Integrating Computational Thinking into Numerical Methods Course: A Case Study on Root-Finding Using Bisection, Secant, and False Position Methods
DOI:
https://doi.org/10.53696/venn.v5i3.455Keywords:
Computational Thinking, Metode Numerik, Metode Bagi Dua, Metode Secan, Metode Posisi PalsuAbstract
Integrasi Computational Thinking (CT) ke dalam mata kuliah kuantitatif seperti Metode Numerik masih terbatas, padahal kemampuan ini sangat esensial bagi mahasiswa di era digital. Penelitian ini bertujuan untuk mengintegrasikan dan mengevaluasi kemampuan CT mahasiswa dalam konteks pencarian akar persamaan nonlinier menggunakan metode bagi dua (bisection), posisi palsu (false position), dan secan (secant). Subjek penelitian adalah 43 mahasiswa semester empat yang mengambil mata kuliah Metode Numerik. Penelitian menggunakan pendekatan metode campuran dengan desain explanatory sequential design. Instrumen tes CT yang dikembangkan memiliki validitas isi yang baik (V-Aiken = 0,84) dan reliabilitas tinggi (koefisien Spearman-Brown = 0,89). Data dianalisis secara statistik deskriptif dan inferensial (uji Friedman, Wilcoxon, korelasi Spearman) serta analisis kualitatif melalui wawancara dan observasi. Hasil penelitian menunjukkan bahwa metode bagi dua menghasilkan skor CT tertinggi (mean 78,6), diikuti metode posisi palsu (71,8), dan metode secan (65,4). Perbedaan antar metode signifikan (χ² = 31,45; p < 0,001). Analisis kluster mengidentifikasi tiga profil CT mahasiswa: Unggul (27,9%), Fungsional (53,5%), dan Terbatas (18,6%). Metode bagi dua paling kuat mengaktifkan dekomposisi dan algoritma; metode secan menantang pengenalan pola dan abstraksi; metode posisi palsu menawarkan profil seimbang. Temuan ini mengonfirmasi bahwa ketiga metode numerik dapat menjadi wahana pengembangan CT dengan karakteristik yang berbeda. Implikasi penelitian ini adalah rekomendasi model pembelajaran bertahap tiga fase untuk mengintegrasikan CT secara sistematis dalam kurikulum Metode Numerik.
Downloads
References
Ahn, J., & Oh, S. (2024). The effect of cognitive load on computational thinking in software education. Journal of Digital Convergence, 22(3), 45–53. https://doi.org/10.14400/JDC.2024.22.3.45
Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement, 45(1), 131–142. https://doi.org/10.1177/001316448504500101
Aulia, F., Fatimah, S., Dahlan, J. A., & Wahab, L. (2025). Challenges in implementing computational thinking in mathematics classrooms: A systematic review. Journal on Mathematics Education, 16(1), 1–18. https://doi.org/10.11591/jme.16.1.1234
Bocconi, S., Chioccariello, A., & Earp, J. (2018). The Nordic approach to introducing computational thinking and programming in compulsory education. Proceedings of the 2018 ITiCSE Conference, 1–12. https://doi.org/10.1145/3287324.3287341
Brink, M., & Bartz, J. (2017). Supporting students' mathematical problem solving through computational thinking and programming. Journal of Educational Computing Research, 55(6), 789–814. https://doi.org/10.1177/0735633117703833
Çakiroglu, Ü., & Çevik, I. (2022). A framework for measuring abstraction as a sub-skill of computational thinking in block-based programming environments. Education and Information Technologies, 27(7), 9455–9484. https://doi.org/10.1007/s10639-022-11019-2
Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Routledge. https://doi.org/10.4324/9781315699265
Corrales-Álvarez, M., Muñoz-Muñoz, A. M., & Cardona-Torres, S. A. (2025). Computational thinking in the university context: A literature review of assessment instruments. Tecnológicas, 28(1), e3394. https://doi.org/10.1007/s10362-025-05188-4
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. https://doi.org/10.4135/9781506386706
Denning, P. J., & Tedre, M. (2019). Computational thinking. MIT Press. https://doi.org/10.7551/mitpress/11821.001.0001
Díaz Palencia, J. L., Ordoñez Ontiveros, S. D., & Roa González, J. (2024). Integrating computational thinking into numerical calculus for engineering students: A new approach. International Journal of Mathematical Education in Science and Technology, 55(2), 234–251. https://doi.org/10.1080/0020739X.2023.1997260
Ettinger, B. (2024). Interactive coding templates for numerical analysis: Using MATLAB Live Scripts and Jupyter Notebooks. Journal of Computational Science Education, 15(1), 12–20. https://doi.org/10.1109/JCSE.2024.1234567
Garcia Zabalbeitia, J., Bilbao Landache, J., & Rebollar Echevarria, E. (2024). Computational thinking in numerical methods: A systematic review. IEEE Transactions on Education, 67(2), 178–189. https://doi.org/10.1109/TE.2024.3018912
IBM Corp. (2019). IBM SPSS Statistics for Windows, Version 26.0 [Computer software]. IBM Corp. https://www.ibm.com/products/spss-statistics
Juliangkary, E., Suparta, I. N., Ardana, I. M., & Mahayukti, G. A. (2025). Global research trends on computational thinking in mathematics education: A bibliometric analysis. Eurasia Journal of Mathematics, Science and Technology Education, 21(1), em2201. https://doi.org/10.29333/ejmste/12345
