Examining Mathematics Achievement of Students from Different Provinces: What PISA 2018 says about Indonesia?
Abstract
Despite participating in PISA for more than 10 years, Indonesian students' mathematics achievements still tend to be low. On the other hand, PISA 2018 shows that students in two provinces, namely (1) Special Region of Yogyakarta, and (2) Special Region of Capital City Jakarta, exhibit higher mathematics achievement than students from other provinces. This research aim is to examine factors affecting students' mathematics performance in these three regions. We carried out statistical multilevel analysis with a random effects model using R software. Based on this analysis, we find differences in factors that influence students' mathematics achievement from three provinces. Variables that significantly influence students’ mathematics achievement in the three regions are parent support, home support, students' mastery goals, and students' competition. The only variables that were significant outside Special Region of Yogyakarta and Special Region of Capital City Jakarta were students' beliefs and students' ESCS. In the three provinces, the variables growth mindset, gender, and father's education level did not affect students' mathematics achievement.
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Aditomo, A. & Felicia, N. (2018). Ketimpangan mutu dan akses pendidikan di Indonesia: Potret berdasarkan Survei PISA 2015. Kilas Pendidikan, 17, 1-8.
Agasisti, T. (2011). Does competition affect Schools' performance? Evidence from Italy through OECD‐PISA data. European Journal of Education, 46(4), 549-565. https://doi.org/10.1111/j.1465-3435.2011.01500.x
Anaya, L. M., & Zamarro, G. (2023). The role of student effort on performance in PISA: Revisiting the gender gap in achievement. Oxford Economic Papers, gpad018. https://doi.org/10.1093/oep/gpad018
Anggraheni, F. Y., Kismiantini, K., & Ediyanto, F. (2022). Multilevel model analysis to investigate predictor variables in mathematics achievement PISA data. Southeast Asian Mathematics Education Journal, 12(2), 95-104. https://doi.org/10.46517/seamej. v13i1.183
Aparicio, J., Cordero, J. M., & Ortiz, L. (2021). Efficiency analysis with educational data: How to deal with plausible values from international large-scale assessments. Mathematics, 9(13), 1579. https://doi.org/10.3390/math9131579
Avvisati, F. (2020). The measure of socio-economic status in PISA: A review and some suggested improvements. Large-Scale Assessments in Education, 8(1), 8.
Bailey, P., Emad, A., Huo, H., Lee, M., Liao, Y., Lishinski, A., ... & Bailey, M. P. (2023). Package ‘EdSurvey’ version 4.0.1 1-158.
Bates D, Mächler M, Bolker B, Walker S (2015). Fitting linear mixed-effects models using lme4.” Journal of Statistical Software, 67(1), 1–48. doi:10.18637/jss.v067.i01.
Cheng, Q., & Hsu, H. Y. (2016). Low SES and high mathematics achievement: A two-level analysis of the paradox in six Asian education systems. Journal of Education and Human Development, 5(1), 77-85. http://dx.doi.org/10.15640/jehd.v5n1a8
Dwianjani, N. K. V., & Candiasa, I. M. (2018). Identifikasi faktor-faktor yang mempengaruhi kemampuan pemecahan masalah matematika. Numerical: Jurnal Matematika Dan Pendidikan Matematika, 2(2), 87–100. https://doi.org/10.25217/ numerical.v2i2.276
Echazarra, A. (2020). Do students learn in co-operative or competitive environments? PISA in focus. No. 107. OECD Publishing.
Efendi, R., & Kismiantini, K. (2022). Analysis of PISA 2018 results in Indonesia: Perspective of socioeconomic status and school resources. AIP Conference Proceedings, 2575 (040020), (pp. 1-7). https://doi.org/10.1063/5.0108065
Fauziah, N., Roza, Y., & Maimunah, M. (2022). Kemampuan matematis pemecahan masalah siswa dalam penyelesaian soal tipe numerasi AKM. Jurnal Cendekia: Jurnal Pendidikan Matematika, 6(3), 3241-3250. https://doi.org/10.31004/cendekia. v6i3.1471
Fung, D., Hung, V., & Lui, W. M. (2018). Enhancing science learning through the introduction of effective group work in Hong Kong secondary classrooms. International Journal of Science and Mathematics Education, 16, 1291-1314. https://doi.org/10.1007/s10763-017-9839-x
Govorova, E., Benítez, I., & Muñiz, J. (2020). Predicting student well-being: Network analysis based on PISA 2018. International Journal of Environmental Research and Public Health, 17(11), 4014. http://doi.org/10.3390/ijerph17114014
Huang, F. L. (2024). Using plausible values when fitting multilevel models with large-scale assessment data using R. Large-scale Assessments in Education, 12(1), 7.
