Students’ Computational Thinking in Flat-Surfaced Solid Geometry: A Systematic Literature Review
DOI:
https://doi.org/10.31949/dm.v8i1.16967Abstract
The integration of computational thinking (CT) has become increasingly essential in mathematics education, particularly in topics that require spatial reasoning and structured problem solving, such as flat-surfaced solid geometry. This study aims to synthesize empirical evidence on students’ computational thinking abilities within this specific mathematical context through a Systematic Literature Review (SLR). Using a descriptive qualitative approach, this review analyzed seven peer-reviewed articles published between 2020 and 2025 in nationally accredited journals indexed at SINTA levels 1–5. The literature search was conducted using Google Scholar and Publish or Perish, guided by predefined inclusion and exclusion criteria, and the study selection process followed PRISMA guidelines. The findings reveal that students’ computational thinking abilities are generally at low to moderate levels and unevenly developed across indicators, with abstraction and decomposition more prominent than pattern recognition and algorithmic thinking. Instructional designs incorporating visualization, contextualization, and structured problem engagement effectively supported CT development, whereas unplugged and manipulative-based activities proved beneficial at the elementary level. However, most studies emphasize outcome-based assessments and provide limited insight into students’ cognitive processes during problem solving. These findings highlight the need for theoretically grounded instructional designs and process-oriented assessment frameworks to support a more integrated and sustainable development of computational thinking in geometry learning.
Keywords:
Computational thinking, Flat-surfaced solid geometry, Mathematics education, Systematic literature review, Problem solvingDownloads
References
Abdul Hanid, M., Mohamad Said, M., Yahaya, N., et al. (2022). Effects of augmented reality application integration with computational thinking in geometry topics. Education and Information Technologies, 27, 9485–9521. https://doi.org/10.1007/s10639-022-10994-w
Abidi, M. H., Cahyono, H., & Susanti, R. D. (2023). Analysis of students’ computational thinking ability in solving contextual problems. Mathematics Education Journal, 7(2), 216–224. https://doi.org/10.22219/mej.v7i1.25041
Acevedo-Borrega, J., Valverde-Berrocoso, J., & Garrido-Arroyo, M. C. (2022). Computational thinking and educational technology: A scoping review of the literature. Education Sciences, 12(1), Article 39. https://doi.org/10.3390/educsci12010039
Aulia, M., Fatimah, S., Dahlan, J. A., & Wahab, A. (2025). Exploring research on computational thinking in mathematics: Trends, challenges, and impact on modern learning. Jurnal Pendidikan MIPA, 26(2), 1196–1218. https://doi.org/10.23960/jpmipa.v26i2.pp1196-1218
Çakiroğlu, Ü., & Selçuk, V. (2025). Machine learning meets secondary school classrooms: Using hands-on activities to advance computational thinking. Education and Information Technologies, 30, 9547–9571. https://doi.org/10.1007/s10639-024-13196-8
Clarke-Midura, J., Silvis, D., Shumway, J. F., Lee, V. R., & Kozlowski, J. S. (2023). Developing a kindergarten computational thinking assessment using evidence-centered design: The case of algorithmic thinking. In Assessing computational thinking (pp. 5–28). Routledge. https://doi.org/10.4324/9781003431152-2
Dagli, Z., & Sancar Tokmak, H. (2022). Exploring high school computer science course teachers’ instructional design processes for improving students’ computational thinking skills. Journal of Research on Technology in Education, 54(4), 511–534. https://doi.org/10.1080/15391523.2021.1881844
