IMPROVING INFORMATICS STUDENTS’ MATRIX ALGEBRA CONCEPTUAL UNDERSTANDING THROUGH A PYTHON-BASED LEARNING TRAJECTORY
Padang, Indonesia
DOI:
https://doi.org/10.36085/math-umb.edu.v13i2.9463Abstract
In matrix algebra courses, conceptual understanding remains low. This is due to the lack of integration and relevance of mathematics learning to their competency, namely informatics engineering. Learning trajectory instruction, characterized by sequential learning and Python computing applications relevant to students, provides a solution to improve students' matrix algebra conceptual understanding. The purpose of this study was to examine students' understanding of mathematical concepts in algebra by implementing a Python-based learning trajectory model. This study was a quasi-experimental study with posttest-only control group design. The sample was taken using a random sampling technique. A sample size of 69 students was selected, consisting of 33 students from the experimental class and 36 students from the control class. The results of this study present the difference in the average test scores for understanding matrix algebra concepts between the experimental and control classes. The t-test showed that t-test (3.469) > t-table (1.997), with α = 0.05 (df = 67), indicating that H1 was accepted, stating that the Python-based Learning trajectory model is effective as an alternative learning strategy to strengthen students' matrix algebra conceptual understanding.
Keywords: Learning Trajectory; Python; Conceptual Understanding; Matrix Algebra
References
Bayanova, A. R., Orekhovskaya, N. A., Sokolova, N. L., Shaleeva, E. F., Knyazeva, S. A., & Budkevich, R. L. (2023). Exploring the role of motivation in STEM education: A systematic review. Eurasia Journal of Mathematics, Science and Technology Education, 19(4), em2250. https://doi.org/10.29333/ejmste/13086
Bayu, E. P. S., Fauzan, A., & Armiati. (2023). Hypothetical learning trajectory for statistical material package A level 2 based on realistic mathematic education. 060013. https://doi.org/10.1063/5.0122395
Charania, A., Bakshani, U., Paltiwale, S., Kaur, I., & Nasrin, N. (2021). Constructivist teaching and learning with technologies in the COVID‐19 lockdown in Eastern India. British Journal of Educational Technology, 52(4), 1478–1493. https://doi.org/10.1111/bjet.13111
Dewimarni, S. (2017). Kemampuan Komunikasi Dan Pemahaman Konsep Aljabar Linier Mahasiswa Universitas Putra Indonesia ‘YPTK’ Padang. Al-Jabar : Jurnal Pendidikan Matematika, 8(1), 53–62. https://doi.org/10.24042/ajpm.v8i1.763
Dewimarni, S., Rizalina, R., & Erdriani, D. (2024). Development of Basic Mathematics Modules Based on Professional Competencies. QALAMUNA: Jurnal Pendidikan, Sosial, Dan Agama, 16(1), 183–192. https://doi.org/10.37680/qalamuna.v16i1.4532
Firmasari, S., Tatang Herman, & Elah Nurlaelah. (2024). The evolution of Indonesian curriculum: Hypothetical learning trajectory for mastery of mathematical and computational thinking. JRAMathEdu (Journal of Research and Advances in Mathematics Education). https://doi.org/10.23917/jramathedu.v8i4.2116
Gultom, G. A., Simatupang, D. A., Gita, S., Purba, A., Rumapea, M. S., Voni, C., & Sinaga, R. (2025). Resistensi Mahasiswa Dalam Mengatasi Kesulitan Belajar Struktur Aljabar di Universitas HKBP Nommensen Pematangsiantar. https://ejournal.as-salam.org/index.php/assalam
Harahap, A. Y. A., Syasmita, I., Annisa, L., & Akbar, F. R. (2025). MATEMATIKA DALAM PERKEMBANGAN ILMU PENGETAHUAN DAN TEKNOLOGI. AL-IRSYAD, 15(1), 136. https://doi.org/10.30829/al-irsyad.v15i1.24079
Juana, N. A., Kaswoto, J., Sugiman, S., & Hidayat, A. A. A. (2022). The Learning Trajectory of Set Concept Using Realistic Mathematics Education (RME). Jurnal Pendidikan Matematika, 17(1), 89–102. https://doi.org/10.22342/jpm.17.1.19077.89-102
Manzano-León, A., Camacho-Lazarraga, P., Guerrero-Puerta, M. A., Guerrero-Puerta, L., Alias, A., Aguilar-Parra, J. M., & Trigueros, R. (2021). Development and Validation of a Questionnaire on Motivation for Cooperative Playful Learning Strategies. International Journal of Environmental Research and Public Health, 18(3), 960. https://doi.org/10.3390/ijerph18030960
Mitchell J. Nathan. (2023). WELCOME TO THE WORLD OF MATHEMATICS -- WHERE ANYTHING IS POSSIBLE! ¡BIENVENIDO AL MUNDO DE LAS MATEMÁTICAS, DONDE TODO ES POSIBLE! (Vol. 1).
