THE DETERMINANTS OF INDONESIAN STUDENTS’ MATHEMATICS PERFORMANCE: AN ANALYSIS THROUGH PISA DATA 2015 WAVE

Authors

  • M. Mujiya Ulkhaq Diponegoro University

DOI:

https://doi.org/10.33578/mbi.v17i8.331

Keywords:

Indonesia, Students, Mathematics, Multivariate Regression, PISA.

Abstract

This study investigates the determinants of Indonesian students’ performance of mathematics proxied by plausible value (PV) of mathematics provided by OECD PISA. The PISA 2015 data is used to answer this research question. A multivariate linear regression is used; as the dependent variable is PV of mathematics, while the information concerning student’s background is used as independent variables, i.e., student’s personal characteristics: age and gender; family background: index of economic, social, and cultural status as well as ICT possession at home; and classroom’s climate: perceived feedback from teacher. Result shows that all determinants but student’s gender are significant at the level of 5%. Several tests to examine the classical assumptions, such as normality of the residuals, test for heteroscedasticity and collinearity are performed. According to these tests, no severe problems occur.

Author Biography

M. Mujiya Ulkhaq, Diponegoro University

Department of Industrial Engineering

References

Acosta, S. T., & Hsu, H. Y. (2014). Negotiating diversity: An empirical investigation into family, school and student factors influencing New Zealand adolescents’ science literacy. Educational Studies, 40(1), 98-115.

Barnard-Brak, L., Lan, W. Y., & Yang, Z. (2018). Differences in mathematics achievement according to opportunity to learn: A 4pL item response theory examination. Studies in Educational Evaluation, 56, 1-7.

Gamazo, A., & Martínez-Abad, F. (2020). An exploration of factors linked to academic performance in PISA 2018 through data mining techniques. Frontiers in Psychology, 11, 575167.

Gamazo, A., Olmos-Migueláñez, S., & Martínez-Abad, F. (2016). Multilevel models for the assessment of school effectiveness using PISA scores. In Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality, pp. 1161-1166.

Martínez-Abad, F. (2019). Identification of factors associated with school effectiveness with data mining techniques: testing a new approach. Frontiers in Psychology, 10, 2583.

Perelman, S., & Santín, D. (2011). Measuring educational efficiency at student level with parametric stochastic distance functions: an application to Spanish PISA results. Education Economics, 19(1), 29-49.

Salas‐Velasco, M. (2020). Assessing the performance of Spanish secondary education institutions: distinguishing between transient and persistent inefficiency, separated from heterogeneity. The Manchester School, 88(4), 531-555.

She, H.‐C., Lin, H. S., & Huang, L. Y. (2019). Reflections on and implications of the Programme for International Student Assessment 2015 (PISA 2015) performance of students in Taiwan: The role of epistemic beliefs about science in scientific literacy. Journal of Research in Science Teaching, 56(10), 1309-1340.

Smith, P., Cheema, J. Kumi-Yeboah, A. Warrican, S. J., & Alleyne, M. L. (2018). Language-based differences in the literacy performance of bidialectal youth. Teachers College Record, 120(1), 1-36.

Ulkhaq, M. M. (2021). Efficiency analysis of Indonesian schools: A stochastic frontier analysis using OECD PISA 2018 data. In 2nd International Conference on Industrial Engineering and Operations Management Asia Pacific Conference, Surakarta, Indonesia.

Ulkhaq, M. M. (2022). The determinants of Indonesian students’ science performance: An analysis through PISA data 2015 wave. In Bioteknologi dan Penerapannya dalam Penelitian dan Pembelajaran Sains, Moh. Nasrudin (Ed.), Pekalongan: PT. Nasya Expanding Management, 529-539.

Willms, J. D. (2010). School composition and contextual effects on student outcomes. Teachers College Record 112(4), 1008-1037.

Wiseman, Alexander W. (2013). Policy responses to PISA in comparative perspective. PISA, power, and policy: The emergence of global educational governance, 303, 322.

Zhu, Y., & Kaiser, G. (2020). Do east asian migrant students perform equally well in mathematics?. International Journal of Science and Mathematics Education, 18(6), 1127-1147.

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Published

2023-03-12

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Section

Articles