Effects Of Microsoft Mathematics 4.0 On Prospective Mathematics Teachers' Computational Thinking  And Learning Motivation

Rafika Meiliati; Dima Marillah; Fitri; Achmad Salido; Aswin; Dayana Sabila Husain

doi:10.24239/koordinat.v7i1.194

Rafika Meiliati Universitas Sembilan belas November Kolaka
Dima Marillah Universitas Sembilan belas November Kolaka
Fitri Universitas Sembilan belas November Kolaka
Achmad Salido Universitas Sembilan belas November Kolaka
Aswin Universitas Sembilan belas November Kolaka
Dayana Sabila Husain Universitas Sembilan belas November Kolaka

DOI: https://doi.org/10.24239/koordinat.v7i1.194

Keywords: Computational thinking, Learning motivation, Microsoft mathematics 4.0, Prospective Mathematics Teachers’

Abstract

This study aimed to examine the effect of Microsoft Mathematics 4.0 on prospective mathematics teachers’ computational thinking (CT) skills and learning motivation in learning functions. A quantitative approach with a quasi-experimental one-group pre-test–post-test design was employed, involving 17 first-semester mathematics education students at Universitas Sembilanbelas November Kolaka. The participants were prospective mathematics teachers who studied the topic of functions using Microsoft Mathematics 4.0 as an interactive learning tool. Data were collected using CT tests and learning motivation questionnaires and analyzed using descriptive statistics, the Shapiro–Wilk normality test, and paired-samples t-tests. The results revealed a statistically significant improvement in students’ CT skills (t(16) = −5.33, p < 0.05) and learning motivation (t(16) = −13.93, p < 0.05) after learning functions with the support of Microsoft Mathematics 4.0. These findings suggest that integrating interactive mathematical software in learning functions can effectively enhance both students’ computational thinking and their learning motivation

References

Abar, C. A. A. P., Santos, José Manuel Dos Santos Dos Breda, A. M. R. D., & Lavicza, Z. (2025). Automatic feedback in mathematics education: A pathway to robotics and computational thinking. Acta Scientiae, 27(2), 1–27. https://doi.org/10.17648/acta.scientiae.8240

Abylkassymova, A. E., Duisebayeva, A. B., Tuyakov, Y. A., Ardabayeva, A. K., & Kossanov, B. M. (2025). Enhancing the preparation of future mathematics teachers in a digital learning environment. International Journal of Information and Education Technology, 15(6), 1193–1200. https://doi.org/10.18178/ijiet.2025.15.6.2322

Angraini, L. M., & Abdurrahman, A. (2024). Computational thinking readiness level of first-year students of mathematics education. International Journal of Mathematics and Mathematics Education (IJMME), 2(3), 207–221. https://doi.org/10.56855/ijmme.v2i3.1099

Baten, E., Vansteenkiste, M., De Muynck, G. J., De Poortere, E., & Desoete, A. (2020). How can the blow of math difficulty on elementary school children’s motivational, cognitive, and affective experiences be dampened? The critical role of autonomy-supportive instructions. Journal of Educational Psychology, 112(8), 1490–1505. https://doi.org/10.1037/edu0000444

Bilqis, A. A. S., Astuti, W., & Hardi, H. (2025). The role of interactive technology in enhancing student engagement in mathematics. Jurnal Pendidikan Matematika, 16(2), 209–215. http://ojs.uho.ac.id/index.php/jpm

Chan, S.-W., Looi, C.-K., Ho, W. K., & Kim, M. S. (2023). Tools and approaches for integrating computational thinking and mathematics: A scoping review of current empirical studies. Journal of Educational Computing Research, 60(8), 2036–2080. https://doi.org/10.1177/07356331221098793

Dockendorff, M. (2020). How can digital technology enhance mathematics teaching and learning? In Examining Multiple Intelligences and Digital Technologies for Enhanced Learning Opportunities (pp. 216–243). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-7998-0249-5.ch011