Duckworth, D., & Fraillon, J. (2025). Computational thinking framework. In J. Fraillon & M. Rožman (Eds.), IEA international computer and information literacy study 2023 (pp. xx–xx). Springer. https://doi.org/10.1007/978-3-031-61194-0_3
Fachrudin, A. D., & Juniati, D. (2023). Kinds of mathematical thinking addressed in geometry research in schools: A systematic review. Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika, 6(2), 154–165. https://doi.org/10.26740/jrpipm.v6n2.p154-165
Fauzi, A. L., Kusumah, Y. S., Nurlaelah, E., & Juandi, D. (2024). Computational thinking in mathematics education: A systematic literature review on its implementation and impact on students’ learning. Jurnal Kependidikan, 10(2), 640–653. https://doi.org/10.33394/jk.v10i2.11140
Fitdyawati, S. D., & In’am, A. (2025). Mathematical problem-solving ability from the perspective of the computational thinking approach. Kreano: Jurnal Matematika Kreatif-Inovatif, 16(1), 210–227. https://doi.org/10.15294/kreano.v16i1.12197
Hidayat, R., Adnan, M., Abdullah, M. F. N. L., & Safrudiannur. (2022). A systematic literature review on the measurement of mathematical modeling in mathematics education. Eurasia Journal of Mathematics, Science and Technology Education, 18(5), em2108. https://doi.org/10.29333/ejmste/12007
Juandi, D. (2024). Computational thinking in mathematics instruction integrated with STEAM education: Global trends and students’ achievement over the last two decades. Beta: Jurnal Tadris Matematika, 17(2), 101–134. juandi
Kaya, D., Yaşar, A. Ö., Çetin, İ., & Kutluca, T. (2025). The relationship between 21st-century skills and computational thinking skills of prospective mathematics and science teachers. Journal of Pedagogical Research, 9(1), 73–95. https://doi.org/10.33902/JPR.202531498
Lehmann, T. H. (2024). How current perspectives on algorithmic thinking can be applied to students’ engagement in algorithmatizing tasks. Mathematics Education Research Journal, 36, 609–643. https://doi.org/10.1007/s13394-023-00462-0
Lu, C., Macdonald, R., Odell, B., et al. (2022). A scoping review of computational thinking assessments in higher education. Journal of Computing in Higher Education, 34, 416–461. https://doi.org/10.1007/s12528-021-09305-y
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, 8171–8193. https://doi.org/10.1007/s10639-022-11518-2
Mangiri, G. R. P., & Prabawanto, S. (2024). Exploring computational thinking in learning mathematics: A systematic literature review from 2017–2024. Jurnal Pendidikan MIPA, 25(1), 34–52. https://doi.org/10.23960/jpmipa/v25i1.pp34-52
Masiulionytė-Dagienė, V., & Jevsikova, T. (2025). Towards a process-oriented assessment of computational thinking: Behavioural data and machine learning approach. Interactive Learning Environments, 1–15. https://doi.org/10.1080/10494820.2025.2567601
Mitrayana, M., & Nurlaelah, E. (2023). Computational thinking in mathematics learning: A systematic literature review. Indonesian Journal of Teaching in Science, 3(2), 133–142. https://doi.org/10.17509/ijotis.v3i2.60179
Mohamed, M. Z. B., Hidayat, R., Suhaizi, N. N. B., Sabri, N. B. M., Mahmud, M. K. H. B., & Baharuddin, S. N. B. (2022). Artificial intelligence in mathematics education: A systematic literature review. International Electronic Journal of Mathematics Education, 17(3), em0694. https://doi.org/10.29333/iejme/12132
Moreno-Palma, N., Hinojo-Lucena, F. J., Romero-Rodríguez, J. M., & Cáceres-Reche, M. P. (2024). Effectiveness of problem-based learning in the unplugged computational thinking of university students. Education Sciences, 14(7), Article 693. https://doi.org/10.3390/educsci14070693
Navarro, E. R., & de Sousa, M. D. C. (2023). The concept of computational thinking in mathematics education. Journal of Mathematics and Science Teacher, 3(2), 1–11. https://doi.org/10.29333/mathsciteacher/13630
