ANALYZING STUDENT COMPUTATIONAL THINKING ABILITY IN DATA PRESENTATION BY MATH ANXIETY AND THEIR ASPECTS

Carolina Fadia Dewi(1), Nanda Arista Rizki(2*), Kurniawan Kurniawan(3), Rusdiana Rusdiana(4),

(1) Universitas Mulawarman
(2) Universitas Mulawarman
(3) Universitas Mulawarman
(4) Universitas Mulawarman
(*) Corresponding Author

Abstract


Computational thinking is an essential skill in mathematics learning. However, many students still face difficulties in applying its aspects. This study aims to examine differences in students’ computational thinking ability in the context of data presentation based on math anxiety levels and computational thinking aspects, as well as the interaction between the two. A quantitative approach with a comparative descriptive desig was employed. The research subjects were 119 seventh-grade students of SMP IT Cordova Samarinda, selected using purposive sampling. Research instruments consisted of a math anxiety questionnaire and a computational thinking test covering four aspects: decomposition, pattern recognition, algorithm, and abstraction-generalization. Data were analyzed using the General Linear Model with Two Way Repeated Measures ANOVA. The results revealed significant differences in cmputational thinking ability based on math anxiety level, with a tendency for lower computational thinking ability among students with high math anxiety. Significant differences were also found across computational thinking aspects, with decomposition scoring the highest and abstraction-generalization the lowest. Howeve, no significant interaction was found between math anxiety level and computational thinking aspects. These findings highlight the importance of instructional approaches that consider affective factors to optimize the holistic development of students’ computational thinking across all aspects.

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References


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.v7i2.25041

Adu-Gyamfi, K., & Bossé, M. J. (2014). Processes And Reasoning In Representations Of Linear Functions. International Journal of Science and Mathematics Education, 12(1), 167–192. https://doi.org/10.1007/s10763-013-9416-x

Amalia, A. (2024). Analisis Kemampuan Computational Thinking Siswa SMP Dalam Menyelesaikan Masalah Matematika Ditinjau Dari Kecemasan Matematis. Universitas Pendidikan Indonesia.

Ansori, M. (2020). Pemikiran Komputasi (Computational Thinking) dalam Pemecahan Masalah. Dirasah : Jurnal Studi Ilmu Dan Manajemen Pendidikan Islam, 3(1), 111–126. https://doi.org/10.29062/dirasah.v3i1.83

Ashcraft, M. H., & Krause, J. A. (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin & Review, 14(2), 243–248.

Aunurrahim, M., Yurniawati, & Madani, F. (2024). Analisis Kemampuan Berpikir Komputasi Siswa Kelas V Sekolah Dasar Ditinjau Dari Kecemasan Matematika. Prosiding MAHASENDIKA III Tahun 2024, 270–285.

Bocconi, S., Chioccariello, G. A., Dettori, A. F., & Engelhardt, K. (2016). Developing Computational Thinking in Compulsory Education. Joint Research Centre (JRC) (Issue June). https://doi.org/10.2791/792158

Carey, E., Hill, F., Devine, A., & Szücs, D. (2016). The chicken or the egg? The direction of the relationship between mathematics anxiety and mathematics performance. Frontiers in Psychology, 6(JAN), 1–6. https://doi.org/10.3389/fpsyg.2015.01987

Cavanagh, R., & Sparrow, L. (2010). Measuring mathematics anxiety: Paper 1-Developing a construct model. AARE Annual Conference, 1–11.

Cooke, A., Cavanagh, R., Hurst, C., & Sparrow, L. (2011). Situational effects of mathematics anxiety in pre-service teacher education. 2011 AARE International Research in Education Conference, Melbourne, Australia, 1–14.

Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years? Frontiers in Psychology, 7(APR). https://doi.org/10.3389/fpsyg.2016.00508

Field, A. (2017). Discovering Statistic Using IBM SPSS Statistic 5th. Sage Publication, 53(9), 1689–1699.