Ismawati, E., Amertawengrum, I. P., & Anindita, K. A. (2023). Portrait of Education in Indonesia: Learning from PISA Results 2015 to Present. International Journal of Learning, Teaching and Educational Research, 22(1), 321-340. https://doi.org/10.26803/ ijlter.22.1.18
Jackson, C. (2022). Package ‘msm’: Multi-state markov and hidden markov models in continuous time. 3 1-115.
Karaman, P. (2022). Examining non-cognitive factors predicting reading achievement in Turkey: Evidence from PISA 2018. International Journal of Contemporary Educational Research, 9(3), 450-459. https://doi.org/10.33200/ijcer.927884
Kartianom, K., & Ndayizeye, O. (2017). What‘s wrong with the Asian and African Students’ mathematics learning achievement? The multilevel PISA 2015 data analysis for Indonesia, Japan, and Algeria. Jurnal Riset Pendidikan Matematika, 4(2), 200-210. http://dx.doi.org/10.21831/jrpm.v4i2.16931
Khine, M. S., Fraser, B. J., Afari, E., & Liu, Y. (2023). Language learning environments and reading achievement among students in China: evidence from PISA 2018 data. Learning Environments Research, 26(1), 31-50. https://doi.org/10.1007/s10984-021-09404-8
Khoirunnisa, P. H., & Malasari, P. N. (2021). Analisis kemampuan berpikir kritis matematis siswa ditinjau dari self confidence. JP3M (Jurnal Penelitian Pendidikan dan Pengajaran Matematika), 7(1), 49-56. https://doi.org/10.37058/jp3m.v7i1.2804
Kismiantini., Setiawan, E. P., Pierewan, A. C., & Montesinos-López, O. A. (2021). Growth mindset, school context, and mathematics achievement in Indonesia: A multilevel model. Journal on Mathematics Education, 12(2), 279-294. https://doi.org/10.22342/ jme.12.2.13690.279-294
Lazarević, L. B., & Orlić, A. (2018). PISA 2012 mathematics literacy in Serbia: A multilevel analysis of students and schools. psihologija, 51(4), 413-432. https://doi.org/10.2298/PSI170817017L
Luschei, T.F. (2017). 20 Years of TIMSS: Lessons for Indonesia. IRJE Indonesian Research J. in Education, 1(1), 6-17. https://doi.org/10.22437/irje.v1i1.4333
Mahdiansyah, M., & Rahmawati, R. (2014). Literasi matematika siswa pendidikan menengah: Analisis menggunakan desain tes internasional dengan konteks Indonesia. Jurnal Pendidikan dan Kebudayaan, 20(4), 452-469. https://dx.doi.org/10.24832/jpnk.v20i4. 158
Marôco, J. (2021). Portugal: The PISA effects on education. Improving a Country’s Education: PISA 2018 Results in 10 Countries, 159-174.
Maulidya, N. S., & Nugraheni, E. A. (2021). Analisis hasil belajar matematika peserta didik ditinjau dari self-confidence. Jurnal Cendekia: Jurnal Pendidikan Matematika, 5(3), 2584-2593.
Muthén, B. O. (1991). Multilevel factor analysis of class and student achievement components. Journal of Educational measurement, 28(4), 338-354. https://doi.org/ 10.1111/j.1745-3984.1991.tb00363.x
Muthén, B. O. (1994). Multilevel covariance structure analysis. Sociological methods & research, 22(3), 376-398. https://doi.org/10.1177/0049124194022003006
OECD. (2019). Indonesia – Country Note – PISA 2018 Result. Retrieved from https://www. oecd.org/pisa/publications/PISA2018_CN_IDN.pdf
Pakpahan, R. (2017). Faktor-faktor yang memengaruhi capaian literasi matematika siswa Indonesia dalam PISA 2012. Jurnal Pendidikan Dan Kebudayaan, 1(3), 331-348. https://doi.org/10.24832/jpnk.v1i3.496
Patriana, W. D., Sutama, S., & Wulandari, M. D. (2021). Pembudayaan literasi numerasi untuk asesmen kompetensi minimum dalam kegiatan kurikuler pada sekolah dasar muhammadiyah. Jurnal Basicedu, 5(5), 3413-3430. https://doi.org/10.31004/ basicedu.v5i5.1302
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., Eispack., Heisterkamp, S., van Willigen, B., and Maintainer, R. (2020). Package ‘nlme’: Linear and nonlinear mixed effects models version 3 1-148.
Pratiwi, I. (2019). Efek program PISA terhadap kurikulum di Indonesia. Jurnal pendidikan dan Kebudayaan, 4(1), 51-71. https://doi.org/10.24832/jpnk.v4i1.1157
Pustejovsky, J. Chen, M. (2023). Package ‘lmeInfo’: Information matrices for ‘lmeStruct’ and ‘glsStruct’ 3 1-10.