Muthmainnah, S., Fatmawati, L., Krismilah, T., Hartini, S., Tegalrejo, S., Ahmad Dahlan, U., & Pakel, S. (2021). Peningkatan Motivasi dan Hasil Belajar melalui Pemanfaatan Lingkungan Sekitar sebagai Sumber Belajar Siswa Kelas 3B SDN Tegalrejo 3 Yogyakarta.
Nur, R., Azzahra, aini, & Suryadi, D. (2024). SYSTEMATIC LITERATURE REVIEW: KESULITAN BELAJAR PADA MATERI MATRIKS TINGKAT SMA SAMPAI PERGURUAN TINGGI (Vol. 10).
Oliphant, T. E. . (2015). Guide to NumPy. Published by Continuum Press, a division of Continuum Analytics, Inc.
Puspitasari, B., & Rayungsari, M. (2024). Systematic Literature Review: Penerapan Media Pembelajaran Matematika Berbasis Teknologi. Polinomial : Jurnal Pendidikan Matematika, 3(2), 81–89. https://doi.org/10.56916/jp.v3i2.891
Putra Hatoguan, I., & Musllim Karo Karo, I. (2025). KAJIAN KONSEPTUAL MATRIKS SEBAGAI STRUKTUR DASAR DALAM ALJABAR LINEAR. JATI (Jurnal Mahasiswa Teknik Informatika), 9(3), 5325–5329. https://doi.org/10.36040/jati.v9i3.14172
Putra, Z. H., Afrillia, Y. M., Dahnilsyah, & Tjoe, H. (2023). Prospective elementary teachers’ informal mathematical proof using GeoGebra: The case of 3D shapes. Journal on Mathematics Education, 14(3), 449–468. https://doi.org/10.22342/jme.v14i3.pp449-468
Rais, D., & Zhao, X. (2024). Elevating student engagement and academic performance: A quantitative analysis of Python programming integration in the Merdeka Belajar curriculum. Journal on Mathematics Education, 15(2), 495–516. https://doi.org/10.22342/jme.v15i2.pp495-516
Riastuti, A., Dadang Juandi, & Didi Suryadi. (2023). KECENDERUNGAN HASIL TENTANG PENELITIAN LEARNING OBSTACLE PADA MATERI ALJABAR DALAM SEPULUH TAHUN TERAKHIR. Jurnal Math-UMB.EDU, 10(3), 134–142. https://doi.org/10.36085/mathumbedu.v10i3.5261
Rosadi, A., Qomaruzzaman, B., & Zaqiah, Q. Y. (2023). Inovasi Pembelajaran Media Video Edukasi Sebagai Upaya Meningkatkan Efikasi Diri Pada Mata Pelajaran PAI. Jurnal Educatio FKIP UNMA, 9(4), 1876–1883. https://doi.org/10.31949/educatio.v9i4.6222
sugiyono. (2013). METODE PENELITIAN KUANTITATIF, KUALITATIF DAN R &. D.
Sulhaliza, A. P., Ermawati, D., & Setiawaty, R. (2025). Penerapan Model PBL Berbantuan Media Augmented Reality Terhadap Kemampuan Pemecahan Masalah Matematis Siswa. Absis: Mathematics Education Journal, 7(1), 57–66. https://doi.org/10.32585/absis.v7i1.6528
Surbakti, N. M., Angelyca Angelyca, Anita Talia, Cecilia Br Perangin-Angin, Dina Olivia Nainggolan, Nia Devi Friskauly, & Sikap Ruth Br Tumorang. (2024). Penggunaan Bahasa Pemrograman Python dalam Pembelajaran Kalkulus Fungsi Dua Variabel. Algoritma : Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian Dan Angkasa, 2(3), 98–107. https://doi.org/10.62383/algoritma.v2i3.67
Wardani, R., Zakaria, M., Priyanto, P., Luthfi, M. I., Rochmah, I. N., Rahman, A. F., & Putra, M. T. M. (2022). An Authentic Learning Approach to Assist the Computational Thinking in Mathematics Learning for Elementary School. Elinvo (Electronics, Informatics, and Vocational Education), 6(2), 139–148. https://doi.org/10.21831/elinvo.v6i2.47251
Zapatera Llinares, A. (2022). Prospective Teachers’ Use of Conceptual Advances of Learning Trajectories to Develop Their Teaching Competence in the Context of Pattern Generalization. Mathematics, 10(12), 1974. https://doi.org/10.3390/math10121974
