Arithmetic Proficiency of Pre-Service Science Teachers: An Empirical Study

Authors

Heni Yunilda Hasibuan , Yayat Ruhiat , Cecep Anwar Hadi Firdos Santosa

DOI:

10.29303/jppipa.v10i10.9195

Published:

2024-10-31

Issue:

Vol. 10 No. 10 (2024): October

Keywords:

Arithmetic skills, Mathematical proficiency, Pre-service science teachers, Science education

Research Articles

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Hasibuan, H. Y., Ruhiat, Y., & Santosa, C. A. H. F. (2024). Arithmetic Proficiency of Pre-Service Science Teachers: An Empirical Study. Jurnal Penelitian Pendidikan IPA, 10(10), 7803–7812. https://doi.org/10.29303/jppipa.v10i10.9195
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Abstract

Mastery of arithmetic operations is fundamental for students pursuing science education, as these skills are essential in solving complex problems in physics, chemistry, and biology. However, gaps in students' arithmetic proficiency can hinder their academic and professional development. This study aims to examine the arithmetic skills of pre-service science teachers in solving mathematical problems across six domains: addition, subtraction, multiplication, division, exponentiation, and mixed operations. A total of 37 short-answer questions were administered, and the results were analyzed by domain. The findings indicate that students demonstrate proficiency in basic operations involving whole numbers, particularly in addition and subtraction. However, challenges persist in the areas of fractions, decimals, and mixed operations, where accuracy rates were notably lower. These gaps in understanding may affect students' ability to apply mathematical concepts in their science courses and future teaching roles. The study's limitations include a focus on quantitative results without exploring the cognitive processes behind student errors. Future research should investigate intervention strategies to address these weaknesses, potentially through targeted instructional approaches or the use of technology to enhance learning outcomes

References

Achufusi-Aka, N. N., & Offiah, F. C. (2011). Prior knowledge of relevant mathematical concepts and gender as factors in achievement in stoichiometry. Mathematics Connection, 10. https://www.ajol.info/index.php/mc/article/view/72798

Alfaris, L., Siagian, R. C., & Sumarto, E. P. (2023). Study review of the speed of light in space-time for STEM student. Jurnal Penelitian Pendidikan IPA, 9(2), 509–519. https://doi.org/10.29303/jppipa.v9i2.2757

Alivio, T. E. G., Howard, E., Mamiya, B., & Williamson, V. M. (2020). How does a math review impact a student’s arithmetic skills and performance in first-semester general chemistry? Journal of Science Education and Technology, 29, 703–712. https://doi.org/10.1007/s10956-020-09851-7

Asshagab, S. M., Ledang, I., Galib, L. M., & Halmuniati. (2023). Analisis kemampuan matematis mahasiswa tadris IPA pada mata kuliah mekanika. Pedagogika: Jurnal Pedagogik Dan Dinamika Pendidikan, 11(1), 206–219. https://doi.org/10.30598/pedagogikavol11issue1year2023

Atayan, A. M., Nikitina, A. V., Sukhinov, A. I., & Chistyakov, A. E. (2022). Mathematical modeling of hazardous natural phenomena in a shallow basin. Computational Mathematics and Mathematical Physics, 62, 269–286. https://doi.org/10.1134/S0965542521120034

Atit, K., Power, J. R., Pigott, T., Lee, J., Geer, E. A., Uttal, D. H., Ganley, C. M., & Sorby, S. A. (2022). Examining the relations between spatial skills and mathematical performance: A meta-analysis. Psychonomic Bulletin & Review, 29, 699–720. https://doi.org/10.3758/s13423-021-02012-w

Basser, P. J., & Jones, D. K. (2002). Diffusion-tensor MRI: Theory, experimental design and data analysis - A technical review. NMR Biomed., 15, 456–467. https://doi.org/10.1002/nbm.783

Beattie, J. R., & Esmonde-White, F. W. L. (2021). Exploration of principal component analysis: Deriving principal component analysis visually using spectra. Applied Spectroscopy, 75(4), 361–375. https://doi.org/10.1177/0003702820987847

Engelbrecht, J., & Borba, M. C. (2024). Recent developments in using digital technology in mathematics education. ZDM-Mathematics Education, 56, 281–292. https://doi.org/10.1007/s11858-023-01530-2

