The Fascinating Connection between Neuroscience and Mathematical Learning
DOI:
https://doi.org/10.37843/rted.v18i1.630
Article Sidebar
Main Article Content
Abstract
Neuroscience studies the nervous system and brain, offering valuable insights into how mathematics is learned and taught. This study aimed to analyze which brain regions are activated and how they relate to mathematical learning, brain plasticity, and the impact of emotional factors on mathematical connections. The research employed a systematic methodology, a qualitative approach, and a naturalistic paradigm. It used a topical narrative design, focusing on a single topic, and a bibliographic documentary approach, drawing on existing documentary sources. The databases were Scopus, ScienceDirect, EBSCO, Web of Science, and ProQuest; the PRISMA 2020 method was applied. The articles found were mostly in English, published between 2020 and 2024, and were available for open access. Eighteen publications were finalized for analysis. Key findings include cortical anatomy, early mathematical skills, and the activation of brain regions in the frontal, intraparietal, and temporal areas. The research highlights the relevance of neuroscience in mathematics learning. It delves into the importance of brain plasticity, the activation of specific brain areas, and emotional factors in the educational process. It emphasizes the need to incorporate neuroscientific discoveries into pedagogical practice to improve the teaching and learning of mathematics. It also emphasizes understanding subjective experiences and using playful strategies to learn mathematics.
Downloads
Metrics
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Those authors who have publications in our journal accept the following terms:
- When a work is accepted for publication, the author retains rights of reproduction, distribution of his/her article for exploitation in all countries of the world in the format provided by our magazine and any other magnetic medium, optical, and digital.
- Authors will retain their copyright and guarantee the journal the right first to publish their work, which will be simultaneously subject to the Creative Commons Acknowledgment License (Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)). That allows third parties to copy and redistribute the material in any medium or format, under the following conditions: Acknowledgment - You must properly acknowledge authorship, provide a link to the license, and indicate if any changes have been made. You may do so in any reasonable way, but not in a way that suggests you have the licensor's endorsement or receive it for your use. NonCommercial - You may not use the material for a commercial purpose. NoDerivatives - If you remix, transform, or build from the material, you cannot broadcast the modified material. There are no additional restrictions - You cannot apply legal terms or technological measures that legally restrict you from doing what the license allows.
- Authors may adopt other non-exclusive license agreements to distribute the published version of the work (e.g., deposit it in an institutional archive or publish it in a monographic volume) provided that the initial publication in this journal is indicated.
- Authors are allowed and recommended to disseminate their work through the Internet (e.g., in institutional telematic archives, repositories, libraries, or their website), producing exciting exchanges and increasing the published work's citations.
- Request of withdrawal an article has to be done in writing by the author to the Editor, becoming effective after a written response from the Editor. For this purpose, the author or authors will send correspondence via e-mail: [email protected].
- The author will not receive financial compensation for the publication of his work.
- All Docentes 2.0 Journal publications are under the Open Journal System (OJS) platform at: https://ojs.docentes20.com/.
References
Abu Bakar, M. A., & Ab Ghani, A. T. (2022). The impact of neuroscience literacy on sustainability of the students’ mathematics learning environment. Journal of Sustainability Science and Management, 17(9), 148–161. https://n9.cl/g309f DOI: https://doi.org/10.46754/jssm.2022.09.010
