Application of geogebra in online learning for pattern recognition skills in analytical geometry courses
DOI:
https://doi.org/10.22460/jpmi.v9i1s.31189Keywords:
Presenter pada International Conference ISAMME 2026Abstract
This study aims to analyze the effect of GeoGebra implementation in online learning on students' pattern recognition skills in Analytical Geometry courses. This study used a quantitative method with a quasi-experimental design. Participants were students enrolled in an online Analytical Geometry class. The subjects taken were one class. The instruments used included a pattern recognition ability test consisting of 3 questions and an observation sheet for learning activities. Pattern recognition indicators are recognizing patterns, similarities, and connections. The results showed a significant effect of GeoGebra implementation on students' pattern recognition skills. The effect size calculation results showed a score of 0.99, which is included in the very large category. The overall mean score was 82.47 and the standard deviation was 7.12. The use of GeoGebra effectively helped students visualize abstract geometric concepts. Digital visualization through GeoGebra minimizes inaccuracies that often occur when drawings are created manually, thus enabling students to identify geometric patterns and regularities more clearly. Therefore, integrating GeoGebra into online learning not only improves conceptual understanding but also strengthens students' ability to recognize mathematical patterns in Analytical Geometry
References
Arslan, M., & Zunlu, H. M. (2020). The effects of GeoGebra supported flipped classroom model on pre-service teachers’ self-efficacy and achievement in analytic geometry. International Journal of Mathematical Education in Science and Technology, 51(3), 405–424.
Barrón-Estrada, M. L., Zatarain-Cabada, R., Romero-Polo, J. A., & Monroy, J. N. (2022). Patrony: A mobile application for pattern recognition learning. Education and Information Technologies, 27(1), 1237–1260. https://doi.org/10.1007/s10639-021-10636-7
Dasgupta, A., & Purzer, S. (2016). No patterns in pattern recognition: A systematic literature review. Proceedings - Frontiers in Education Conference, FIE, 2016-November. https://doi.org/10.1109/FIE.2016.7757676
Fauzi, A. L., Kusumah, Y. S., Nurlaelah, E., & Juandi, D. (2025). Computational thinking education in K-12 artificial intelligence literacy and physical computing: edited by Siu-Cheung Kong and Harold Abelson, Cambridge, The MIT Press, 2022, 288 pp., $60.00 (paperback), ISBN: 9780262543477. Taylor & Francis.
Ioannis Rizos, N. G. (2024). Pattern recognition among primary school students: The relationship with mathematical problem-solving. Contemporary Mathematics and Science Education, 5(2), ep24010. https://doi.org/https://doi.org/10.30935/conmaths/14689
Lehmann, T. (2024). Computational problem solving in STEM education. In Ways of Thinking in STEM-based Problem Solving: Teaching and Learning in a New Era (pp. 235–249). https://doi.org/10.4324/9781003404989-17
Lins, R., & Meira, L. (2022). The role of functional thinking in the teaching and learning of mathematics. Journal for Research in Mathematics Education (JRME), 53(3), 251–268.
Llinares, A. Z. (2022). Prospective Teachers’ Use of Conceptual Advances of Learning Trajectories to Develop Their Teaching Competence in the Context of Pattern Generalization. Mathematics, 10(12). https://doi.org/10.3390/math10121974
Panaoura, A., & Panaoura, G. (2021). Examining the effect of visuospatial abilities and pattern recognition in mathematical achievement. Early Childhood Education Journal, 49(4), 543–554.
Pinto, G., Peixoto, F., & Leite, A. (2020). Pattern Generalization in Pre-service Teachers: The Role of Problem-Solving Strategies and Cognitive Variables. International Journal of Science and Mathematics Education, 18(3), 473–494.
Polledo, E., Garaizar, P., & Guenaga, M. (2021). Lempel: Developing the pattern recognition skill in computational thinking through an online educational game. CEUR Workshop Proceedings, 3029, 28–37. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121292379&partnerID=40&md5=8551ebdf68ec55dfa9dc4332efd5d1cb
Rachmi, E. B., Mahendra, I., Purnomo, A., & Budi, M. (2023). Student’s Computational Thinking: Focusing on Decomposition and Pattern Recognition in Solving Mathematical Problems. International Journal of Education in Mathematics, Science and Technology (IJEMST), 11(2), 295–311.
Rosmiati, N. N., & Fajariyah, A. (2023). The effect of using Geogebra learning media on students’ conceptual understanding during online learning. International Journal of Education in Mathematics, Science and Technology (IJEMST), 11(3), 577–589.
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/https://doi.org/10.1016/j.edurev.2017.09.003
Yasin, M., & Nusantara, T. (2023). Characteristics of Pattern Recognition to Solve Mathematics Problems in Computational Thinking. AIP Conference Proceedings, 2569. https://doi.org/10.1063/5.0112171
Zulnaidi, H., & Zakaria, E. (2022). The effect of GeoGebra on students’ achievement and conceptual understanding in learning vectors. Eurasia Journal of Mathematics, Science and Technology Education (EJMSTE), 18(1).
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The author is responsible for acquiring the permission(s) to reproduce any copyrighted figures, tables, data, or text that are being used in the submitted paper. Authors should note that text quotations of more than 250 words from a published or copyrighted work will require grant of permission from the original publisher to reprint. The written permission letter(s) must be submitted together with the manuscript.Article Metrics
Abstract view : 0 timesPDF - 1413 times