Fredricks, J. A., Hofkens, T., Wang, M.-T., Mortenson, E., & Scott, P. (2018). Supporting girls’ and boys’ engagement in math and science learning: A mixed methods study. Journal of Research in Science Teaching, 55(2), 271–298. https://doi.org/10.1002/tea.21419

Goda, H., Sasaki, E., Akiyama, K., Maruyama-Nakashita, A., Nakabayashi, K., Li, W., Ogawa, M., Yamauchi, Y., Preston, J., Aoki, K., Kiba, T., Takatsuto, S., Fujioka, S., Asami, T., Nakano, T., Kato, H., Mizuno, T., Sakakibara, H., Yamaguchi, S., … Shimada, Y. (2008). The AtGenExpress hormone and chemical treatment data set: Experimental design, data evaluation, model data analysis and data access. The Plant Journal, 55(3), 526–542. https://doi.org/10.1111/j.1365-313X.2008.03510.x

Gupta, T. (2019). Promoting mathematical reasoning and problem solving through inquiry-based relevance focused computer simulations: A stoichiometry lab. Chemistry Teacher International, 1(1). https://doi.org/10.1515/cti-2018-0008

Hakim, D. L. (2023). Relationship between science and mathematics student learning outcomes. Jurnal Penelitian Pendidikan IPA, 9(5), 3890–3898. https://doi.org/10.29303/jppipa.v9i5.3684

Hasibuan, H. Y., Syarifudin, E., Suherman, & Santosa, C. A. H. F. (2023). Ethnoscience as the policy implementation of Kurikulum Merdeka in science learning: A systematic literature review. Jurnal Penelitian Pendidikan IPA, 9(8), 366–372. https://doi.org/10.29303/jppipa.v9i8.4500

Hasibuan, H. Y., Yuhana, Y., Santosa, C. A. H. F., Syamsuri, S., & Wahyudin, U. (2023). Menyelisik penelitian terkait diagnostik kognitif materi matematika di Indonesia melalui systematic literature review. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 12(2), 1762–1777. https://doi.org/10.24127/ajpm.v12i2.6886

Hidayah, Z., Ilhami, S. A. A., As-Syakur, A., Wiyanto, D. B., & Wirayuhanto, H. (2023). Pemodelan spasial genangan akibat kenaikan muka air laut di pesisir selatan kabupaten Tulungagung Jawa Timur. Jurnal Kelautan Nasional, 18(1), 1–12. https://doi.org/10.15578/jkn.v18i1.10796

Hidayat, R., & Wardat, Y. (2023). A systematic review of augmented reality in science, technology, engineering and mathematics education. Education and Information Technologies, 29, 9257–9282. https://doi.org/10.1007/s10639-023-12157-x

Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context specific meta-analysis. Computers & Education, 153, 1–25. https://doi.org/10.1016/j.compedu.2020.103897

Judijanto, L., Manu, C. M. A., Sitopu, J. W., Mangelep, N. O., & Hardiansyah, A. (2024). The impact of mathematics in science and technology development. International Journal of Teaching and Learning, 2(2), 451–458.

Kusaeri, & Ridho, A. (2019). Learning outcome of mathematics and science: Features of Indonesian madrasah students. Jurnal Penelitian Dan Evaluasi Pendidikan, 23(1), 95–105. https://doi.org/10.21831/pep.v23i1.24881

Lee, N. H., Lee, J., & Wong, Z. Y. (2021). Preparing students for the fourth industrial revolution through mathematical learning: The constructivist learning design. Journal of Educational Research in Mathematics, 31(3), 321–356. https://doi.org/10.29275/jerm.2021.31.3.321

Lobell, D., & Burke, M. (2010). On the use of statistical models to predict crop yield responses to climate change. Agricultural and Forest Meteorology, 150, 1443–1452. https://doi.org/10.1016/J.AGRFORMET.2010.07.008

National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics.