Acosta-Faneite, S. F. (2023). Los enfoques de investigación en las ciencias sociales. Revista Latinoamericana Ogmios, 3(8), 82–95. https://doi.org/10.53595/rlo.v3.i8.084 DOI: https://doi.org/10.53595/rlo.v3.i8.084
Álvarez-Vargas, D., Begolli, K. N., Choc, M., Acevedo-Farag, L. M., Bailey, D. H., Richland, L., & Bustamante, A. (2024). Fraction Ball impact on student and teacher math talk and behavior. Journal of Experimental Child Psychology, 241, 105777. https://doi.org/10.1016/j.jecp.2023.105777 DOI: https://doi.org/10.1016/j.jecp.2023.105777
Amalric, M., & Cantlon, J. F. (2022). Common neural functions during children's learning from naturalistic and controlled mathematics paradigms. Journal of Cognitive Neuroscience, 34, 1-19. https://doi.org/10.1162/jocn_a_01848 DOI: https://doi.org/10.1101/2022.01.07.475365
Antonopoulou, H., Halkiopoulos, C., & Gkintoni, E. (2023). Educational neuroscience and its contribution to math learning. Technium Education and Humanities, 4(1), 86–87. https://doi.org/10.47577/teh.v4i.8237 DOI: https://doi.org/10.47577/teh.v4i.8237
Ayala, A. (2023). Efecto de un programa de intervención neuropsicológica en el desarrollo de las habilidades académicas en los primeros años escolares. Propósitos y Representaciones, 11(3), e1876. https://doi.org/10.20511/pyr2023.v11n3.1876 DOI: https://doi.org/10.20511/pyr2023.v11n3.1876
Bonilla-Zambrano, M. V., Rivadeneira-Barreiro, L., & Rivadeneira-Barreiro, M. P. (2024). Importancia de las estrategias didácticas basadas en neuroeducación para mejorar el aprendizaje significativo en la asignatura de matemáticas. MQRInvestigar, 8(3), 297–321. https://doi.org/10.56048/mqr20225.8.3.2024.297-321 DOI: https://doi.org/10.56048/MQR20225.8.3.2024.297-321
Branchi, I. (2023). A mathematical formula of plasticity: Measuring susceptibility to change in mental health and data science. Neuroscience & Biobehavioral Reviews, 152, 105272. https://doi.org/10.1016/j.neubiorev.2023.105272 DOI: https://doi.org/10.1016/j.neubiorev.2023.105272
Borg, C., & Muñoz Martín, R. (2024). Investigación cualitativa naturalista. University of Malta Library. https://n9.cl/3rq1w
Bueno, D., & Forés, A. (2021). Neurociència aplicada a l’educació. Com. Llengua, Societat i Comunicació, (19), 10. https://doi.org/10.1344/LSC-2021.19.10 DOI: https://doi.org/10.1344/LSC-2021.19.10
Caballero-Cobos, M., & Llorent, V. J. (2022). Los efectos de un programa de formación docente en neuroeducación en la mejora de las competencias lectoras, matemática, socioemocionales y morales de estudiantes de secundaria. Un estudio cuasi-experimental de dos años. Revista de Psicodidáctica, 27(2), 158–167. https://doi.org/10.1016/j.psicod.2022.04.001 DOI: https://doi.org/10.1016/j.psicod.2022.04.001
Cohen, L., & Rubinsten, O. (2022). Handbook of cognitive mathematics. Elsevier.
Gashaj, V., Trnini?, D., Formaz, C., Tobler, S., Gómez Cañón, J. S., Poikonen, H., & Kapur, M. (2024). Bridging cognitive neuroscience and education: Insights from EEG recording during mathematical proof evaluation. Trends in Neuroscience and Education, 35, 100226. https://doi.org/10.1016/J.TINE.2024.100226 DOI: https://doi.org/10.1016/j.tine.2024.100226
Goswami, U. (2004). Neuroscience and education. British Journal of Educational Psychology, 74(1), 1–14. https://doi.org/10.1111/j.0952-3383.2004.00352.x DOI: https://doi.org/10.1111/j.0952-3383.2004.00352.x
Gur, T., Balta, N., Dauletkulova, A., Assanbayeva, G., & Fernández-Cézar, R. (2023). Mathematics achievement emotions of high school students in Kazakhstan. Journal on Mathematics Education, 14(3), 525–544. https://doi.org/10.22342/jme.v14i3.pp525-544 DOI: https://doi.org/10.22342/jme.v14i3.pp525-544
Henning, S., Xie, Y., Zhang, H., & Diedrichsen, J. (2021). How learning unfolds in the brain: Toward an optimization view. Neuron, 109(24), 3720–3731. DOI: https://doi.org/10.1016/j.neuron.2021.09.005
Hernández Sampieri, R., & Mendoza Torres, C. (2018). Metodología de la investigación (2a ed.). McGraw-Hill.
