Optimizing Mathematical Problem-Solving Skills through Brain-Based Learning: A Neuro-Pedagogical Perspective
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Background. Mathematical problem-solving requires complex cognitive processes that integrate reasoning, executive function, and emotional regulation. Persistent gaps in students’ performance suggest that conventional instructional approaches often fail to align with the brain’s natural learning mechanisms.
Purpose. This study aims to examine the effectiveness of Brain-Based Learning (BBL) in optimizing mathematical problem-solving skills from a neuro-pedagogical perspective.
Method. A quasi-experimental pretest–posttest control group design was employed involving 64 Grade 8 students divided into experimental and control groups. The intervention was conducted over eight weeks and integrated neuroscience-informed strategies emphasizing emotional safety, multisensory engagement, distributed practice, and metacognitive reflection. Data were collected through validated problem-solving tests, working memory assessments, and mathematics anxiety questionnaires.
Results. Inferential statistical analyses revealed significant improvements in problem-solving performance in the experimental group compared to the control group (p < 0.001), with large effect sizes. Working memory capacity increased and mathematics anxiety significantly decreased among students exposed to Brain-Based Learning strategies. The findings indicate that neuro-aligned instructional design enhances both cognitive processing and affective readiness, leading to substantial gains in higher-order mathematical reasoning.
Conclusion. The study concludes that Brain-Based Learning provides an evidence-based pedagogical framework capable of optimizing mathematical problem-solving performance in contemporary classrooms.
Ar?kan, A. (2026). A longitudinal study on pre-service teachers’ spatial thinking skills and spatial anxiety. Thinking Skills and Creativity, 60, 102101. https://doi.org/10.1016/j.tsc.2025.102101
Bach, K. M., Hofer, S. I., & Bichler, S. (2025). Adaptive learning, instruction, and teaching in schools: Unraveling context, sources, implementation, and goals in a systematic review. Learning and Individual Differences, 124, 102781. https://doi.org/10.1016/j.lindif.2025.102781
Bobrowicz, K., López-Pernas, S., Teuber, Z., Saqr, M., & Greiff, S. (2024). Prospects in the field of learning and individual differences: Examining the past to forecast the future using bibliometrics. Learning and Individual Differences, 109, 102399. https://doi.org/10.1016/j.lindif.2023.102399
Chen, M. (2025). Out-of-class support for the flipped language classroom: Using VoiceThread microlectures to boost active teaching and learning. System, 132, 103723. https://doi.org/10.1016/j.system.2025.103723
Citraro, S., Haim, E., Carini, A., Siew, C. S. Q., Rossetti, G., & Stella, M. (2026). SpreadPy: A Python tool for modelling spreading activation and superdiffusion in cognitive multiplex networks. Computers in Human Behavior Reports, 21, 100940. https://doi.org/10.1016/j.chbr.2026.100940
Cosentino, G., Anton, J., Sharma, K., Gelsomini, M., Giannakos, M., & Abrahamson, D. (2025). Exploring children’s embodied interactions through digitally facilitated enactment: A case study when math education MOVES. International Journal of Human-Computer Studies, 201, 103509. https://doi.org/10.1016/j.ijhcs.2025.103509
da Costa, D. I., de Souza, R. V., & Fiamoncini, T. C. (2026). The role of neuropsychological assessment in the investigation of neurodevelopmental disorders. Jornal de Pediatria, 102, 101470. https://doi.org/10.1016/j.jped.2025.101470
de Barros, R., Resende, L. M., & Pontes, J. (2025). Exploring creativity and innovation in organizational contexts: A systematic review and bibliometric analysis of key models and emerging opportunities. Journal of Open Innovation: Technology, Market, and Complexity, 11(2), 100526. https://doi.org/10.1016/j.joitmc.2025.100526
Dubinsky, J. M., & Hamid, A. A. (2024). The neuroscience of active learning and direct instruction. Neuroscience & Biobehavioral Reviews, 163, 105737. https://doi.org/10.1016/j.neubiorev.2024.105737
Espinoza-Ortiz, A. A., & Guerrero-Jiménez, K. M. (2026). Executive functions and mathematics performance in primary school students: A systematic review. International Journal of Educational Research Open, 10, 100562. https://doi.org/10.1016/j.ijedro.2025.100562
Flanagan, D. P. (2025). Chapter 3—Clinical reasoning and decision-making for specific learning disabilities. Dalam J. J. W. Andrews & D. H. Saklofske (Ed.), Clinical Reasoning and Decision-Making Process (hlm. 41–148). Academic Press. https://doi.org/10.1016/B978-0-443-13552-1.00014-X
Furnham, A. (2025). Personality and the education process: Individual difference preferences for teacher, technology, testing, time and topic. Learning and Individual Differences, 119, 102637. https://doi.org/10.1016/j.lindif.2025.102637
Gómez-Ochoa de Alda, J. A., Marcos-Merino, J. M., Valares-Masa, C., & Esteban-Gallego, M. R. (2025). Anticipatory emotions and academic performance: The role of boredom in a preservice teachers’ lab experience. Heliyon, 11(1), e41142. https://doi.org/10.1016/j.heliyon.2024.e41142
Guerrero, S., Valenciano-Valcárcel, J., & Rodríguez, A. (2024). Unveiling alternative schools: A systematic review of cognitive and social-emotional development in different educational approaches. Children and Youth Services Review, 158, 107480. https://doi.org/10.1016/j.childyouth.2024.107480