Ridwan, R., & Kismiantini, K. (2023, March). The effects of students' cooperative attitudes, competitive attitudes, and teachers' teaching styles on students' mathematics achievement: Indonesian case from PISA 2018. AIP Conference Proceedings, 2556(050015), (pp. 1-9). https://doi.org/10.1063/5.0110263
Rohmat, A. N., & Lestari, W. (2019). Pengaruh konsep diri dan percaya diri terhadap kemampuan kemampuan berpikir kritis matematis. JKPM (Jurnal Kajian Pendidikan Matematika), 5(1), 73-84. http://dx.doi.org/10.30998/jkpm.v5i1.5173
Rosnawati, R. (2013). Kemampuan penalaran matematika siswa SMP Indonesia pada TIMSS 2011. Prosiding Seminar Nasional Penelitian, Pendidikan dan Penerapan MIPA, Fakultas MIPA, Universitas Negeri Yogyakarta, 18, (pp. 1-6).
Sari, R. H. N., & Wijaya, A. (2017). Mathematical literacy of senior high school students in Yogyakarta. Jurnal Riset Pendidikan Matematika, 4(1), 100-107. http://dx.doi.org/10.21831/jrpm.v4i1.10649
Stacey, K. (2011). The PISA view of mathematical literacy in Indonesia. Journal on mathematics education, 2(2), 95-126. https://doi.org/10.22342/jme.2.2.746.95-126
Sumaryanta, S., Priatna, N., & Sugiman, S. (2019). Pemetaan hasil ujian nasional matematika. Idealmathedu: Indonesian Digital Journal of Mathematics and Education, 6(1), 543-557. https://doi.org/10.53717/idealmathedu.v6i1.38
Sun, L., Bradley, K. D., & Akers, K. (2012). A multilevel modelling approach to investigating factors impacting science achievement for secondary school students: PISA Hong Kong sample. International Journal of Science Education, 34(14), 2107-2125. https://doi.org/10.1080/09500693.2012.708063
Suprapto, N. (2016). What should educational reform in Indonesia look like?-Learning from the PISA science scores of East-Asian countries and Singapore. In Asia-Pacific Forum on Science Learning & Teaching, 17(2), 1-21.
Suprayitno, T. (ed). (2019). Pendidikan di Indonesia: Belajar dari hasil PISA 2018. Jakarta: Ministry of Education, Culture, Research, and Technology.
Suputra, W. A. (2021). Klasterisasi hasil ujian nasional SMA/MA dengan algoritma k-means. Wahana Matematika dan Sains: Jurnal Matematika, Sains, dan Pembelajarannya, 15(1), 22-30. https://doi.org/10.23887/wms.v15i1.25380
Thien, L. M., Darmawan, I. G. N., & Ong, M. Y. (2015). Affective characteristics and mathematics performance in Indonesia, Malaysia, and Thailand: what can PISA 2012 data tell us?. Large-scale Assessments in Education, 3, 1-16. https://doi.org/10.1186/ s40536-015-0013-z
Tambunan, S. M. (2006). Hubungan antara kemampuan spasial dengan prestasi belajar matematika. Makara Human Behavior Studies in Asia, 10(1), 27-32. https://doi.org/ 10.7454/mssh.v10i1.13
Ulkhaq, M. M. (2022). The determinants of Indonesian students’ mathematics performance: An analysis through PISA data 2018 wave. Proceedings of the First Jakarta International Conference on Multidisciplinary Studies Towards Creative Industries, JICOMS 2022, 16 November 2022, Jakarta, Indonesia: JICOMS 2022 (p. 200). European Alliance for Innovation. https://doi.org/10.2991/978-2-38476-044-2_13
Widjaja, W. (2011). Towards mathematical literacy in the 21st century: perspectives from Indonesia. Southeast Asian mathematics education journal, 1(1), 75-84. https://doi.org/10.46517/seamej.v1i1.12
Winardi, W., Karyono, Y., Mutijo., Sasono, D.H. (2023). Indeks pembangunan manusia 2022. Jakarta: Badan Pusat Statistik.
You, H. S., Park, S., & Delgado, C. (2021). A closer look at US schools: What characteristics are associated with scientific literacy? A multivariate multilevel analysis using PISA 2015. Science Education, 105(2), 406-437. https://doi.org/10.1002/sce.21609
Zamarro, G., Hitt, C., & Mendez, I. (2019). When students don’t care: Reexamining international differences in achievement and student effort. Journal of Human Capital, 13(4), 519-552.
Zhan, Y., Wan, Z.H., Chen, J. (2023). How is student resilience affected by teacher feedback, teacher support, and achievement goals? A mediation model based on PISA 2018 survey data. The Asia-Pacific Education Research, 1-12. https://doi.org/10.1007/s40299-023-00764-8
DOI: https://doi.org/10.46517/seamej.v14i1.331
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