How Do Computational Thinking Skills Support Secondary Students in Solving Complex Mathematical Pattern Problems?

Maulida Aulia; Sri Suryanti; Li Long

doi:10.31764/jtam.v10i4.39590

How Do Computational Thinking Skills Support Secondary Students in Solving Complex Mathematical Pattern Problems?

Maulida Aulia, Sri Suryanti, Li Long

Abstract

Abstract: Solving complex number pattern problems not only involves detecting the regularity of the numbers but also involves generalizing the pattern, filtering relevant information, and formulating problem solutions. However, many secondary students have continued to rely on procedural strategies and have failed to employ higher-order cognitive processes in problem-solving tasks. This research investigates how computational thinking (CT) skills facilitate lower secondary students' ability to solve complex number-pattern problems. In addition, the research aims to identify the most prominent CT indicators among the other indicators. The research employed an exploratory case study approach using both quantitative and qualitative methods. Twenty-seven eighth-grade students from a private institution in Indonesia participated in the research. Data were gathered through an open-ended problem-solving test on complex number patterns and through semi-structured interviews with students, using stimulated recall techniques. The quantitative data analysis included descriptive analysis in identifying the levels of CT indicators achieved by the students. On the other hand, the qualitative data analysis involved thematic analysis of the answers on the answer sheets and the interviewees' statements, in accordance with the four CT indicators: decomposition, pattern recognition, abstraction, and algorithmic thinking. The findings show that most students were only able to attain the beginning-to-middle stages of CT. Specifically, pattern recognition (30.80%) and decomposition (23.10%) received the most attention among the students. In contrast, very few students achieved the CT stage of abstraction and algorithmic thinking (7.70%). These results imply that CT is very important for students, enabling them to analyze information and discover regularities. Nonetheless, the problem faced by the students is that of finding solutions for these regularities and making algorithms. As such, there is a need to incorporate computational thinking in mathematics, particularly when teaching students about number sequences. Implications would be providing students with more difficult problems to solve.

Keywords

Computational Thinking Skill; Mathematics Problem Solving; Complex Number Pattern; Abstraction; Algorithmic Thinking.

Full Text:

DOWNLOAD [PDF]

References

Adeoye-Olatunde, O. A., & Olenik, N. (2021). Research and Scholarly Methods: Semi-structured Interviews. Department of Pharmacy Practice Faculty Publications, 1–72. https://doi.org/10.1002/jac5.1441

Adhikari, R., & Timsina, T. P. (2024). An Educational Study Focused on the Application of Mixed Method Approach as a Research Method. OCEM Journal of Management, Technology & Social Sciences, 3(1), 94–109. https://doi.org/10.3126/ocemjmtss.v3i1.62229

Aminah, N., Sukestiyarno, Y. L., Wardono, W., & Cahyono, A. N. (2022). Computational Thinking Process of Prospective Mathematics Teacher in Solving Diophantine Linear Equation Problems. European Journal of Educational Research, 11(3), 1495–1507. https://doi.org/10.12973/eu-jer.11.3.1495

Amri, S., Budiyanto, C. W., & Yuana, R. A. (2019). Beyond computational thinking: Investigating CT roles in the 21st century skill efficacy. AIP Conference Proceedings, 2194, 1–8. https://doi.org/10.1063/1.5139735

Apriandi, D., Retnawati, H., & Abadi, A. M. (2023). How Computational Thinking Skills Students in Solving Problems on Pattern Numbers? AIP Conference Proceedings, 2595, 1–7. https://doi.org/10.1063/5.0123713

Asbar, V., Asma, N., & Husna, A. (2026). Computational Thinking Ability as the Foundation for Solving Contextual Mathematical Problems among Informatics Students. Journal Of Informatics, Education and Management (JIEM), 8(1), 897–904. https://doi.org/10.61992/jiem.v8i1.280

Astuti, A., Suryawati, E., Suanto, E., Yuanita, P., & Noviana, E. (2025). Charting a course: Exploring computational thinking skills in statistics content among junior high school students. Journal of Pedagogical Research, 9(1), 182–202. https://doi.org/10.33902/JPR.202531653

Cahdriyana, R. A., & Richardo, R. (2020). Computational Thinking in Teacher Education. In Emerging Research, Practice, and Policy on Computational Thinking. Springer International Publishing, 205-220. https://doi.org/10.1007/978-3-319-52691-1_13

Chan, S. W., Looi, C. K., Ho, W. K., Huang, W., Seow, P., & Wu, L. (2021). Learning number patterns through computational thinking activities: A Rasch model analysis. Heliyon, 7(9), 1-14. https://doi.org/10.1016/j.heliyon.2021.e07922

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

Costa, J. (2024). Mixed Methods in Educational Large-Scale Studies: Integrating Qualitative Perspectives into Secondary Data Analysis. Education Sciences, 14(12), 1–13. https://doi.org/10.3390/educsci14121347

Cui, Z., Ng, O., & Jong, M. S. (2023). Integration of Computational Thinking with Mathematical Problem-based Learning Integration of Computational Thinking with Mathematical Problem-based Learning: Insights on Affordances for Learning. Educational Technology & Society, 26(2), 131–146. https://doi.org/10.2307/48721001

