact of Physical Facilities on Students’ Level of Motivation and Aca- demic Performance in Senior Secondary Schools in South West Nigeria. Journal of Education and Practice. 7: 38-42. Alimi, O. S., Ehinola, G. B., & Alabi, F. O. (2012). School Types, Facilities and Ac- ademic Performance of Students in Sen- ior Secondary Schools in Ondo State, Nigeria. 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