Grover, S., & Pea, R. (2013). Computational Thinking in K-12: A Review of the State of the Field. Educational Researcher, 42(1), 38–43. https://doi.org/10.3102/0013189X12463051

Grover, S., & Pea, R. D. (2018). Computational Thinking: A Competency Whose Time Has Come. In S. Sentance, E. Barendsen, & C. Schulte (Eds.), Computer Science Education: Perspectives on Teaching and Learning in School (Issue October, pp. 19–38). Bloomsbury Publishing. https://doi.org/10.5040/9781350057142.ch-003

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

Kamil, M. R., Ihsan Imami, A., & Abadi, A. P. (2021). Analisis kemampuan berpikir komputasional matematis Siswa Kelas IX SMP Negeri 1 Cikampek pada materi pola bilangan. AKSIOMA: Jurnal Matematika Dan Pendidikan Matematika, 12(2), 259–270.

Kuswanto, H., Rodiyanti, N., Kholisho, Y. N., & Arianti, B. D. D. (2020). Pengaruh Kemampuan Matematika Terhadap Kemampuan Computational Thinking Pada Anak Usia Sekolah Dasar. Educatio, 15(2), 138–144. https://doi.org/10.29408/edc.v15i2.2916

Latifah, A. G., Quini, I. F., & Aripin, U. (2024). Kemampuan Berpikir Komputasi Ditinjau dari Kecemasan Belajar Matematika Pembelajaran matematika adalah proses interaksi dari elemen belajar yang bertujuan untuk meningkatkan kemampuan berpikir siswa untuk memecahkan masalah . Pembelajaran matematika dapat. Teorema: Teori Dan Riset Matematika, 09(September), 351–360.

Lestari, S., & Roesdiana, L. (2023). Analisis Kemampuan Berpikir Komputasional Matematis Siswa Pada Materi Program Linear. RANGE: Jurnal Pendidikan Matematika, 4(2), 178–188. https://doi.org/10.32938/jpm.v4i2.3592

Nasiba, U. (2022). Brankas Rahasia: Media Pembelajaran Numerasi Berbasis Berpikir Komputasi untuk Meningkatkan Kemampuan Pemecahan Masalah. Jurnal Didaktika Pendidikan Dasar, 6(2), 521–538. https://doi.org/10.26811/didaktika.v6i2.764

Ow-Yeong, Y. K., Yeter, I. H., & Ali, F. (2023). Learning data science in elementary school mathematics: a comparative curriculum analysis. International Journal of STEM Education, 10(1). https://doi.org/10.1186/s40594-023-00397-9

Setiana, D. S. (2018). Pengembangan Instrumen Tes Matematika untuk Mengukur Kemampuan Berpikir Kritis. Jurnal Pendidikan Surya Edukasi, 4(2), 35–48. https://doi.org/10.37729/jpse.v4i2.5341

Shute, V. J. (2017). Demystifying computational thinking. Educational Research Review, September. https://doi.org/10.1016/j.edurev.2017.09.003

Wardani, N. (2022). Pengaruh Kecemasan Matematika terhadap Hasil Belajar Siswa SMA Kelas X. NUCLEUS, 3(2), 155–161. https://doi.org/10.37010/nuc.v3i2.992

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining Computational Thinking for Mathematics and Science Classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5

Wijaya, R., Fahinu, & Ruslan. (2018). Pengaruh Kecemasan Matematika dan Gender Terhadap Kemampuan Penalaran Adaptif Matematika Siswa SMP Negeri 2 Kendari. Jurnal Pendidikan Matematika, 9(2), 173–184.

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

Yadav, A., Mayfield, C., Zhou, N., & Hambrusch, S. (2014). Computational Thinking in Elementary and Secondary Teacher Education. ACM Transactions on Computing Education, 14(1). https://doi.org/10.1145/2576872




DOI: https://doi.org/10.31327/jme.v10i2.2528

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Copyright (c) 2025 Carolina Fadia Dewi, Nanda Arista Rizki, Kurniawan Kurniawan, Rusdiana Rusdiana


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