Strategies for Enhancing Students' Mathematical Reasoning and Disposition Ability in a Freedom Curriculum
DOI:
https://doi.org/10.25217/ji.v10i1.5267Keywords:
Mathematical Reasoning, Disposition, Freedom CurriculumAbstract
It is crucial to have suitable learning models in the Freedom curriculum, allowing students sufficient time to delve into concepts and improve skills, particularly in mathematical reasoning and disposition. CORE learning (Connecting, Organizing, Reflecting, and Extending) is a different approach to enhancing upper school students' mathematical reasoning and disposition abilities. This quantitative study employs descriptive and two-way multivariate analysis to examine the impact of learning models and gender on students' mathematical reasoning and disposition abilities. The study focuses on grade IX students at a public senior high school in Surakarta, Indonesia. The control group is class Phase E-8, which follows a direct learning approach and is known as the Non-CORE class. In the meantime, the Phase E-10 class is an experimental class implementing the CORE learning model. The study findings show variances in mathematical thinking and attitude among high school students in CORE versus non-CORE classes. Additionally, there is no reliance on enforcing CORE learning on male and female students, suggesting that CORE learning can be suggested for enhancing mathematical reasoning skills and disposition ability of all students irrespective of gender. CORE learning has been proven to be an effective strategy for improving students' mathematical reasoning and disposition through education oriented towards a constructivist approach centered on students, where students actively construct their knowledge through a series of processes that connect, organize, reflect, and extend concepts. This study contributes to the discourse on constructivist pedagogy by providing strong evidence that the CORE learning model improves mathematical reasoning and attitudes among upper secondary students. Those taught with CORE outperform peers in traditional settings in both cognitive and attitudinal measures. The lack of gender-based differences indicates CORE supports equitable learning. Aligned with Indonesia’s Freedom Curriculum, the model promotes active, student-centered learning and shows promise as a scalable, inclusive approach to improving math proficiency and engagement.
References
Areepattamannil, S., & Freeman, J. G. (2008). Gender and attitudes toward science: A comparison of Canadian and Indian students. International Journal of Science Education, 30(9), 1147–1164. https://doi.org/10.1080/09500690701345554
Ari, A. A. I. P., & Abadi, I. B. G. S. (2020). Improving science learning outcomes through CORE learning model based on sets. Jurnal Ilmiah Sekolah Dasar, 4, 655–666.
Ashcraft, M. H., & Moore, A. M. (2009). Mathematics anxiety and the affective drop in performance. Journal of Psychoeducational Assessment, 27(3), 197–205. https://doi.org/10.1177/0734282908330580
Atiyah, K., Priatna, N., & colleagues. (2023). Analysis of the Connecting, Organizing, Reflecting and Extending (CORE) model to improving the mathematical reasoning ability students. SJME (Supremum Journal of Mathematics Education), 7, 157–167. https://doi.org/10.35706/sjme.v7i2.7746
Beilock, S. L., & Maloney, E. A. (2015). Math anxiety: A factor in math achievement not to be ignored. Policy Insights from the Behavioral and Brain Sciences, 2(1), 4–12. https://doi.org/10.1177/2372732215601438
Benbow, C. P., & Stanley, J. C. (1980). Sex differences in mathematical reasoning ability: More facts. Science, 210(4475), 1262–1264. https://doi.org/10.1126/science.7434024
Charles, M., & Bradley, K. (2009). Indulging our gendered selves? Sex segregation by field of study in 44 countries. American Journal of Sociology, 114(4), 924–976. https://doi.org/10.1086/597055
Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35. https://doi.org/10.1037/bul0000052
Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43(6), 1241–1299.
Duckworth, A. L., Quinn, P. D., & Tsukayama, E. (2019). What No Child Left Behind leaves behind: The roles of IQ and self-control in predicting standardized achievement test scores and report card grades. Journal of Educational Psychology, 104(2), 439–451. https://doi.org/10.1037/a0015863
Durlak, J. A., & DuPre, E. P. (2008). Implementation matters: A review of research on the influence of implementation on program outcomes and the factors affecting implementation. American Journal of Community Psychology, 41(3–4), 327–350. https://doi.org/10.1007/s10464-008-9165-0
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153
Else-Quest, N. M., Mineo, C. C., & Higgins, A. (2013). Mathematics achievement of girls and women: A meta-analysis and explanatory framework. Review of Educational Research, 83(3), 385–423. https://doi.org/10.3102/0034654313482465
Fan, X., & Chen, M. (2001). Parental involvement and students' academic achievement: A meta-analysis. Educational Psychology Review, 13(1), 1–22. https://doi.org/10.1023/A:1009048817385
Fauzi, I., Rakhmat, C., & Budiman, N. (2023). Complex Thinking: How are Students' Mathematical Problem-Solving Skills in Elementary School?. Bulletin of Science Education, 3(3), 228-240. https://doi.org/10.51278/bse.v3i3.916
Fennema, E., & Sherman, J. (1976). Sex-related differences in mathematics achievement, spatial visualization, and affective factors. American Educational Research Journal, 13(1), 51–71. https://doi.org/10.3102/00028312013001051
Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. https://doi.org/10.1073/pnas.1319030111
Frenzel, A. C., Goetz, T., & Pekrun, R. (2007). Emotional transmission in the classroom: Exploring the relationship between teacher and student enjoyment. Journal of Educational Psychology, 99(3), 525–536. https://doi.org/10.1037/0022-0663.99.3.525
Gilligan, C. (1982). In a different voice: Psychological theory and women’s development. Harvard University Press.