Ng, B. L. L., Liu, W. C., & Wang, J. C. K. (2016). Student motivation and learning in mathematics and science: A cluster analysis. International Journal of Science and Mathematics Education, 14, 1359–1376. https://doi.org/10.1007/s10763-015-9654-1

Noya, T. I., Gaol, J. L., & Agus, S. B. (2024). Estimasi area tergenang akibat kenaikan muka air laut menggunakan data unmanned aerial vehicles (UAV) pada kawasan pesisir teluk Ambon dalam, provinsi Maluku, Indonesia (Studi kasus: Kawasan pesisir desa Waiheru). Jurnal Kelautan Tropis, 27(2), 296–310. https://doi.org/10.14710/jkt.v27i2.23005

Pospiech, G., & Fischer, H. E. (2022). Physical–mathematical modelling and its role in learning physics. In Physics Education (pp. 201–229). Springer, Cham. https://doi.org/10.1007/978-3-030-87391-2_8

Powell, C. B., Simpson, J., Williamson, V. M., Dubrovskiy, A., Walker, D. R., Jang, B., Shelton, G. R., & Mason, D. (2020). Impact of arithmetic automaticity on students’ success in second-semester general chemistry. Chemistry Education Research and Practice, 21, 1028–1041. https://doi.org/10.1039/D0RP00006J

Quinn, G. P., & Keough, M. J. (2002). Experimental design and data analysis for biologists. Cambridge University Press.

Ramful, A., & Narod, F. B. (2014). Proportional reasoning in the learning of chemistry: Levels of complexity. Mathematics Education Research Journal, 26, 25–46. https://doi.org/10.1007/S13394-013-0110-7

Régnière, J., Powell, J., Bentz, B., & Nealis, V. (2012). Effects of temperature on development, survival and reproduction of insects: Experimental design, data analysis and modeling. Journal of Insect Physiology, 58(5), 634–647. https://doi.org/10.1016/j.jinsphys.2012.01.010

Ríordáin, M. N., Johnston, J., & Walshe, G. (2015). Making mathematics and science integration happen: Key aspects of practice. International Journal of Mathematical Education in Science and Technology, 47(2), 233–255. https://doi.org/10.1080/0020739X.2015.1078001

Santosa, C. A. H. F., Rafianti, I., & Yulistiany, D. (2022). Worked-example method on mathematical problem-solving ability in term of students’ initial ability. Kreano, Jurnal Matematika Kreatif-Inovatif, 13(2), 210–220. https://doi.org/10.15294/kreano.v13i2.33301

Solís, M., Cordero, F., Barrios-Borges, E., & Cruz-Ramos, A. A. D. la. (2022). Modelling of natural phenomena as a source to re-signify mathematical knowledge. In M. Rosa, F. Cordero, D. C. Orey, & P. Carranza (Eds.), Mathematical modelling programs in Latin America: A collaborative context for social construction of knowledge for educational change (pp. 367–389). Springer.

Sudha, V., Murugadoss, G., & Thangamuthu, R. (2021). Structural and morphological tuning of Cu‑based metal oxide nanoparticles by a facile chemical method and highly electrochemical sensing of sulphite. Scientific Reports, 11(3413), 1–12. https://doi.org/10.1038/s41598-021-82741-z

Szabo, Z. K., Körtesi, P., Guncaga, J., Szabo, D., & Neag, R. (2020). Examples of problem-solving strategies in mathematics education supporting the sustainability of 21st-century skills. Sustainability, 12, 1–28. https://doi.org/10.3390/su122310113

Tolmie, A. K., Ghazali, Z., & Morris, S. (2016). Children’s science learning: A core skills approach. British Journal of Educational Psychology, 86(3), 481–497. https://doi.org/10.1111/bjep.12119

Varelas, M., Martin, D. B., & Kane, J. M. (2013). Content learning and identity construction: A framework to strengthen african american students’ mathematics and science learning in urban elementary schools. Human Development, 55(5–6), 319–339. https://doi.org/10.1159/000345324

Zhuravkov, M., & Romanova, N. (2016). Review of methods and approaches for mechanical problem solutions based on fractional calculus. Mathematics and Mechanics of Solids, 21, 595–620. https://doi.org/10.1177/1081286514532934

Author Biographies

Heni Yunilda Hasibuan, Universitas Sultan Ageng Tirtayasa

Yayat Ruhiat, Universitas Sultan Ageng Tirtayasa

Department of Physics Education

Cecep Anwar Hadi Firdos Santosa, Universitas Sultan Ageng Tirtayasa

Department of Mathematics Education

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Copyright (c) 2024 Heni Yunilda Hasibuan, Yayat Ruhiat, Cecep Anwar Hadi Firdos Santosa

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