Dubinina, G., Konnova, L., & Stepanyan, I. (2022). Technologies for teaching mathematics in a multilingual digital environment. Education Sciences, 12, Article 590. https://doi.org/10.3390/educsci12090590

Fung, C. H., & Poon, K. K. (2020). Can dynamic activities boost mathematics understanding and metacognition? A case study on the limit of rational functions. International Journal of Mathematical Education in Science and Technology, 52(8), 1225–1239. https://doi.org/10.1080/0020739X.2020.1749905

Gopalan, V., Bakar, J. A. A., Zulkifli, A. N., Alwi, A., & Mat, R. C. (2017). A review of the motivation theories in learning. AIP Conference Proceedings, 1891(1), 020043. https://doi.org/10.1063/1.5005376

Higgins, K., Huscroft-D’Angelo, J., & Crawford, L. (2019). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research, 57(2), 283–319. https://doi.org/10.1177/0735633117748416

Hossein-Mohand, H., & Hossein-Mohand, H. (2023). Influence of motivation on the perception of mathematics by secondary school students. Frontiers in Psychology, 13(January), 1–16. https://doi.org/10.3389/fpsyg.2022.1111600

Irawan, E., Rosjanuardi, R., & Prabawanto, S. (2024). Research trends of computational thinking in mathematics learning: A bibliometric analysis from 2009 to 2023. Eurasia Journal of Mathematics, Science and Technology Education, 20(3). https://doi.org/10.29333/ejmste/14343

Jamna, N. D., Hamid, H., & Bakar, M. T. (2022). Analisis kemampuan berpikir komputasi matematis siswa SMP pada materi persamaan kuadrat. Jurnal Pendidikan Guru Matematika, 2(3). https://doi.org/10.33387/jpgm.v2i3.5149

Jonsson, B., Mossegård, J., Lithner, J., & Karlsson Wirebring, L. (2022). Creative mathematical reasoning: Does need for cognition matter? Frontiers in Psychology, 12, Article 797807. https://doi.org/10.3389/fpsyg.2021.797807

Kohen, Z., Amram, M., Dagan, M., & Miranda, T. (2019). Self-efficacy and problem-solving skills in mathematics: The effect of instruction-based dynamic versus static visualization. Interactive Learning Environments, 30(4), 759–778. https://doi.org/10.1080/10494820.2019.1683588

Latifah, T., & Afriansyah, E. A. (2021). Kesulitan dalam kemampuan pemecahan masalah matematis siswa pada materi statistika. Journal of Authentic Research on Mathematics Education (JARME), 3(2), 134–150.

Martín-Lucas, J., & Dujo, Á. G. del. (2022). Knowledge-building in an environment mediated by digital technology: A case study in higher education. Education and Information Technologies, 28, 3267–3287. https://doi.org/10.1007/s10639-022-11304-0

Mendezabal, M. J. N., & Tindowen, D. J. C. (2018). Improving students’ attitude, conceptual understanding and procedural skills in differential calculus through Microsoft Mathematics. Journal of Technology and Science Education, 8(4), 385–397. https://doi.org/10.3926/jotse.356

Miguens, A. L. B., Piedade, J. M. N., Santos, R. J. B. dos, & Oliva, T. L. (2024). Meaningful learning in mathematics: A study on motivation for learning and development of computational thinking using educational robotics. Educational Media International, 61, 4–15. https://doi.org/10.1080/09523987.2024.2357472

Murtianto, Y. H., Sutrisno, Nizaruddin, & Muhtarom. (2019). Effect of learning using mathematica software toward mathematical abstraction ability, motivation, and independence of students in analytic geometry. Infinity Journal, 8(2), 219–228. https://doi.org/10.22460/infinity.v8i2.p219-228