Han, S. S., & Weiss, B. (2005). Sustainability of teacher implementation of school-based mental health programs. Journal of Abnormal Child Psychology, 33(6), 665–679. https://doi.org/10.1007/s10802-005-7646-2
Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge.
Hyde, J. S. (1990). Gender differences in mathematics performance: A meta-analysis. Psychological Bulletin, 107(2), 139–155. https://doi.org/10.1037/0033-2909.107.2.139
Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance. Science, 321(5888), 494–495. https://doi.org/10.1126/science.1160364
Kim, Y., & Baylor, A. L. (2016). Research-based design of pedagogical agents to support student learning: Review and implications. International Journal of Artificial Intelligence in Education, 26(1), 160–196. https://doi.org/10.1007/s40593-015-0054-4
Kementerian Pendidikan dan Kebudayaan. (2014). Matematika untuk SMA/MA Kelas X Semester 2. Pusat Kurikulum dan Perbukuan.
Kementerian Pendidikan dan Kebudayaan. (2021). Matematika untuk SMA/SMK Kelas X. Pusat Kurikulum dan Perbukuan.
Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi Republik Indonesia. (2022). Kurikulum Merdeka. Retrieved April 10, 2024, from https://www.kemdikbud.go.id/
Kurtz-Costes, B., Helmke, L. A., & Rowley, S. J. (2014). Gender stereotypes and the development of math self-concept in children: A longitudinal study. Sex Roles, 70(7–8), 342–355. https://doi.org/10.1007/s11199-014-0340-z
Lepore, M. (2024). A holistic framework to model students’ cognitive process in mathematics education through fuzzy cognitive maps. Heliyon, 10, e35863. https://doi.org/10.1016/j.heliyon.2024.e35863
Lestari, F., Efendi, D., & Dara, T. (2023). Video Online Learning: An Alternative for Students' Mathematics Problem Solving. Bulletin of Science Education, 3(3), 171-178. https://doi.org/10.51278/bse.v3i3.807
Lubienski, S. T., Robinson, J. P., & Ganley, C. M. (2013). Is there a gender gap in mathematical development? Educational Researcher, 42(5), 238–244. https://doi.org/10.3102/0013189X13486649
Loka, J. M., Wena, I. M., & Wibawa, K. A. (2020). Pengaruh penerapan model pembelajaran CORE terhadap hasil belajar matematika siswa kelas VIII SMP Widya Sakti Denpasar. In Prosiding Mahasaraswati Seminar Nasional Pendidikan Matematika.
Maccoby, E. E., & Jacklin, C. N. (1974). The psychology of sex differences. Stanford University Press.
Martin, A. J., & Marsh, H. W. (2006). Academic resilience and its psychological and educational correlates: A construct validity approach. Psychology in the Schools, 43(3), 267–281. https://doi.org/10.1002/pits.20149
Michael, J. (2006). Where’s the evidence that active learning works? Advances in Physiology Education, 30(4), 159–167. https://doi.org/10.1152/advan.00053.2006
Muizaddin, R., & Santoso, B. (2016). Model pembelajaran CORE sebagai sarana dalam meningkatan hasil belajar siswa. Jurnal Pendidikan Manajemen Perkantoran, 1, 224–232.
Ningsih, S. W., Sugiman, S., Merliza, P., & Ralmugiz, U. (2020). Keefektifan model pembelajaran CORE dengan strategi konflik kognitif ditinjau dari prestasi belajar, berpikir kritis, dan self-efficacy. Pythagoras: Jurnal Matematika dan Pendidikan Matematika, 15, 73–86.
Nugraha, A. A. (2024). Eksperimentasi model pembelajaran CORE (Connecting, Organizing, Reflecting, Extending) terhadap kemampuan penalaran matematis ditinjau dari disposisi matematis siswa Fase E SMA N 4 Surakarta tahun ajaran 2023/2024 (Undergraduate thesis, Universitas Sebelas Maret Surakarta). Unpublished manuscript.