Dahshan, M., & Galanti, T. (2024). Teachers in the Loop: Integrating Computational Thinking and Mathematics to Build Early Place Value Understanding. Education Sciences, 14(2), 1–19. https://doi.org/10.3390/educsci14020201

Firdaus, A. Q., Suryanti, S., & Hadi, F. N. (2026). Identification of Computational Thinking Patterns in Students Mathematical Problem Solving: Empirical Evidence from Algebra Learning Activities. Jurnal Riset Pendidikan Dan Inovasi Pembelajaran Matematika (JRPIPM), 10(1), 22–32. https://doi.org/10.26740/jrpipm.v10n1.p22-32

Golding, J., & Ince, A. (2024). Ethical Issues in Researching Higher Education Teaching and Learning. 4(3), 1147–1162. https://doi.org/10.3390/encyclopedia

Helsa, Y., Juandi, D., & Turmudi. (2023). Computational Thinking Skills Indicators in Number Patterns. Mathematics Education Journal, 17(2), 167–188. https://doi.org/10.22342/jpm.17.2.20042.167-188

Iskandar, R. S. F., Darhim, D., Dahlan, J. A., & Jupri, A. (2025). Student’s Learning Difficulties On Mathematical Understanding Of A Number Pattern. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 14(1), 199–210. https://doi.org/10.24127/ajpm.v14i1.9677

Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85. https://doi.org/10.1007/BF02300500

Jupri, A., & Drijvers, P. (2016). Student difficulties in mathematizing word problems in Algebra. Eurasia Journal of Mathematics, Science and Technology Education, 12(9), 2481–2502. https://doi.org/10.12973/eurasia.2016.1299a

Knutson, J., & Stagg, K. (2025). The Impact of Teaching Computational Thinking on the Growth of Students Algebraic Thinking. International Journal of Education in Mathematics, Science and Technology, 13(6), 1615–1631. https://doi.org/10.46328/ijemst.5213

Lee, I., Grover, S., Martin, F., Pillai, S., & Malyn-Smith, J. (2020). Computational Thinking from a Disciplinary Perspective: Integrating Computational Thinking in K-12 Science, Technology, Engineering, and Mathematics Education. Journal of Science Education and Technology, 29(1), 1–8. https://doi.org/10.1007/s10956-019-09803-w

Lee, S. W. Y., Tu, H. Y., Chen, G. L., & Lin, H. M. (2023). Exploring the multifaceted roles of mathematics learning in predicting students computational thinking competency. International Journal of STEM Education, 10(1), 1–16. https://doi.org/10.1186/s40594-023-00455-2

Lodi, M., & Martini, S. (2021). Computational Thinking, Between Papert and Wing. Science and Education, 30(4), 883–908. https://doi.org/10.1007/s11191-021-00202-5

Lv, L., Zhong, B., & Liu, X. (2023). A literature review on the empirical studies of the integration of mathematics and computational thinking. Education and Information Technologies, 28(7), 8171–8193. https://doi.org/10.1007/s10639-022-11518-2

Maula, N. F., Suryadi, D., & Jupri, A. (2024). Learning obstacles in the generalization process: In case number pattern topic. Research and Development in Education (RaDEn), 4(2), 964–976. https://doi.org/10.22219/raden.v4i1

Maulina, A. A., & Khusna, H. (2024). Analysis of Computational Thinking Skills of Vocational School Students Based on Mathematical Literacy Skills in the Society 5.0 Era. 9(1), 102–120. https://doi.org/10.33541/edumatsains

Mulligan, J., & Mitchelmore, M. (2009). Awareness of Pattern and Structure in Early Mathematical Development. Mathematics Education Research Journal, 21(2), 33–49. https://doi.org/10.1007/BF03217544

Ngadengon, Z., Subramaniam, T. S., Yasak, Z., Syukri, M., & Hazim, M. N. (2024). Theory On Computational Thinking In Education: A Systematic Review. International Journal of Education, Psychology and Counseling, 9(53), 488–507. https://doi.org/10.35631/IJEPC.953037

Nordby, S. K., Bjerke, A. H., & Mifsud, L. (2022). Computational Thinking in the Primary Mathematics Classroom: a Systematic Review. Digital Experiences in Mathematics Education, 8(1), 27–49. https://doi.org/10.1007/s40751-022-00102-5

Palop, B., Díaz, I., Rodríguez-Muñiz, L. J., & Santaengracia, J. J. (2025). Redefining computational thinking: A holistic framework and its implications for K-12 education. Education and Information Technologies, 30(10), 13385–13410. https://doi.org/10.1007/s10639-024-13297-4

Peng, J., Hao, M., Chen, B., & Wang, M. (2025). Cultivating computational thinking in a STEM course through the ICDCO instructional model. Education and Information Technologies, 30(17), 25137–25175. https://doi.org/10.1007/s10639-025-13716-0

Peracaula-Bosch, M., & González-Martínez, J. (2024). Towards a Hermeneutics of Computational Thinking in Wing’s Approximations. Journal of Educational Computing Research, 61(8), 139–158. https://doi.org/10.1177/07356331231193142