Naganjaneyulu, V., Ali, S. M., Ali, M. I., Jabeen, M., & Naseeruddin, S. (2020). Microsoft mathematics as a teaching and learning tool for mathematics. International Journal of Management and Humanities, 5(4), 55–59. https://doi.org/10.35940/ijmh.b1140.125420

Nurlaelah, E., Usdiyana, D., & Fadilah, N. (2024). The relationship between computational thinking ability and logical mathematical intelligence. Mosharafa: Jurnal Pendidikan Matematika, 13(1), 87–96. https://doi.org/10.31980/mosharafa.v13i1.1978

Pérez, A. (2018). A framework for computational thinking dispositions in mathematics education. Journal for Research in Mathematics Education JRME, 49(4), 424–461. https://doi.org/10.5951/jresematheduc.49.4.0424

Pintrich, P. R., Smith, D. A. F., Garcia, T., & Mckeachie, W. J. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (Mslq). Educational and Psychological Measurement, 53(3), 801–813. https://doi.org/10.1177/0013164493053003024

Salsabilah, S. A., & Rahaju, E. B. (2022). Miskonsepsi siswa SMP pada materi grafik fungsi kuadrat. MATHEdunesa, 11(3), 924–937. https://doi.org/10.26740/mathedunesa.v11n3.p924-937

Saputri, A. N., Warsitarumanti, S., Maharani, D., Herman, T., & Hasanah, A. (2024). Analisis faktor-faktor kesulitan siswa dalam belajar materi persamaan kuadrat. PHI: Jurnal Pendidikan Matematika, 8(1), 37. https://doi.org/10.33087/phi.v8i1.332

Sarah, L. L. (2021). Automatic trash bin arduino project (ATAP): Enhancing computational thinking skills through STEM learning. SEAQIS Journal of Science Education, 1(1), 27–35. https://doi.org/10.58249/sjse.v1i1.22

Siregar, F. S. N., & Yahfizham, Y. (2025). Microsoft mathematics sebagai media untuk pengembangan pembelajaran matematika siswa. Pentagon: Jurnal Matematika Dan Ilmu Pengetahuan Alam, 3(2), 100–108. https://doi.org/10.62383/pentagon.v3i2.539

Siregar, T. M., Andini, A., Panjaitan, Aprini Handayani Endy, N. S., & Siregar, Paradiba Apriliani Anggraini, S. (2024). Analisis faktor yang mempengaruhi rendahnya motivasi belajar siswa pada mata pelajaran matematika. AR RUMMAN - Journal of Education and Learning Evaluation, 1(2), 710–715. https://doi.org/10.31932/j-pimat.v2i2.860

Stratton, S. J. (2019). Quasi-experimental design (pre-test and post-test studies) in prehospital and disaster research. Prehospital and Disaster Medicine, 34(6), 573–574. https://doi.org/10.1017/S1049023X19005053

Tanjung, K., & Yahfizham, Y. (2024). Pemanfaatan media pembelajaran matematika berbantuan aplikasi Microsoft Mathematics (Systematic Literature Review). Konstanta : Jurnal Matematika Dan Ilmu Pengetahuan Alam, 2(2), 84–90. https://doi.org/10.59581/konstanta.v2i2.3155

Wang, H. H., & Wang, C. H. A. (2024). Teaching design students machine learning to enhance motivation for learning computational thinking skills. Acta Psychologica, 251(December), 104619. https://doi.org/10.1016/j.actpsy.2024.104619

Wu, T., Sarwono, E., & Huang, Y.-M. (2025). Incorporating computational thinking into virtual laboratories to enhance learning motivation, engagement, and higher-order thinking skills. J. Comput. Assist. Learn., 41(2), Article e70017. https://doi.org/10.1111/jcal.70017

Zhou, X., & Tsai, C.-W. (2023). The effects of socially shared regulation of learning on the computational thinking, motivation, and engagement in collaborative learning by teaching. Education and Information Technologies, 28(7), 8135–8152. https://doi.org/10.1007/s10639-022-11527-1