OECD. (2019). PISA 2018 results (Volume I): What students know and can do. OECD Publishing. https://doi.org/10.1787/5f07c754-en
Ong, M., Wright, C., Espinosa, L., & Orfield, G. (2011). Inside the double bind: A synthesis of empirical research on undergraduate and graduate women of color in STEM. Harvard Educational Review, 81(2), 172–209. https://doi.org/10.17763/haer.81.2.t022245n7x4752v2
Oz, T., & Isk, A. (2024). Exploring mathematical reasoning skills of middle school students. Thinking Skills and Creativity, 53, 101612. https://doi.org/10.1016/j.tsc.2024.101612
Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2017). Measuring emotions in students’ learning and performance: The achievement emotions questionnaire (AEQ). Contemporary Educational Psychology, 33(3), 315–319. https://doi.org/10.1016/j.cedpsych.2007.01.002
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9
Peranginangin, A. P. (2023). Education and Mathematics Models (A Case Study of Epidemiology of Virus Spread). Bulletin of Science Education, 3(3), 330-347. https://doi.org/10.51278/bse.v3i3.940
Pramesti, G., & Ario, W. (2021). Mudah dan menyenangkan mengolah data dengan SPSS Statistika 26. Jakarta: Gramedia.
Pramesti, G., Surjatiningsih, M., & Nastiti, B. T. Y. (2024). Is learning trajectory necessary for mathematics junior high school students’ understanding ability? Unnes Journal of Mathematics Education, 13, 171–184.
Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223–231. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x
Rusani, I., Anwar, Z., Arshad, R. B., Budiarti, M. I. E., & Sira’a, Y. (2024). Analysis of Students' Mathematical Problem-Solving Ability and Semiotics in Terms of Adersity Quotient (AQ). Bulletin of Science Education, 4(3), 279-290. https://doi.org/10.51278/bse.v4i3.1609
Sadler, P. M., Sonnert, G., Hazari, Z., & Tai, R. (2012). Stability and volatility of STEM career interest in high school: A gender study. Science Education, 96(3), 411–427. https://doi.org/10.1002/sce.21007
Schleicher, A. (2018). World class: How to build a 21st-century school system. OECD Publishing.
Steele, C. M. (2011). Whistling Vivaldi: How stereotypes affect us and what we can do. W. W. Norton & Company.
Stoet, G., & Geary, D. C. (2018). The gender-equality paradox in science, technology, engineering, and mathematics education. Psychological Science, 29(4), 581–593. https://doi.org/10.1177/0956797617741719
Qi, Y., Chen, Y., Yu, X., Yang, X., He, X., & Ma, X. (2024). The relationships among working memory, inhibitory control, and mathematical skills in primary school children: Analogical reasoning matters. Cognitive Development, 70, 101437. https://doi.org/10.1016/j.cogdev.2024.101437
Retnowati, E., & Aqiila, A. (2017). Efektivitas strategi pengelompokan berpasangan dalam pembelajaran matematika model CORE. Cakrawala Pendidikan, 13–23.
Rusani, I., Anwar, Z., Arshad, R. B., Budiarti, M. I. E., & Sira’a, Y. (2024). Analysis of Students' Mathematical Problem-Solving Ability and Semiotics in Terms of Adersity Quotient (AQ). Bulletin of Science Education, 4(3), 279-290. https://doi.org/10.51278/bse.v4i3.1609
Santoso, S., & Pramesti, G. (2024). Multivariate analysis on students’ cognitive assessment, attitude, and skill evaluation in problem-based learning. Mathematics Education Journal, 8, 172–184.
Sari, E., & colleagues. (2020). CORE (Connecting, Organizing, Reflecting & Extending) learning model to improve the ability of mathematical connections. In Journal of Physics: Conference Series (Vol. 012028). IOP Publishing.
Supianti, I. I., Yaniawati, P., Ramadhan, A. G., Setyaji, M., & Puspitasari, P. (2022). Improving connection ability and mathematical disposition of junior high school students with connecting, organizing, reflecting, extending (CORE) learning model. Jurnal Pendidikan Matematika, 16, 187–202.
Vo, T. T., Dai, S., & French, B. F. (2024). Examining Black girls’ mathematics and science dispositions using large-scale assessment and survey data: A quantcrit framework. Methods in Psychology, 11, 100158.
Walkington, C. A. (2013). Using adaptive learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance and learning outcomes. Journal of Educational Psychology, 105(4), 932–945. https://doi.org/10.1037/a0031882
Wang, M. T., & Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review, 29(1), 119–140. https://doi.org/10.1007/s10648-015-9355-x
Wang, M. T., Eccles, J. S., & Kenny, S. (2013). Not lack of ability but more choice: Individual and gender differences in STEM career choice. Psychological Science, 24(5), 770–775. https://doi.org/10.1177/0956797612463085
Wigfield, A., Eccles, J. S., Schiefele, U., Roeser, R. W., & Davis-Kean, P. (2015). Development of achievement motivation and engagement. In R. M. Lerner (Ed.), Handbook of child psychology and developmental science (7th ed., Vol. 3, pp. 1–44). Wiley.
ZA, H. A., & Aisyah, N. (2025). Penerapan Metode Drill pada Bilangan Operasi Hitung Matematika terhadap Hasil Belajar Siswa Kelas 2 di MI Munada Sungai Nibung. Attractive: Innovative Education Journal, 7(2), 84-108. https://doi.org/10.51278/aj.v7i2.1666
Zhang, Q., Guo, J., & Wei, Y. (2023). Mathematical dispositions among Hong Kong mathematics pre-service teachers: A metaphor-based exploration. Asian Education and Development Studies, 12, 221–235.
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