Ochogboju, A. O., & Díez-Palomar, J. (2025). Modeling concrete and virtual manipulatives for mathematics teacher training: A case study in ICT-enhanced pedagogies. Information, 16(8), Article 698. https://doi.org/10.3390/info16080698
Pellas, N. (2025). Enhancing computational thinking, spatial reasoning, and executive function skills: The impact of tangible programming tools in early childhood and across different learner stages. Journal of Educational Computing Research, 63(1), 3–32. https://doi.org/10.1177/07356331241292767
Prahmana, R. C. I., Kusaka, S., Peni, N. R. N., Endo, H., Azhari, A., & Tanikawa, K. (2024). Cross-cultural insights on computational thinking in geometry: Indonesian and Japanese students’ perspectives. Journal on Mathematics Education, 15(2), 613–638. https://doi.org/10.22342/jme.v15i2.pp613-638
Saragih, M. V. A., Nurjanah, N., & Yulianti, K. (2025). Improving high school students’ computational thinking ability and mathematical resilience through project-based learning assisted by GeoGebra. Edumatica: Jurnal Pendidikan Matematika, 15(1), 87–101. https://doi.org/10.22437/edumatica.v15i1.42801
Sumarno, F., Suparman, S., & Mahmudah, K. R. (2025). Global research trends on computational thinking in mathematics education: A bibliometric analysis (2000–2025). Jurnal Math Educator Nusantara, 11(2), 200–219. https://doi.org/10.29407/jmen.v11i2.25725
Tsortanidou, X., Daradoumis, T., & Barberá-Gregori, E. (2023). Unplugged computational thinking at K–6 education: Evidence from a multiple-case study in Spain. Education 3–13, 51(6), 948–965. https://doi.org/10.1080/03004279.2022.2029924
Wang, C., Lu, C., Chen, F., Liu, X., & Wang, Q. (2026). Assessing computational thinking beyond programming: A scoping review of non-programming-based computational thinking assessments for K–12 education. Journal of Computer Assisted Learning, 42(1), e70191. https://doi.org/10.1002/jcal.70191
Wardoyo, G. S., Hadi, F. R., & Pradana, L. N. (2025). Empowering young thinkers: Enhancing computational thinking through problem posing and GeoGebra. Matematika dan Pembelajaran, 13(2), 310–329. https://doi.org/10.33477/mp.v13i2.11428
Weng, X., Ye, H., Dai, Y., & Ng, O. L. (2024). Integrating artificial intelligence and computational thinking in educational contexts: A systematic review of instructional design and student learning outcomes. Journal of Educational Computing Research, 62(6), 1420–1450. https://doi.org/10.1177/07356331241248686
Winarni, S., Driana, E., Ernawati, E., & Setiadi, H. (2025). Implementing computational thinking-based summative assessment in STEM: Opportunities and barriers in an Indonesian Islamic senior high school. Jurnal Pendidikan MIPA, 26(4), 2742–2765. https://doi.org/10.23960/jpmipa.v26i4.pp2742-2765
Wu, T. T., Silitonga, L. M., & Murti, A. T. (2024). Enhancing English writing and higher-order thinking skills through computational thinking. Computers & Education, 213, Article 105012. https://doi.org/10.1016/j.compedu.2024.105012
Ye, H., Liang, B., Ng, O. L., & Yang, X. (2023). Integration of computational thinking in K–12 mathematics education: A systematic review on CT-based mathematics instruction and student learning. International Journal of STEM Education, 10, Article 3. https://doi.org/10.1186/s40594-023-00396-w
Youjun, T., & Xiaomei, M. (2022). Computational thinking: A mediation tool and higher-order thinking for linking EFL grammar knowledge with competency. Thinking Skills and Creativity, 46, Article 101143. https://doi.org/10.1016/j.tsc.2022.101143
Zubainur, C. M., Rossalina, C. R., Subianto, M., & Fadhiliani, D. (2025). Unpacking research on computational thinking in mathematics education: A systematic literature review. Jurnal Elemen, 11(2), 447–467. https://doi.org/10.29408/jel.v11i2.29183
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