Pinto, E., Cañadas, M. C., & Moreno, A. (2022). Functional Relationships Evidenced and Representations Used by Third Graders Within a Functional Approach to Early Algebra. International Journal of Science and Mathematics Education, 20(6), 1183–1202. https://doi.org/10.1007/s10763-021-10183-0

Puntambekar, S. (2022). Distributed Scaffolding: Scaffolding Students in Classroom Environments. Educational Psychology Review, 34(1), 451–472. https://doi.org/10.1007/s10648-021-09636-3

Purwasih, R., Turmudi, & Dahlan, J. A. (2024). How do you solve number pattern problems through mathematical semiotics analysis and computational thinking? Journal on Mathematics Education, 15(2), 403–430. https://doi.org/10.22342/jme.v15i2.pp403-430

Rabillas, A. R., Kilag, O. K. T., Cañete, N. A., Trazona, M. S., Calope, M. L. L., & Kilag, J. N. (2024). Elementary Math Learning Through Piaget’s Cognitive Development Stages. International Mulitisciplinary Journal Of Research For Innovation, Sustainability and Excellence (IMJRISE), 1(9), 202–2010. https://risejournals.org/index.php/imjrise/article/view/678

Rott, B., Specht, B., & Knipping, C. (2021). A descriptive phase model of problem-solving processes. ZDM - Mathematics Education, 53(4), 737–752. https://doi.org/10.1007/s11858-021-01244-3

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

Subramaniam, S., Maat, S. M., & Mahmud, M. S. (2022). Computational thinking in mathematics education: A systematic review. In Cypriot Journal of Educational Sciences. Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi, 17(6), 2029–2044. https://doi.org/10.18844/cjes.v17i6.7494

Sullivan, P., Clarke, D., & Clarke, B. (2013). Teaching with Tasks for Effective Mathematics Learning. In Teaching With Task For Effective Mathematics Learning. Springer Science & Business Media, 9, 1–201. https://doi.org/10.1007/978-1-4614-4681-1

Susanti, R. D., & Taufik, M. (2021). Analysis of Student Computational Thinking in Solving Social Statistics Problems. SJME (Supremum Journal of Mathematics Education), 5(1). https://doi.org/10.35706/sjme.v5i1.4376

Taherdoost, H. (2016). Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research. In International Journal of Academic Research in Management (IJARM), 5(2). https://doi.org/10.2139/ssrn.3205035

Taufik, M., Inam, A., & Susanti, R. D. (2024). Computational thinking in mathematical problem solving: Pattern recognition. International Journal of Multidisciplinary: Applied Business and Education Research, 5(3), 791–797. https://doi.org/10.11594/ijmaber.05.03.05

Udvaros, J., Forman, N., & Avornicului, M. S. (2023). Developing computational thinking with microcontrollers in Education 4.0. International Journal of Advanced Natural Sciences and Engineering Researches, 4(4), 103–108. https://doi.org/10.59287/ijanser.2023.7.4.563

Verschaffel, L., Schukajlow, S., Star, J., & Van Dooren, W. (2020). Word problems in mathematics education: a survey. ZDM - Mathematics Education, 52(1), 1–16. https://doi.org/10.1007/s11858-020-01130-4

Voon, X. P., Wong, S. L., Wong, L. H., Khambari, M. N. M., & Syed-Abdullah, S. I. S. (2022). Developing Computational Thinking Competencies through Constructivist Argumentation Learning: A Problem-Solving Perspective. International Journal of Information and Education Technology, 12(6), 529–539. https://doi.org/10.18178/ijiet.2022.12.6.1650

Wilkie, K. J., & Ayalon, M. (2018). Investigating Years 7 to 12 students knowledge of linear relationships through different contexts and representations. Mathematics Education Research Journal, 30(4), 499–523. https://doi.org/10.1007/s13394-018-0236-8

Wing, J. M. (2006). Computational Thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215.

Wu, T. T., Asmara, A., Huang, Y. M., & Permata Hapsari, I. (2024). Identification of Problem-Solving Techniques in Computational Thinking Studies: Systematic Literature Review. SAGE Open, 14(2), 1–20. https://doi.org/10.1177/21582440241249897

Yadav, A., Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55–62. https://doi.org/10.1145/2994591

Ye, H., Liang, B., Ng, O. L., & Chai, C. S. (2023). Integration of computational thinking in K-12 mathematics education: a systematic review on CT-based mathematics instruction and student learning. In International Journal of STEM Education. Springer Science and Business Media Deutschland GmbH, 10(1), 1–26. https://doi.org/10.1186/s40594-023-00396-w

Zhai, X., Chu, X., Wang, M., Tsai, C.-C., Liang, J.-C., & Spector, J. M. (2024). A systematic review of Stimulated Recall (SR) in educational research from 2012 to 2022. Humanities and Social Sciences Communications, 11(1), 1–14. https://doi.org/10.1057/s41599-024-02987-6

DOI: https://doi.org/10.31764/jtam.v10i4.39590