Khabsa, J., et al. (2023). Conceptualizing the reporting of living systematic reviews. Journal of Clinical Epidemiology, 156, 113–118. https://doi.org/10.1016/j.jclinepi.2023.01.008 DOI: https://doi.org/10.1016/j.jclinepi.2023.01.008
Kuhl, U., Friederici, A. D., Skeide, M. A., Friederici, A. D., Emmrich, F., Brauer, J., Wilcke, A., Neef, N., Boltze, J., Skeide, M., Kirsten, H., Schaadt, G., Müller, B., Kraft, I., Czepezauer, I., & Dörr, L. (2020). Early cortical surface plasticity relates to basic mathematical learning. NeuroImage, 204, 116235. https://doi.org/10.1016/j.neuroimage.2019.116235 DOI: https://doi.org/10.1016/j.neuroimage.2019.116235
Lázaro, G. (2022). Principios del cerebro para el aprendizaje. ResearchGate. https://doi.org/10.13140/RG.2.2.32995.02088
Lin, P., Zhou, X., Zang, S., Zhu, Y., Zhang, L., Bai, Y., & Wang, H. (2023). Early neural markers for individual difference in performance. Neuropsychologia, 181, 108493. https://doi.org/10.1016/j.neuropsychologia.2023.108493 DOI: https://doi.org/10.1016/j.neuropsychologia.2023.108493
Letelier Galvez, M. (2020). La comprensión del cerebro y la educación de personas jóvenes y adultas. Estudios Pedagógicos, 46(2), 177–190. https://doi.org/10.4067/S0718-07052020000200177 DOI: https://doi.org/10.4067/S0718-07052020000200177
Méndez López, D. E., & González Santos, G. A. (2022). Neurociencia aplicada a la enseñanza-aprendizaje de la matemática en el ciclo básico. Revista Académica Sociedad Del Conocimiento Cunzac, 2(2), 211–215. https://doi.org/10.46780/sociedadcunzac.v2i2.46 DOI: https://doi.org/10.46780/sociedadcunzac.v2i2.46
Méndez-Mantuano, M. O., Macías, J. L. A., Valdez, A. Y. L., Flores, J. L. M., & Yuqui, C. E. P. (2020). Aplicación de la metodología neuroestimuladora en la enseñanza de las matemáticas. European Scientific Journal ESJ, 16(22). https://doi.org/10.19044/esj.2020.v16n22p52 DOI: https://doi.org/10.19044/esj.2020.v16n22p52
Menon, V., & Chang, H. (2021). Emerging neurodevelopmental perspectives on mathematical learning. Developmental Review, 60, 100964. https://doi.org/10.1016/j.dr.2021.100964 DOI: https://doi.org/10.1016/j.dr.2021.100964
Merrick, M., & Field, E. R. (2023). Feelings on feedback: Children’s emotional responses during mathematics problem solving. Contemporary Educational Psychology, 74. https://doi.org/10.1016/j.cedpsych.2023.102209 DOI: https://doi.org/10.1016/j.cedpsych.2023.102209
Muñoz Sánchez, Y., Castillo Pérez, I., & Rivera González, M. I. (2025). Método de Investigación Cualitativo. Ingenio y Conciencia Boletín Científico de la Escuela Superior Ciudad Sahagún, 12(23), 125-127. https://doi.org/10.29057/escs.v12i23.13781 DOI: https://doi.org/10.29057/escs.v12i23.13781
Nieder, A. (2024). The calculating brain. Physiological Reviews. https://doi.org/10.1152/physrev.00014.2024 DOI: https://doi.org/10.1152/physrev.00014.2024
Nieto-Bravo, J. A., Pérez-Vargas, J. J., & Moncada-Guzmán, C. J. (2022). Métodos narrativos en investigación social y educativa. Revista de Ciencias Sociales (Ve), 29(1), 215–226. https://n9.cl/o54icv
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). 1 The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(n71). https://doi.org/10.1136/bmj.n71 DOI: https://doi.org/10.1136/bmj.n71
Poikonen, H., Zaluska, T., Wang, X., Magno, M., & Kapur, M. (2023). Nonlinear and machine learning analyses on high density EEG data of math experts and novices Scientific Reports, 13(8012). https://doi.org/10.1038/s41598-023-35032-8 DOI: https://doi.org/10.1038/s41598-023-35032-8
Soto-Cerros, S., García-González, M. d. S., & Pascual-Martín, M. I. (2023). La relación entre el Dominio Afectivo y el modelo MTSK: una oportunidad de investigación. Educación Matemática, 35(2), 226–246. https://doi.org/10.24844/em3502.09 DOI: https://doi.org/10.24844/EM3502.09
Suárez, M., Prado, J., & Booth, J. (2022). Neurocognitive mechanisms underlying multiplication and subtraction performance in adults and skill development in children: a scoping review. ScienceDirect, 48, 16. https://doi.org/10.1016/j.cobeha.2022.101228 DOI: https://doi.org/10.1016/j.cobeha.2022.101228
Van der Beek, J. P. J., Van der Ven, S. H. G., Kroesbergen, E. H., & Leseman, P. P. M. (2024). How emotions are related to competence beliefs during mathematical problem solving: Differences between boys and girls. Learning and Individual Differences, 109, 102402. https://doi.org/10.1016/j.lindif.2023.102497 DOI: https://doi.org/10.1016/j.lindif.2023.102402
Wilkey, E. D., Gupta, I., Peiris, A., & Ansari, D. (2023). The mathematical brain at rest. Current Opinion in Behavioral Sciences, 49(1), 101246. https://doi.org/10.1016/j.cobeha.2022.101246 DOI: https://doi.org/10.1016/j.cobeha.2022.101246
Únete a nuestro canal de Telegram para recibir notificaciones de nuestras publicaciones