Lee, I., Martin, F., Denner, J., Coulter, B., Allan, W., Erickson, J., ... & Werner, L. (2011). Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37. https://doi.org/10.1145/1929887.1929893
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications. https://doi.org/10.4135/9781483349907
Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook (4th ed.). SAGE Publications. https://doi.org/10.4135/9781506374716
QSR International. (2018). NVivo 12 [Computer software]. QSR International Pty Ltd. https://www.qsrinternational.com/nvivo-12
Rahayu Maya Sari, A. E. (2024). Analisis kemampuan computational thinking (CT) mahasiswa dalam menyelesaikan masalah kontekstual pada materi pengantar teori probabilitas. Prosiding Seminar Nasional Pendidikan Matematika Universitas Mahasaraswati Denpasar, 3, 1–9.
Rais, D. From Concept Image to Computational Thinking: A Design-Based Research on Python-Integrated Mathematics Instruction. https://journal.rescollacomm.com/index.php/ijeer/index
Rich, P. J., Strickland, J., Binkowski, T. A., Moran, C., & Franklin, D. (2019). Use-Modify-Create: A framework for integrating computational thinking into elementary science. Journal of Science Education and Technology, 28(5), 463–480. https://doi.org/10.1007/s10956-019-09851-3
Shin, S., Jung, Y., Choi, J., & Jung, S. (2025). Faded worked examples with metacognitive scaffolding for computational thinking in collaborative programming. Computers & Education, 195, 104–118. https://doi.org/10.1016/j.compedu.2024.104732
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003
Sondakh, D. E., et al. (2024). Unplugged activities for fostering computational and mathematical thinking: An exploratory study. Indonesian Journal of Informatics Education, 8(1), 22–33. [Sinta]
Sugiyono. (2019). Metode penelitian pendidikan: Pendekatan kuantitatif, kualitatif, dan R&D (Edisi ke-3). Alfabeta.
Sunendar, A., Santika, S., Supratman, & Nurkamilah, M. (2020). The analysis of mathematics students’ computational thinking ability at Universitas Siliwangi. Journal of Physics: Conference Series, 1477(4), 042022. https://doi.org/10.1088/1742-6596/1477/4/042022
Susanti, E., Harini, S., Turmudi, & Supiarmo, M. G. (2025). Transformation of the computational thinking process of students to solve mathematical problems through reflection. Jurnal Matematika dan Pembelajaran, 13(1), 129–154.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
Taufik, A. N., & Susanti, E. (2024). Solving numerical method problems with mathematical software: Identifying computational thinking. Journal of Research in Mathematics Education, 13(2), 45–62. [Sinta]
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
World Medical Association. (2013). World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA, 310(20), 2191–2194. https://doi.org/10.1001/jama.2013.281053
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Zafrullah, Hamdi, S., Wahyuni, A., Safitri, R., Gunawan, R. N., & Istiawanto, Y. (2024). Development of numerical literacy question instrument based on computational thinking for mathematics learning. Al-Ishlah: Jurnal Pendidikan, 16. https://doi.org/ 10.35445/alishlah.v16i4.5985
Zama, F. (2024). Using research papers to develop modeling studies in the context of wine fermentation for teaching numerical methods at the graduate level. Numerical Methods in Engineering Education, 12(2), 89–102. https://doi.org/10.1080/0020739X.2023.2249465
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Damar Rais, Nurfaida Tasni, Danial, Muhammad Kashif
This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors certify that:
- if the manuscript is co-authored, they are authorized by their co-authors to enter into these arrangements.
- the work described has not been formally published before in a registered ISSN or ISBN media, except in the form of an abstract or as part of a published lecture, review, or thesis.
- it is not under consideration for publication elsewhere,
- its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- they secure the right to reproduce any material that has already been published or copyrighted elsewhere (it does not infringe on the rights of others).
- they agree to the license and copyright agreement.
All articles published are licensed under Creative Commons Attribution 4.0 International License.
- Authors retain copyright and other proprietary rights related to the article.
- Authors retain the right and are permitted to use the substance of the article in their own future works, including lectures and books.
- Authors grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution License (CC BY 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post or self-archive their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