Huang, D., Hash, N., Cummings, J. J., & Prena, K. (2025). Academic cheating with generative AI: Exploring a moral extension of the theory of planned behavior. Computers and Education: Artificial Intelligence, 8, 100424. https://doi.org/10.1016/j.caeai.2025.100424
Immordino-Yang, M. H., Kundrak, C., Knecht, D., & Matthews, J. (2024). Civic reasoning depends on transcendent thinking: Implications of adolescent brain development for SEL. Social and Emotional Learning: Research, Practice, and Policy, 4, 100067. https://doi.org/10.1016/j.sel.2024.100067
Ismail, S. A. S., Maat, S. M., & Khalid, F. (2025). From numbers to nerves: A score year of scientometric study on mathematics anxiety. Acta Psychologica, 260, 105621. https://doi.org/10.1016/j.actpsy.2025.105621
Jarutkamolpong, S., & Kwangmuang, P. (2025). Enhancing undergraduate creative thinking through a constructivist mobile learning application: Design, development, and evaluation. Thinking Skills and Creativity, 57, 101866. https://doi.org/10.1016/j.tsc.2025.101866
Kaur, V. (2024). Neurostrategy: A scientometric analysis of marriage between neuroscience and strategic management. Journal of Business Research, 170, 114342. https://doi.org/10.1016/j.jbusres.2023.114342
Kokubun, K., Nemoto, K., & Yamakawa, Y. (2025). The brain that understands different cultures: MRI-measured brain structure correlates with cultural intelligence. Acta Psychologica, 258, 105166. https://doi.org/10.1016/j.actpsy.2025.105166
Le Cunff, A.-L., Giampietro, V., & Dommett, E. (2024). Neurodiversity and cognitive load in online learning: A systematic review with narrative synthesis. Educational Research Review, 43, 100604. https://doi.org/10.1016/j.edurev.2024.100604
Li, H., & Wu, H. (2025). Looking to the past for mapping the future: A bibliometric review of extant creativity research in second language education. Acta Psychologica, 257, 105138. https://doi.org/10.1016/j.actpsy.2025.105138
Li, S., Wang, T., Zheng, J., & Lajoie, S. P. (2025). A complex dynamical system approach to student engagement. Learning and Instruction, 98, 102120. https://doi.org/10.1016/j.learninstruc.2025.102120
Morrison, L., & Hughes, J. (2024). Promising practices for online professional learning. Computers and Education Open, 7, 100209. https://doi.org/10.1016/j.caeo.2024.100209
O?uz, S. N., P?nar, Y., Bodur, D., & Ertunç, A. (2026). Extroversion and emotional well-being in unstructured compared to structured preschool environments: Three case studies. Acta Psychologica, 264, 106443. https://doi.org/10.1016/j.actpsy.2026.106443
Rapaport, H., & Sowman, P. F. (2024). Examining predictive coding accounts of typical and autistic neurocognitive development. Neuroscience & Biobehavioral Reviews, 167, 105905. https://doi.org/10.1016/j.neubiorev.2024.105905
Ruscica, P., Daxberger, H., Resch, G., Hadzovic, A., Dalili, S., & Arhonditsis, G. B. (2026). Transforming education and research with extended reality technologies: How virtual reality can shape the future of data interactions in earth and environmental sciences. Ecological Informatics, 93, 103535. https://doi.org/10.1016/j.ecoinf.2025.103535
Senge, P. M., Cook, L., Kitil, M. J., Schonert-Reichl, K. A., Clinton, J. M., Boell, M., Martin, J. S., & Ruddy, C. (2025). Developing children’s innate systems intelligence to enhance social and emotional learning. Social and Emotional Learning: Research, Practice, and Policy, 6, 100167. https://doi.org/10.1016/j.sel.2025.100167
Singh, D., Mishra, A., & Aggarwal, A. (2025). An empirical approach to investigate the impact of technical and non-technical parameters on programmers’ code comprehension proficiency. Expert Systems with Applications, 286, 127988. https://doi.org/10.1016/j.eswa.2025.127988
Suksasilp, C., Friston, K., & Garfinkel, S. (2025). Computational modeling and autonomic control. Dalam J. H. Grafman (Ed.), Encyclopedia of the Human Brain (Second Edition) (hlm. 245–266). Elsevier. https://doi.org/10.1016/B978-0-12-820480-1.00076-0
Tan, L. Y., Hu, S., Yeo, D. J., & Cheong, K. H. (2025). Artificial intelligence-enabled adaptive learning platforms: A review. Computers and Education: Artificial Intelligence, 9, 100429. https://doi.org/10.1016/j.caeai.2025.100429
Wang, D., Tao, Y., & Chen, G. (2024). Artificial intelligence in classroom discourse: A systematic review of the past decade. International Journal of Educational Research, 123, 102275. https://doi.org/10.1016/j.ijer.2023.102275
Wang, L., Luo, G., Yang, J., Zhang, W., Yang, P., Sun, B., Liang, Z., & Wang, D. (2026). A reading model of English as a foreign language accommodated by programming-oriented computational thinking: An interdisciplinary approach. Thinking Skills and Creativity, 61, 102162. https://doi.org/10.1016/j.tsc.2026.102162
Zhang, J., Oh, S.-S., & Xu, Y. (2026). Gamified Physical Education and Cognitive Performance Among Chinese Secondary School Students: Cross-Sectional Moderation Mediation Study. JMIR Serious Games, 14. https://doi.org/10.2196/81086
Zhang, J., Wang, Y., Leong, C., Mao, Y., & Yuan, Z. (2024). Bridging Stories and Science: An fNIRS-based hyperscanning investigation into child learning in STEM. NeuroImage, 285, 120486. https://doi.org/10.1016/j.neuroimage.2023.120486
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